text stringlengths 38 1.54M |
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import numpy as np, matplotlib.pyplot as plt
d = np.load('2457548.45923.npz')
NOT_REAL_ANTS="0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 66, 67, 68, 69, 70, 71, 73, 74, 75, 76, 77, 78, 79, 82, 83, 84, 85, 86, 87, 90, 91, 92, 93, 94, 95, 98, 99, 100, 101, 102, 103, 106, 107, 108, 109, 110, 111"
ex_ants = [int(a) for a in NOT_REAL_ANTS.split(', ')]
keep_ants = [a for a in range(d['gains'].shape[2]) if a not in ex_ants]
good_ants = [a for a in keep_ants if a not in [81,22,43]]
low = list(range(0,102))
orbcomm = list(range(375,390))
others = list(range(695,705))+list(range(759,761))+list(range(768,771))+list(range(830,832))+list(range(850,852))+list(range(921,1023))
others+=[510,511,512,850,851,852,853,854]
msk=low+orbcomm+others
msk_spec = np.zeros((1024))
good_chans = [c for c in range(1024) if c not in msk]
freqs = np.linspace(100,200,num=1024)
for c in range(1024):
if c in good_chans:
msk_spec[c] = 1
f,ax = plt.subplots()
ax.fill_between(freqs[202:301],0,3, facecolor='k',alpha=0.2)
ax.fill_between(freqs[581:681],0,3,facecolor='k',alpha=0.2)
for i,a in enumerate(good_ants):
if a==80:
continue
if i <= 8:
ls='-'
else:
ls='--'
msk_gain = np.ma.masked_where(np.abs(d['gains'][0,:,a])*msk_spec==0.,
d['gains'][0,:,a])
#ax.plot(np.fft.fftshift(np.fft.fftfreq(1024,np.diff(freqs)[0]*1e6))*1e9,
# np.abs(np.fft.fftshift(np.fft.ifft(msk_gain))),
# ls,label=str(a),lw=2)
ax.plot(freqs,np.abs(msk_gain),ls,label=str(a),lw=2)
ax.set_ylim(0,2.75)
#ax.set_ylim(-np.pi,np.pi)
#ax.set_xlim(100,200)
#plt.legend()
#plt.xlabel('Frequency [MHz]',size=12)
plt.ylabel('Amplitude [arb.]',size=12)
plt.grid()
plt.show()
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"""
This problem was asked by Amazon.
Run-length encoding is a fast and simple method of encoding strings.
The basic idea is to represent repeated successive characters
as a single count and character.
For example, the string "AAAABBBCCDAA" would be encoded as "4A3B2C1D2A".
Implement run-length encoding and decoding.
You can assume the string to be encoded have no digits and consists
solely of alphabetic characters.
You can assume the string to be decoded is valid.
"""
import unittest
def encode(s: str) -> str:
if not s:
return ''
counter = 1
char = s[1]
encoded = ''
for c in s[1:]:
if c is char:
counter += 1
else:
encoded += f'{counter}{char}'
char = c
counter = 1
encoded += f'{counter}{char}'
return encoded
def decode(s: str) -> str:
if not s:
return ''
counter = int(s[0])
decoded = counter * s[1]
for i, c in enumerate(s[2:]):
if i % 2 is 0:
counter = int(c)
else:
decoded += counter * c
return decoded
class TestSolution(unittest.TestCase):
def test_given_encode(self) -> None:
self.assertEqual(encode('AAAABBBCCDAA'), '4A3B2C1D2A')
def test_given_decode(self) -> None:
self.assertEqual(decode('4A3B2C1D2A'), 'AAAABBBCCDAA')
if __name__ == '__main__':
unittest.main()
|
In this kata you are required to, given a string, replace every letter with its position in the alphabet.
If anything in the text isn't a letter, ignore it and don't return it.
"a" = 1, "b" = 2, etc.
soln:
from string import ascii_lowercase
LETTERS = {letter: str(index) for index, letter in enumerate(ascii_lowercase, start=1)}
def alphabet_position(text):
text = text.lower()
numbers = [LETTERS[character] for character in text if character in LETTERS]
return ' '.join(numbers)
from string import ascii_lowercase
cap_letter = {small_letter: str(index) for index, small_letter in enumerate(ascii_lowercase, start=1)}
def alphabet_position(text):
text = text.lower()
nos = [cap_letter [char] for char in text if char in cap_letter ]
return ' '.join(nos)
other coders soln:
def alphabet_position(text):
return ' '.join(str(ord(c) - 96) for c in text.lower() if c.isalpha())
or
def alphabet_position(s):
return " ".join(str(ord(c)-ord("a")+1) for c in s.lower() if c.isalpha())
or
alphabet = 'abcdefghijklmnopqrstuvwxyz'
def alphabet_position(text):
if type(text) == str:
text = text.lower()
result = ''
for letter in text:
if letter.isalpha() == True:
result = result + ' ' + str(alphabet.index(letter) + 1)
return result.lstrip(' ')
or
from string import ascii_lowercase
def alphabet_position(text):
return ' '.join(str(ascii_lowercase.index(n.lower()) + 1) for n in text if n.isalpha())
or
import re
def alphabet_position(text):
return " ".join([str(ord(i) - 96) for i in re.findall('[a-z]', text.lower())]) |
#!/usr/bin/python3
# -*- coding: utf-8 -*-
# (C) w:fa:User:Reza1615, 2020
# (C) w:fa:User:Huji, 2020
# Distributed under the terms of the CC-BY-SA 3.0
import pywikibot
from persiantools import digits
from datetime import datetime
month_names = [
"ژانویه",
"فوریه",
"مارس",
"آوریل",
"مه",
"ژوئن",
"ژوئیه",
"اوت",
"سپتامبر",
"اکتبر",
"نوامبر",
"دسامبر"
]
summary = "ربات:ساخت رده حذف زماندار"
content = "{{جا:الگو:شروع حذف زماندار}}"
now = datetime.now()
year = digits.en_to_fa(str(now.year))
month = month_names[now.month - 1]
day = digits.en_to_fa(str(now.day))
title = 'رده:صفحههای حذف زماندار در %s %s %s' % (day, month, year)
p = pywikibot.Page(pywikibot.getSite("fa"), title)
if not p.exists():
p.put(content, summary)
|
import os.path
import shutil
import sys
import numpy as np
import gc
import tensorflow as tf
from nets import nets
from data import data
from runs import preprocessing
import pickle
def evaluate_network(opt):
# Initialize dataset and creates TF records if they do not exist
dataset = data.ImagenetDataset(opt)
# Repeatable datasets for training
val_dataset = dataset.create_dataset(set_name='val', repeat=True)
# Handles to switch datasets
handle = tf.placeholder(tf.string, shape=[])
iterator = tf.data.Iterator.from_string_handle(
handle, val_dataset.output_types, val_dataset.output_shapes)
val_iterator = val_dataset.make_initializable_iterator()
################################################################################################
################################################################################################
# Declare DNN
################################################################################################
# Get data from dataset dataset
image, label = iterator.get_next()
from tensorflow.python.client import device_lib
local_device_protos = device_lib.list_local_devices()
gpus = [x.name for x in local_device_protos if x.device_type == 'GPU']
if opt.dnn.name == 'resnet':
image_split = [tf.reshape(t, [-1, data._DEFAULT_IMAGE_SIZE, data._DEFAULT_IMAGE_SIZE, 3]) for t in
zip(tf.split(image, len(gpus)))]
elif opt.dnn.name == 'inception':
image = tf.cast(image, tf.float32)
image_split = [tf.reshape(t, [-1, 299, 299, 3]) for t in
zip(tf.split(image, len(gpus)))]
label_split = [tf.reshape(t, [-1]) for t in zip(tf.split(label, len(gpus)))]
# Call DNN
logits_list = []
for idx_gpu, gpu in enumerate(gpus):
with tf.device(gpu):
with tf.name_scope('gpu_' + str(idx_gpu)) as scope:
to_call = getattr(preprocessing, opt.dnn.name)
u_images = []
for _image in tf.unstack(image_split[idx_gpu], num=opt.hyper.batch_size / len(gpus), axis=0):
im_tmp = to_call(_image, opt)
u_images.append(im_tmp)
_images = tf.stack(u_images)
to_call = getattr(nets, opt.dnn.name)
logit, activations = to_call(_images, opt)
tf.get_variable_scope().reuse_variables()
logits_list.append(logit)
logits = tf.reshape(tf.stack(logits_list, axis=0), [-1, 1001])
pred_label = tf.argmax(logits, axis=1)
acc_1 = tf.nn.in_top_k(predictions=logits, targets=label, k=1, name='top_1_op')
acc_5 = tf.nn.in_top_k(predictions=logits, targets=label, k=5, name='top_5_op')
################################################################################################
config = tf.ConfigProto(allow_soft_placement=True)#inter_op_parallelism_threads=80,
#intra_op_parallelism_threads=80,
#
#config.gpu_options.allow_growth = True
with tf.Session(config=config) as sess:
print("RESTORE")
print(opt.log_dir_base + opt.name)
if opt.dnn.name == 'resnet':
saver = tf.train.Saver(max_to_keep=opt.max_to_keep_checkpoints)
saver.restore(sess, tf.train.latest_checkpoint(opt.log_dir_base + opt.name + '/'))
elif opt.dnn.name == 'inception':
variable_averages = tf.train.ExponentialMovingAverage(0.9999)
variables_to_restore = variable_averages.variables_to_restore()
saver = tf.train.Saver(variables_to_restore)
# saver = tf.train.Saver()
saver.restore(sess, tf.train.latest_checkpoint(opt.log_dir_base + opt.name + '/'))
'''
ckpt = tf.train.get_checkpoint_state(opt.log_dir_base + opt.name + '/')
if ckpt and ckpt.model_checkpoint_path:
if os.path.isabs(ckpt.model_checkpoint_path):
# Restores from checkpoint with absolute path.
saver.restore(sess, ckpt.model_checkpoint_path)
else:
# Restores from checkpoint with relative path.
saver.restore(sess, os.path.join(opt.log_dir_base + opt.name + '/',
ckpt.model_checkpoint_path))
'''
val_handle_full = sess.run(val_iterator.string_handle())
# Run one pass over a batch of the validation dataset.
sess.run(val_iterator.initializer)
acc_tmp_1 = 0.0
acc_tmp_5 = 0.0
total = 0
total_iter = int(dataset.num_total_images / opt.hyper.batch_size) + 1
for num_iter in range(total_iter):
acc_val_1, acc_val_5 = sess.run(
[acc_1, acc_5],
feed_dict={handle: val_handle_full})
for i in range(len(acc_val_1)):
total += 1
acc_tmp_1 += acc_val_1[i]
acc_tmp_5 += acc_val_5[i]
print('iteration:', str(num_iter) + '/' + str(total_iter-1), 'running_top-1:',
acc_tmp_1 / float(total), 'running_top-5:', acc_tmp_5 / float(total))
sys.stdout.flush()
if total > 0:
ret_acc = acc_tmp_1 / float(total)
ret_acc_5 = acc_tmp_5 / float(total)
sys.stdout.flush()
sess.close()
return ret_acc, ret_acc_5
def run(opt):
################################################################################################
# Read experiment to run
################################################################################################
# Skip execution if instructed in experiment
if opt.skip:
print("SKIP")
quit()
print('name:', opt.name)
print('factor:', opt.dnn.factor)
print('batch size:', opt.hyper.batch_size)
################################################################################################
# Define training and validation datasets through Dataset API
################################################################################################
record_acc, record_acc_5 = evaluate_network(opt)
tf.reset_default_graph()
gc.collect()
print("top-1:", record_acc)
print("top-5: ", record_acc_5)
sys.stdout.flush()
print(":)")
|
#!/bin/python3
import math
import os
import random
import re
import sys
class SinglyLinkedListNode:
def __init__(self, node_data):
self.data = node_data
self.next = None
class SinglyLinkedList:
def __init__(self):
self.head = None
def print_singly_linked_list(node, sep, fptr):
while node:
fptr.write(str(node.data))
node = node.next
if node:
fptr.write(sep)
# Complete the insertNodeAtTail function below.
#
# For your reference:
#
# SinglyLinkedListNode:
# int data
# SinglyLinkedListNode next
#
#
def insertNodeAtTail(head, data):
new_node = SinglyLinkedListNode(data)
if head==None:
head = new_node
temp = head
while(temp.next!=None):
temp = temp.next
temp.next = new_node
new_node.next = None
return head
if __name__ == '__main__': |
from scipy import signal
import numpy as np # linear algebra
import matplotlib.pyplot as plt
DeltaQ = 150 #Internal heat gain difference between day and night
#day_DeltaQ = DeltaQ #Day Delta Q internal [W]
Qday = 400 #Day internal heat gain W
nightQ = Qday - DeltaQ #Night internal heat gain
t1= 8 #Presence from [hour]
t2= 23 #Presence until [hour]
days_hours = 24 #number_of_hour_in_oneday + start hour at 0
days = 365 #number of simulation days
periods = 24*3600*days #in seconds (day_periods*365 = years)
pulse_width = (t2-t1)/24 # % of the periods
phase_delay = t1 #in seconds
#t = np.linspace(0, 24*3600, 24)
t= np.linspace(0,1,(days_hours*days)+1,endpoint=False) #+1 start from 0
pulseday = signal.square(2 * np.pi* days * t,duty=pulse_width)
pulseday = np.clip(pulseday, 0, 1)
# add delay to array
pulseday=np.roll(pulseday,phase_delay)
#______pulse week generator______________
week = days/7
pulse_w = 0.99
pulse_week = signal.square(2*np.pi*week*t,duty=pulse_w)
pulse_week = np.clip(pulse_week, 0, 1)
#create simulation time
time_t = np.linspace(0,periods,(days_hours*days)+1)
#Internal heat gain
Qinternal = nightQ + pulseday*DeltaQ*pulse_week
Qinternal=Qinternal[np.newaxis]
Qinternal=Qinternal.T
#Plot 48 hours
#plt.plot(time_t[0:48], Qinternal[0:48])
#plt.ylabel('Internal heat gain (W)')
#plt.xlabel('time (sec)')
#plt.legend(loc=2)
#print(Qinternal)
Qinternal=np.delete(Qinternal, -1, 0) |
#!usr/bin/pytthon
# coding:utf-8
from numpy import *
# 已知用户物品矩阵为dataMat ，行为物品，列为用户
# 计算用户相似度
# -----------------
# 余弦相似度计算
# 欧式距离计算
def eulidSim(inA, inB):
return 1.0 / (1.0 + linalg.norm(inA, inB))
# 皮尔逊系数计算
def pearsSim(inA, inB):
if len(inA) <3 : return 1.0
# 将值从[-1, 1]映射到[0, 1]
return 0.5+0.5*corrcoef(inA, inB, rowvar=0)[0][1]
# 余弦相似度
def cosSim(inA, inB):
num = float(inA*inB.T)
denom = linalg.norm(inA) * linalg.norm(inB)
# 将值从[-1, 1]映射到[0, 1]
return 0.5 + 0.5 * (num / denom)
# 获取向量中非零元素的平均值
def avg(intA):
return float(mean(intA[intA > 0], 1)[0][0])
# 基于用户相似度的推荐
# 数据矩阵，用户，相似度计算方法，物品
def userSimiliar(dataMat, user, simMeas, N = 5):
userNum = shape(dataMat)[0] #获取所有用户数
usersSim= zeros((1, userNum)) #用户相似度向量
# 用户未评分的物品的下标
unratedItems = nonzero(dataMat[user,:].A ==0)[1]
unratedItemGrad = dict() #未评分物品的评分值
unratedItemNum = dict() #根据其他用户，对未评分物品进行评分的次数
# 用户i对商品的平均评分
avgRate = avg(dataMat[user,:])
for item in unratedItems:
unratedItemNum[item] = 0
unratedItemGrad[item] = 0
for i in range(userNum):
if i == user: continue
# 获取用户相似度
usersSim[0][i] = simMeas(dataMat[user,:], dataMat[i,:])#计算用户i和用户user的相似度
#获取用户i评分但是用户user没有评分的物品的下标
unratedItem = list(set(nonzero(logical_or(dataMat[user,:]>0, dataMat[i,:]>0))[1]) - set(nonzero(dataMat[user,:])[1]))
if len(unratedItem) == 0 :continue #说明用户i所评分过的物品，用户User已评分过
for item in unratedItem:
# print unratedItemGrad[item],
# print dataMat[i,item]
unratedItemGrad[item] = unratedItemGrad[item]+ usersSim[0][i] * dataMat[i,item]
unratedItemNum[item] = unratedItemNum[item]+usersSim[0][i]
for item in unratedItems:
if unratedItemNum[item] == 0: continue
unratedItemGrad[item] = unratedItemGrad[item] / unratedItemNum[item]
recommand = sorted(unratedItemGrad.items(), key=lambda jj:jj[1], reverse=True)
recommandItems = list()
for j in range(N):
recommandItems.append(recommand[j])
return recommandItems
# 基于物品相似度的推荐引擎
# 数据矩阵、用户、相似度计算方法、物品。行对应用户、列对应物品
def standEst(dataMat, user, simMeas, item):
# 获取物品数
n = shape(dataMat)[1]
simTotal = 0.0; ratSimTotal = 0.0
for j in range(n):
# 获取用户对当前物品的评分
userRating = dataMat[user,j]
if userRating == 0: continue
# 寻找对物品ITEM评分，且对当前物品有评分的用户
# logical_and逻辑与计算，只有两个位置的都时真的时候才为真，此处计算共同对物品j和物品ITEM进行评分的用户
# nonzeron返回非零元素的下标
overLap = nonzero(logical_and(dataMat[:,item].A >0, dataMat[:,j].A >0))[0]
if len(overLap) == 0: similarity = 0
# 计算两列的相似度，即同一用户对item和j的评分的相似度
else : similarity = simMeas(dataMat[overLap,item] , dataMat[overLap,j])
# 获取总相似度
simTotal += similarity
# 获取用户总评价
ratSimTotal += similarity * userRating
if simTotal == 0: return 0
else : return ratSimTotal/ simTotal
def recommend(dataMat, user, N=3, simMeas=cosSim, estMethod = standEst):
# 获取用户没有评分的物品
unratedItems = nonzero(dataMat[user,:].A == 0)
if len(unratedItems) == 0: return 'you rated everything'
itemScores = []
# 填充用户对所有没有评分的物品的预测评分
for item in unratedItems:
estimatedScore = estMethod(dataMat, user, simMeas, item)
itemScores.append((item, estimatedScore))
# 根据评分对物品进行排序，返回Top-N
return sorted(itemScores, key=lambda jj:jj[1], reverse=True)[:N]
def simBetweenUsers(dataMat, users, simMeas):
# 初始化用户相似度矩阵
simResult = zeros(((users[-1]+1), (users[-1]+1)))
for user1 in users:
for user2 in users:
if(user1 != user2):
simResult[user1][user2] = simMeas(dataMat[user1,:], dataMat[user2,:])
return simResult
|
#!/usr/bin/python3
# import socket programming library
import socket
import json
import time
import csv
import hadoop
import pandas
from io import StringIO
# import thread module
from _thread import *
import threading
print_lock = threading.Lock()
def processJobInfo(stats):
statsstr = '\n'.join(stats)
print(statsstr)
jobsInfo = pandas.read_csv(StringIO(statsstr), sep=',')
for index, row in jobsInfo.iterrows():
print(row)
#hadoop.getJobInfo(row['JobId'])
# thread fuction
def threaded(c, addr):
# lock acquired by client
print_lock.acquire()
print('Connected to :', addr[0], ':', addr[1])
print_lock.release()
stat_file = "/mnt/temp/state_" + addr[0] + "_" + str(addr[1]);
lenght = 0;
wait_for_stat_flag = 1
wait_for_stat_data = 2
status = wait_for_stat_flag;
done = False
while not done:
if status == wait_for_stat_flag:
print("Wait for Start Flag")
# data received from client
data = c.recv(1024).decode('ascii')
if data.startswith('lenght:'):
lenght = int(data.split(":")[1])
c.send(("ready\n").encode('ascii'));
status = wait_for_stat_data
else: #data.startswith('done'):
print_lock.acquire()
print('Connection Closed by Client')
print_lock.release()
done = True
c.close()
elif status == wait_for_stat_data:
# data received from client
print("Wait for Data" + str(lenght))
data = c.recv(lenght);
data = c.recv(lenght);
stats = data.decode('ascii');
c.send(str("done\n").encode('ascii'))
processJobInfo(stats.split('\n')[2:]);
# send back reversed string to client
status = wait_for_stat_flag;
def Main():
host = ""
# reverse a port on your computer
# in our case it is 12345 but it
# can be anything
port = 4964
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind((host, port))
print("socket binded to post", port)
# put the socket into listening mode
s.listen(5)
print("socket is listening")
# a forever loop until client wants to exit
while True:
# establish connection with client
c, addr = s.accept()
# Start a new thread and return its identifier
start_new_thread(threaded, (c, addr, ))
s.close()
if __name__ == '__main__':
Main()
|
import cv2
import cvzone
from cvzone.SelfiSegmentationModule import SelfiSegmentation
import os
cap = cv2.VideoCapture('1.avi')
cap.set(3, 640)
cap.set(4, 480)
cap.set(cv2.CAP_PROP_FPS, 60)
segmentor = SelfiSegmentation()
fpsReader = cvzone.FPS()
imgBg = cv2.imread('Images/1.jpg')
imgBg = cv2.resize(imgBg,(640, 480))
imgIndex = 0
listImg = os.listdir('Images')
imgList = []
for imgPath in listImg:
img = cv2.imread(f'Images/{imgPath}')
img = cv2.resize(img,(640, 480))
imgList.append(img)
while True:
success, img = cap.read()
# imgOut = segmentor.removeBG(img, (0, 255, 0), threshold=0.8)
imgOut = segmentor.removeBG(img, imgList[imgIndex], threshold=0.8)
imgStacked = cvzone.stackImages([img, imgOut],2,0.8)
_, imgStacked = fpsReader.update(imgStacked, color=(0, 0, 255))
cv2.imshow('image out', imgStacked)
key = cv2.waitKey(1)
if key == ord('a'):
if imgIndex > 0:
imgIndex -=1
elif key == ord('d'):
if imgIndex < len(imgList) - 1:
imgIndex +=1
elif key == ord('q'):
break
|
import tensorflow as tf
import models.bert_util.bert_utils
from explain.explain_model import CrossEntropyModeling, CorrelationModeling
from explain.pairing.match_predictor import build_model
from tf_util.tf_logging import tf_logging
from trainer.multi_gpu_support import get_multiple_models, get_avg_loss, get_avg_tensors_from_models, \
get_batch2feed_dict_for_multi_gpu, get_concat_tensors_from_models, get_concat_tensors_list_from_models, get_train_op
from trainer.tf_train_module import get_train_op2
class LMSModel:
def __init__(self, modeling_option, bert_hp, lms_config, num_gpu):
ex_modeling_class = {
'ce': CrossEntropyModeling,
'co': CorrelationModeling
}[modeling_option]
def build_model_fn():
return build_model(ex_modeling_class, bert_hp, lms_config)
self.num_gpu = num_gpu
self.match_predictor = None
self.match_predictor_list = None
self.bert_hp = bert_hp
if num_gpu == 1:
tf_logging.info("Using single GPU")
task_model_, ex_model_, match_predictor = build_model_fn()
loss_tensor = match_predictor.loss
per_layer_loss = match_predictor.all_losses
batch2feed_dict = models.bert_util.bert_utils.batch2feed_dict_4_or_5_inputs
logits = task_model_.logits
ex_score_tensor = ex_model_.get_ex_scores(lms_config.target_idx)
per_layer_logit_tensor = match_predictor.per_layer_logits
self.match_predictor = match_predictor
else:
main_models, ex_models, match_predictor_list = zip(*get_multiple_models(build_model_fn, num_gpu))
loss_tensor = get_avg_loss(match_predictor_list)
per_layer_loss = get_avg_tensors_from_models(match_predictor_list,
lambda match_predictor: match_predictor.all_losses)
batch2feed_dict = get_batch2feed_dict_for_multi_gpu(main_models)
logits = get_concat_tensors_from_models(main_models, lambda model: model.logits)
def get_loss_tensor(model):
t = tf.expand_dims(tf.stack(model.get_losses()), 0)
return t
ex_score_tensor = get_concat_tensors_from_models(ex_models,
lambda model: model.get_ex_scores(lms_config.target_idx))
per_layer_logit_tensor = \
get_concat_tensors_list_from_models(match_predictor_list, lambda model: model.per_layer_logits)
self.match_predictor_list = match_predictor_list
self.logits = logits
self.batch2feed_dict = batch2feed_dict
self.ex_score_tensor = ex_score_tensor
self.loss_tensor = loss_tensor
self.per_layer_logit_tensor = per_layer_logit_tensor
self.per_layer_loss = per_layer_loss
# logits for nli classification
def get_logits(self):
return self.logits
# logits for match score of each layers
def get_lms(self):
return self.per_layer_logit_tensor
def get_train_op(self, lr, max_steps):
if self.num_gpu == 1:
with tf.variable_scope("match_optimizer"):
train_op = get_train_op2(self.match_predictor.loss, lr, "adam", max_steps)
else:
with tf.variable_scope("match_optimizer"):
train_op = get_train_op([m.loss for m in self.match_predictor_list], lr, max_steps)
return train_op |
def try5():
d = Definer()
m = d.matcher
f1 = CFunc(PrimTypes.INT)
f1.add(CPtr(CPtr(PrimTypes.VOID)))
m.add_rule(CPtr(PrimTypes.VOID), 'PVOID')
m.add_rule(PrimTypes.INT, 'INT')
m.tree_names_list.append('MYSTRUC')
# m.add_rule(CPtr(f1), 'MY_PROC')
s1 = CStruct()
s1.add(PrimTypes.UINT, 'a')
u1 = CUnion()
u1.add(PrimTypes.CHAR, 'b1')
u1.add(CPtr(CTypeRef('MYSTRUC')), 'b2')
s1.add(u1, '')
s1.add(PrimTypes.INT, 'c')
# mk = BraceDefMaker('TEST_16', s1, d)
e1 = CEnum()
e1.add('RED', 10)
e1.add('GREEN', 20)
e1.add('BLUE', 30)
mk = BraceDefMaker('TEST16', e1, d)
print(mk.typedef())
print(mk.pure_def())
print(mk.mixed_def())
# try5()
|
from uncertainties import ufloat
from uncertainties.umath import *
print
print '*************Values *********************'
print
H = ufloat(67.4000000, 1.40000000) # H = 67.4+/-1.4
h = H/100.0
print 'h = ', h
obh2 = ufloat(0.0220700000, 0.000330000000)
print 'obh2 = ' , obh2
ob = obh2/h**2
ErrorLnOb = 0.00124
LnOb = log(ob)
#*******************************
#print 'ErrorLnOb0 =' , ErrorLnOb
#print 'ob0 = ', ob
#print 'ErrorOb0 = ' , ob.s
#*********************************
print
print '**** check if ErrorLnOmega_b = ErrorOmega_b/ Omega_b******* '
print
ErrorOb = exp(ErrorLnOb)
print 'LnOb0 = ', LnOb
print 'ErrorLnOb = ', (ErrorLnOb/LnOb)
print 'ErrorOb /Ob = ', ob.s / ob.n
print 'ErrorLnOb x Ob = ', LnOb.s * ob.n
|
numList = []
for x in range(5):
numList.append(int(input("Number " + str(x+1) + ": ")))
print("You entered: " + str(numList))
avg = 0
for x in numList:
avg += int(x)
avg = avg / len(numList)
print("The average is: " + str(avg))
print("The range is: " + str(len(numList)))
rem = int(input("Which item do you want to remove?: "))
del numList[numList.index(rem)]
print("The new list has the following values: " + str(numList))
avg = 0
for x in numList:
avg += int(x)
avg = avg / len(numList)
print("The average is: " + str(avg))
print("The range is: " + str(len(numList)))
|
# -*- mode: Python; -*-
'''Implementation of vrt-data.'''
import os
from subprocess import Popen, PIPE
from libvrt.args import BadData
from libvrt.args import transput_args
# TODO here AND rel-tools to RAISE not EXIT on failure
from libvrt.bins import SORT
from libvrt.dataline import valuegetter
# remnants of vrt-meta seem good here
from libvrt.metaname import nametype, isname
from libvrt.metamark import marktype
def parsearguments(argv, *, prog = None):
description = '''
Present the annotated tokens in a VRT document as a relation in
the form of a Tab-Separated Values (TSV) document, complete with a
head and unique rows in the body. Initially identified positional
names become field names, or default to v1, v2, up to the
initially encountered number of fields, while the corresponding
values become the content of records. This is not a VRT validator.
'''
parser = transput_args(description = description,
inplace = False)
parser.add_argument('--quiet', '-q', action = 'store_true',
help = '''
do not warn when a token has a different
number of annotations than the first name
comment or the first token (default is to warn
four times)
''')
parser.add_argument('--mark', '-m', metavar = 'value',
type = marktype,
default = b'',
help = '''
a mark to use as the value when there are too
few fields (defaults to the empty string -
should the default be visible?)
''')
group = parser.add_mutually_exclusive_group(required = True)
group.add_argument('--tag', '-t', metavar = 'name',
type = nametype,
help = '''
name to use for a tag field to number the
records of the resulting relation
''')
group.add_argument('--unique', '-u', action = 'store_true',
help = '''
omit duplicate records (implies sorting)
''')
args = parser.parse_args()
args.prog = prog or parser.prog
return args
def main(args, ins, ous):
'''Transput VRT (bytes) in ins to TSV (bytes) in ous.'''
data = (
line for line in ins
if not line.isspace()
if (
not (line.startswith(b'<')) or
line.startswith(b'<!-- #vrt positional attributes: ')
)
)
line = next(data, None)
if line is None:
raise BadData('no data, no head')
if line.startswith(b'<'):
left, rest = line.rstrip(b'->\r\n').split(b':')
head = rest.split()
else:
head = [
'v{}'.format(k).encode('utf-8')
for k, v
in enumerate(line.rstrip(b'\r\n').split(b'\t'),
start = 1)
]
if (not all(isname(name) for name in head) or
len(set(head)) < len(head)):
raise BadData('bad names')
values = valuegetter(head, missing = args.mark,
warn = not args.quiet,
many = 4,
prog = args.prog)
if args.tag:
if args.tag in head:
raise BadData('tag name in head already')
def ship(rec, tag):
ous.write(b'\t'.join((*rec, str(tag).encode('utf-8'))))
ous.write(b'\n')
return
ship(head, args.tag.decode('utf-8'))
ship(values(line), 1)
for k, line in enumerate(data, start = 2):
ship(values(line), k)
else:
return 0
else:
# encoded streams seem only available from Python 3.6 on,
# which is too new, so working in UTF-8 again - maybe that is
# nicer anyway
def ship(out, rec):
out.write(b'\t'.join(rec))
out.write(b'\n')
return
ship(ous, head)
ous.flush()
with Popen([ SORT, '--unique' ],
env = dict(os.environ,
LC_ALL = 'C'),
stdin = PIPE,
stdout = ous,
stderr = None) as proc:
ship(proc.stdin, values(line))
for line in data:
ship(proc.stdin, values(line))
|
# Regex
'''
You have a test string S. Your task is to match the string hackerrank. This is case sensitive.
'''
Regex_Pattern = r'hackerrank' # Do not delete 'r'.
import re
Test_String = input()
match = re.findall(Regex_Pattern, Test_String)
print("Number of matches :", len(match))
# Matching Anything But a Newline
'''
You have a test string S.
Your task is to write a regular expression that matches only and exactly strings of form: abc.def.ghi.jkx,
where each variable a, b, c, d, e, f, g, h, i, j, k, x can be any single character except the newline.
'''
regex_pattern = r"...\....\....\....$" # Do not delete 'r'.
import re
import sys
test_string = input()
match = re.match(regex_pattern, test_string) is not None
print(str(match).lower())
# Matching Digits & Non-Digit Characters
'''
You have a test string S. Your task is to match the pattern xxXxxXxxxx
Here x denotes a digit character, and X denotes a non-digit character.
'''
Regex_Pattern = r"\d\d\D\d\d\D\d\d\d\d" # Do not delete 'r'.
import re
print(str(bool(re.search(Regex_Pattern, input()))).lower())
# Matching Whitespace & Non-Whitespace Character
'''
You have a test string S. Your task is to match the pattern XXxXXxXX
Here, x denotes whitespace characters, and X denotes non-white space characters.
'''
Regex_Pattern = r"\S\S\s\S\S\s\S\S" # Do not delete 'r'.
import re
print(str(bool(re.search(Regex_Pattern, input()))).lower())
# Matching Word & Non-Word Character
'''
You have a test string S. Your task is to match the pattern xxxXxxxxxxxxxxXxxx
Here, x denotes word character, and X denotes non-word character.
'''
Regex_Pattern = r"\w\w\w\W\w{10}\W\w\w\w" # Do not delete 'r'.
import re
print(str(bool(re.search(Regex_Pattern, input()))).lower())
# Matching Start & End
'''
You have a test string S. Your task is to match the pattern Xxxxx.
Here, x denotes a word character, and X denotes a digit.
S must start with a digit X and end with . symbol.
S should be 6 characters long only.
'''
Regex_Pattern = r"^\d\w{4}\.$" # Do not delete 'r'.
import re
print(str(bool(re.search(Regex_Pattern, input()))).lower()) |
# --------------
# Importing header files
import numpy as np
# Path of the file has been stored in variable called 'path'
data = np.genfromtxt(path,delimiter=",",skip_header=1)
print ("\nData: \n\n",data)
print ("\nTypeof data: \n\n",type(data))
#New record
new_record=[[50, 9, 4, 1, 0, 0, 40, 0]]
census = np.concatenate((data,new_record))
print (census)
#Code starts here
# --------------
#Code starts here
age = census[:,0]
print (age)
max_age = np.max(age)
print (max_age)
min_age = np.min(age)
print (min_age)
age_mean = np.mean(age)
print (age_mean)
age_std = np.std(age)
print (age_std)
# --------------
#Code starts here
race_0 = census[census[:,2] == 0]
race_1 = census[census[:,2] == 1]
race_2 = census[census[:,2] == 2]
race_3 = census[census[:,2] == 3]
race_4 = census[census[:,2] == 4]
len_0 = len(race_0)
print(len_0)
len_1 = len(race_1)
print (len_1)
len_2 = len(race_2)
print (len_2)
len_3 = len(race_3)
print (len_3)
len_4 = len(race_4)
print (len_4)
minority_race = 3
print (minority_race)
print (census[:,2].size)
# --------------
#Code starts here
senior_citizens = census[census[:,0] > 60]
working_hours_sum = np.sum(senior_citizens[:,6])
senior_citizens_len = len(senior_citizens)
avg_working_hours = working_hours_sum/senior_citizens_len
print(avg_working_hours)
# --------------
#Code starts here
high = census[census[:,1] > 10]
low = census[census[:,1] <= 10]
avg_pay_high = np.mean(high[:,7])
print (avg_pay_high)
avg_pay_low = np.mean(low[:,7])
print (avg_pay_low)
if avg_pay_high > avg_pay_low:
print ('True')
else:
print ('False')
|
import os
#declarar variables
Comensal,Azafata,precio1,precio2,precio3="","",0,0,0
#INPUT
Comensal=os.sys.argv[1]
Azafata=os.sys.argv[2]
precio1=int(os.sys.argv[3])
precio2=int(os.sys.argv[4])
precio3=int(os.sys.argv[5])
#PROCESSING
total =int(precio1 + precio2 + precio3)
#OUTPUT
print(" ############################################# ")
print(" # CEVICHERIA - SEÑOR DELFIN ")
print(" ############################################# ")
print(" #Comensal: " , Comensal + " Azafata: " , Azafata)
print(" #Arroz con mariscos: " , precio1)
print(" #refresco de lima: " , precio2)
print(" #ocopa: " , precio3)
print("# Total : ", total)
#condicional multiple
#si el pedido es mayor a 100 soles mostrarle al comprador que ha ganado un plato de ocopa mas refresco
#si el pedido es igual a 70 soles mostrarle al comprador que ha ganado un refresco
#si el pedido es menor a 40 soles decirle que no ha ganado nada
if(total>100):
print("usted ha ganado un plato de ocopa mas refresco")
if(total==70):
print("usted a ganado un refresco")
if(total<40):
print("usted no ha ganadado nada")
#fin_if
|
from typing import Dict, List, Optional
from pydantic import BaseModel
class RecognitionModel(BaseModel):
error: bool = False
error_msg: str = ""
data: Dict = {}
|
from django.db import models
# Create your models here.
class Employee(models.Model):
fullname = models.CharField(max_length=30)
job = models.CharField(max_length=15)
salary = models.IntegerField()
email = models.EmailField(max_length=50)
def __str__(self):
return self.fullname + "," + self.job
|
from .distributions import GMMDiag, GMMFull, MoE
import tensorflow as tf
import tensorflow.compat.v1 as tf1
from ..utils.tf_utils import log_normalize
class GMMApprox(object):
def __init__(self, log_unnormalized_prob, gmm=None, k=10, loc=0., std=1., ndim=None, loc_tril=None,
samples=20, temp=1., cov_type='diag'):
"""
:param log_unnormalized_prob: Unnormalized log density to estimate
:type log_unnormalized_prob: a tensorflow function that takes [batch_size, ndim]
as input and returns [batch_size]
:param gmm:
:param k: number of components for GMM approximation
:param loc: for initialization, mean
:param std: for initialization, standard deviation
:param ndim:
"""
self.log_prob = log_unnormalized_prob
self.ndim = ndim
self.temp = temp
if gmm is None:
assert ndim is not None, "If no gmm is defined, should give the shape of x"
if cov_type == 'diag':
log_priors = tf.Variable(10. * tf.ones(k))
locs = tf.Variable(tf.random_normal((k, ndim), loc, std))
log_std_diags = tf.Variable(tf1.log(std/k * tf.ones((k, ndim))))
gmm = GMMDiag(log_priors=log_priors,
locs=locs,
log_std_diags=log_std_diags)
elif cov_type == 'full':
log_priors = tf.Variable(10. * tf.ones(k))
locs = tf.Variable(tf1.random_normal((k, ndim), loc, std))
loc_tril = loc_tril if loc_tril is not None else std/k
tril_cov = tf.Variable(loc_tril ** 2 * tf.eye(ndim, batch_shape=(k, )))
gmm = GMMFull(log_priors=log_priors,
locs=locs,
tril_cov=tril_cov)
else:
raise ValueError("Unrecognized covariance type")
self.num_samples = samples
self.gmm = gmm
@property
def sample_shape(self):
return (self.num_samples, )
@property
def opt_params(self):
"""
Parameters to train
:return:
"""
return self.gmm.opt_params
def mixture_lower_bound(self, k):
samples = self.gmm.component_sample(k, self.sample_shape)
log_qs = self.gmm.log_prob(samples)
log_ps = self.temp * self.log_prob(samples)
return tf.reduce_mean(log_ps - log_qs)
def mixture_elbo_fast(self, *args):
samples_conc = tf.reshape(
tf.transpose(self.gmm.all_components_sample(self.sample_shape), perm=(1, 0, 2))
, (-1, self.ndim)) # [k * nsamples, ndim]
log_qs = tf.reshape(self.gmm.log_prob(samples_conc), (self.gmm.k, self.num_samples))
log_ps = tf.reshape(self.temp * self.log_prob(samples_conc), (self.gmm.k, self.num_samples))
component_elbos = tf.reduce_mean(log_ps-log_qs, axis=1)
return tf.reduce_sum(component_elbos * tf.exp(log_normalize(self.gmm.log_priors)))
# log_qs =
def mixture_elbo(self):
component_elbos = tf.stack([self.mixture_lower_bound(k)
for k in range(self.gmm.k)])
return tf.reduce_sum(component_elbos * tf.exp(log_normalize(self.gmm.log_priors)))
@property
def cost(self):
return -self.mixture_elbo_fast()
# return -self.mixture_elbow()
class GMMApproxCond(GMMApprox):
def __init__(self, log_unnormalized_prob, moe=None, ndim_in=None, ndim_out=None, **kwargs):
"""
:param log_unnormalized_prob: Unnormalized log density of the conditional model to estimate log p(y | x)
:type log_unnormalized_prob: a tensorflow function that takes [batch_size, ndim_y] [batch_size, ndim_x]
as input and returns [batch_size]
:param moe:
:type moe: MoE
"""
self.ndim_in = ndim_in # x
self.ndim_out = ndim_out # y
GMMApprox.__init__(self, log_unnormalized_prob, gmm=moe, **kwargs)
@property
def moe(self):
return self.gmm
def mixture_elbow_fast(self, x):
# importance sample mixture weights
samples, weights = self.moe.sample_is(x)
loq_qs = self.moe.log_prob(samples, x)
log_ps = self.temp * self.log_prob(y, x)
elbos_is = tf.reduce_mean(log_ps-loq_qs, axis=1)
return tf.reduce_sum(elbos_is * tf1.exp(weights))
def cost(self, x):
return -self.mixture_elbow_fast(x) |
# -*- coding:utf-8 -*-
import sys
sys.path.append('..')
from Model.BookModel import BookModel
from Model.ISBNBookModel import IsbnBookModel
from View.BookView import BookView
class BookController(object):
def __init__(self):
self.Model = BookModel()
self.View = BookView()
#上传图书ISBN信息
'''
levelNum VARCHAR(10) NOT NULL,
subTitle VARCHAR(100),
author VARCHAR(100) NOT NULL,
date VARCHAR(20) NOT NULL,
imagesMedium VARCHAR(100) NOT NULL,
imagesLarge VARCHAR(100) NOT NULL,
publisher VARCHAR(50) NOT NULL,
isbn VARCHAR(13) NOT NULL PRIMARY KEY,
title VARCHAR(100) NOT NULL,
summary VARCHAR(400) NOT NULL
'''
def BookUpLoadISBNcontroller(self,request):
if request.get('title',default=None):
isbn = request['isbn']
levelNum = request['levelNum']
subTitle = request.get('subTitle',default=None)
author = request['author']
date = request['date']
imagesMedium = request['imagesMedium']
imagesLarge = request['imagesLarge']
publisher = request['publisher']
isbn = request['isbn']
title = request['title']
summary = request['summary']
result = IsbnBookModel.BookUpLoadIsbn(isbn=isbn,levelNum=levelNum,subTitle=subTitle,author=author,date=date,imagesLarge=imagesLarge,imagesMedium=imagesMedium,publisher=publisher,title=title,summary=summary)
else:
isbn = request['isbn']
result = IsbnBookModel.BookUpLoadIsbn(isbn=isbn)
res = self.View.BookUpLoadISBNView(result)
return res
#传入的参数是一个字典，表示UserBook 属性
'''
bookId INTEGER NOT NULL PRIMARY KEY AUTO_INCREMENT,
userId INTEGER NOT NULL,
isbn VARCHAR(13) NOT NULL,
tag1 VARCHAR(100) NOT NULL,
tag2 VARCHAR(100) NOT NULL,
place VARCHAR(100) NOT NULL,
isGroupVisible INTEGER NOT NULL,
lend INTEGER NOT NULL,
'''
def BookUpLoadController(self,request):
#取出字典里的字典
userId = request['userId']
isbn = request['isbn']
tag1 = request['tag1']
tag2 = request['tag2']
place = request['place']
isGroupVisible = request['isGroupVisible']
lend = request['lend']
bookId = self.Model.BookUpLoadUser(userId=userId,isbn=isbn,tag1=tag1,tag2=tag2,place=place,isGroupVisible=isGroupVisible,lend=lend)
res = self.View.BookUpLoadView(bookId)
return res
#删除图书视图
def BookDeleteController(self,request):
#取出字典里的字典
bookId = request['bookId']
result = self.Model.BookDelete(bookId)
res = self.View.BookDeleteView(result)
return res
#管理图书视图
'''
bookId INTEGER NOT NULL PRIMARY KEY AUTO_INCREMENT,
userId INTEGER NOT NULL,
isbn VARCHAR(13) NOT NULL,
tag1 VARCHAR(100) NOT NULL,
tag2 VARCHAR(100) NOT NULL,
place VARCHAR(100) NOT NULL,
isGroupVisible INTEGER NOT NULL,
lend INTEGER NOT NULL,
'''
def BookChangeBookInfoController(self,request):
#取出不同的参数请求调动不同的model函数
bookId = request.get('bookId',default=0)
tag1 = request.get('tag1',default=None)
tag2 = request.get('tag2',default=None)
place = request.get('place',default=None)
isGroupVisible = request.get('isGroupVisible',default=None)
lend = request.get('lend',default=None)
#修改结果 0表示正确 1表示失败 2表示没有修改需求
results = [2,2,2,2,2]
if tag1:
result = self.Model.EditTag1(bookId,tag1)
if not result:
results[0] = 1
else:
results[0] = 0
if tag2:
result = self.Model.EditTag2(bookId,tag2)
if not result:
results[1] = 1
else:
results[1] = 0
if place:
result = self.Model.EditPlace(bookId,place)
if not result:
results[2] = 1
else:
results[2] = 0
if isGroupVisible:
result = self.Model.ShareBook(bookId,isGroupVisible)
if not result:
results[3] = 1
else:
results[3] = 0
if lend:
result = self.Model.LendBook(bookId,lend)
if not result:
results[4] = 1
else:
results[4] = 0
res = self.View.BookChangeBookInfoView(results)
return res
#查询图书视图
"""
Args:
可能的查询参数
bookId INTEGER NOT NULL PRIMARY KEY AUTO_INCREMENT,
userId INTEGER NOT NULL,
isbn VARCHAR(13) NOT NULL,
tag1 VARCHAR(100) NOT NULL,
tag2 VARCHAR(100) NOT NULL,
place VARCHAR(100) NOT NULL,
isGroupVisible INTEGER NOT NULL,
lend INTEGER NOT NULL,
Returns:
一个字典（也可能是字典列表），用户信息，之后封装为JSON发出
"""
def BookQueryController(self,request):
#print(request['bookId'])
#提取出所有可能的查询参数
print(request)
bookId = request.get('bookId',default=0)
userId = request.get('userId',default=0)
isbn = request.get('isbn',default=None)
tag1 = request.get('tag1',default=None)
tag2 = request.get('tag2',default=None)
place = request.get('place',default=None)
isGroupVisible = request.get('isGroupVisible',default=2)
lend = request.get('lend',default=0)
#返回的是一个字典列表
result = self.Model.QueryBook(bookId=bookId,userId=userId,isbn=isbn,tag1=tag1,tag2=tag2,place=place,isGroupVisible=isGroupVisible,lend=lend)
res = self.View.BookQueryView(result)
return res |
max = 1000000
primes = [True]*max
for i in range(2,max):
x = 2*i
while x < max:
primes[x] = False
x += i
print(primes[:30])
count = 1
x = 2
while count < 10001:
x += 1
if primes[x]:
count += 1
print(x)
|
import re, time, json, threading, requests, traceback
from datetime import datetime
import paho.mqtt.client as mqtt
import DAN, SA
def df_func_name(df_name):
return re.sub(r'-', r'_', df_name)
MQTT_broker = getattr(SA,'MQTT_broker', None)
MQTT_port = getattr(SA,'MQTT_port', 1883)
MQTT_User = getattr(SA,'MQTT_User', None)
MQTT_PW = getattr(SA,'MQTT_PW', None)
MQTT_encryption = getattr(SA,'MQTT_encryption', None)
device_model = getattr(SA,'device_model', None)
device_name = getattr(SA,'device_name', None)
ServerURL = getattr(SA,'ServerURL', None)
device_id = getattr(SA,'device_id', None)
if device_id==None: device_id = DAN.get_mac_addr()
IDF_list = getattr(SA,'IDF_list', [])
ODF_list = getattr(SA,'ODF_list', [])
exec_interval = getattr(SA,'exec_interval', 1)
IDF_funcs = {}
for idf in IDF_list:
IDF_funcs[idf] = getattr(SA, df_func_name(idf), None)
ODF_funcs = {}
for odf in ODF_list:
ODF_funcs[odf] = getattr(SA, df_func_name(odf), None)
def on_connect(client, userdata, flags, rc):
if not rc:
print('MQTT broker: {}'.format(MQTT_broker))
if ODF_list == []:
print('ODF_list is not exist.')
return
topic_list=[]
for odf in ODF_list:
topic = '{}//{}'.format(device_id, odf)
topic_list.append((topic,0))
if topic_list != []:
r = client.subscribe(topic_list)
if r[0]: print('Failed to subscribe topics. Error code:{}'.format(r))
else: print('Connect to MQTT borker failed. Error code:{}'.format(rc))
def on_disconnect(client, userdata, rc):
print('MQTT Disconnected. Re-connect...')
client.reconnect()
def on_message(client, userdata, msg):
samples = json.loads(msg.payload)
ODF_name = msg.topic.split('//')[1]
if ODF_funcs.get(ODF_name):
ODF_data = samples['samples'][0][1]
ODF_funcs[ODF_name](ODF_data)
else:
print('ODF function "{}" is not existed.'.format(ODF_name))
def mqtt_pub(client, deviceId, IDF, data):
topic = '{}//{}'.format(deviceId, IDF)
sample = [str(datetime.today()), data]
payload = json.dumps({'samples':[sample]})
status = client.publish(topic, payload)
if status[0]: print('topic:{}, status:{}'.format(topic, status))
def on_register(result):
func = getattr(SA, 'on_register', None)
if func: func(result)
def MQTT_config(client):
client.username_pw_set(MQTT_User, MQTT_PW)
client.on_connect = on_connect
client.on_message = on_message
client.on_disconnect = on_disconnect
if MQTT_encryption: client.tls_set()
client.connect(MQTT_broker, MQTT_port, keepalive=60)
DAN.profile['dm_name'] = device_model
DAN.profile['df_list'] = IDF_list + ODF_list
if device_name: DAN.profile['d_name']= device_name
if MQTT_broker: DAN.profile['mqtt_enable'] = True
result = DAN.device_registration_with_retry(ServerURL, device_id)
on_register(result)
if MQTT_broker:
mqttc = mqtt.Client()
MQTT_config(mqttc)
mqttc.loop_start()
while True:
try:
for idf in IDF_list:
if not IDF_funcs.get(idf):
print('IDF function "{}" is not existed.'.format(idf))
continue
IDF_data = IDF_funcs.get(idf)()
if not IDF_data: continue
if type(IDF_data) is not tuple: IDF_data=[IDF_data]
if MQTT_broker: mqtt_pub(mqttc, device_id, idf, IDF_data)
else: DAN.push(idf, IDF_data)
time.sleep(0.001)
if not MQTT_broker:
for odf in ODF_list:
if not ODF_funcs.get(odf):
print('ODF function "{}" is not existed.'.format(odf))
continue
ODF_data = DAN.pull(odf)
if not ODF_data: continue
ODF_funcs.get(odf)(ODF_data)
time.sleep(0.001)
except Exception as e:
if str(e).find('mac_addr not found:') != -1:
print('Reg_addr is not found. Try to re-register...')
DAN.device_registration_with_retry(ServerURL, device_id)
else:
exception = traceback.format_exc()
print(exception)
if MQTT_broker: mqttc.reconnect()
time.sleep(1)
time.sleep(exec_interval)
|
from histogram_functions import get_words
from histogram_lists import count_words
import random
def sample_by_frequency(histogram):
# Find the most any word appears and set max_frequency equal to that value
max_frequency = 0
for item in histogram:
if item[1] > max_frequency:
max_frequency = item[1]
# Generate a random frequency from one to max_frequency
rand_frequency = random.randint(0, max_frequency)
while True:
# choose a random index to check
rand_index = random.randint(0, len(histogram) - 1)
selected_list = histogram[rand_index]
# check if the selected words frequency is higher or equal to the randomly generated frequency
# if it is, return the word
if selected_list[1] >= rand_frequency:
return selected_list[0]
def higher_markov_sampling(histogram):
# Find the most any word appears and set max_frequency equal to that value
max_frequency = 0
for key, value in histogram.items():
if value > max_frequency:
max_frequency = value
# Generate a random frequency from one to max_frequency
rand_frequency = random.randint(0, max_frequency)
while True:
# choose a random index to check
rand_index = random.randint(0, len(histogram) - 1)
list_from_histrogram = list(histogram)
selected_word = list_from_histrogram[rand_index]
# check if the selected words frequency is higher or equal to the randomly generated frequency
# if it is, return the word
if histogram[selected_word] >= rand_frequency:
return selected_word
def higher_markov_check_frequency(histogram):
frequency_dict = {}
for _ in range(10000):
word_pair = random.choice(list(histogram))
word = higher_markov_sampling(histogram[word_pair])
if word_pair in frequency_dict:
following_words = frequency_dict[word_pair]
if word in following_words:
following_words[word] += 1
else:
following_words[word] = 1
else:
frequency_dict[word_pair] = {word:1}
return frequency_dict
def check_frequency(histogram):
frequency_dict = {}
for _ in range(10000):
word = sample_by_frequency(histogram)
if word in frequency_dict:
frequency_dict[word] += 1
else:
frequency_dict[word] = 1
return frequency_dict
if __name__ == '__main__':
word_list = get_words('GoT_text.txt')
counts = count_words(word_list)
sample = sample_by_frequency(counts)
frequency_check = check_frequency(counts)
print(sample)
print(frequency_check)
|
from hwt.hdlObjects.operator import Operator
from hwt.hdlObjects.operatorDefs import AllOps
from hwt.hdlObjects.types.defs import BOOL
from hwt.hdlObjects.value import Value
class EventCapableVal(Value):
def _hasEvent__val(self, now):
BoolVal = BOOL.getValueCls()
return BoolVal(self.updateTime == now,
BOOL,
self.vldMask,
now)
def _hasEvent(self, now):
if isinstance(self, Value):
return self._hasEvent__val(now)
else:
return Operator.withRes(AllOps.EVENT, [self], BOOL)
def _onFallingEdge__val(self, now):
v = self._hasEvent__val(now)
v.val = v.val and not self.val
return v
def _onFallingEdge(self, now):
if isinstance(self, Value):
return self._onFallingEdge__val(now)
else:
return Operator.withRes(AllOps.FALLIGN_EDGE, [self], BOOL)
def _onRisingEdge__val(self, now):
v = self._hasEvent__val(now)
v.val = v.val and self.val
return v
def _onRisingEdge(self, now):
if isinstance(self, Value):
return self._onRisingEdge__val(now)
else:
return Operator.withRes(AllOps.RISING_EDGE, [self], BOOL) |
import logging
class LastLogsHandler(logging.Handler):
def __init__(self, size):
logging.Handler.__init__(self)
self.strA = []
self.i = 0
self.len = size
for i in range(self.len):
self.strA.append(None)
def emit(self, record):
self.strA[self.i] = record
self.i += 1
if self.i == self.len:
self.i = 0
def getStr(self):
s = ""
for n in range(self.len):
k = self.i - n-1
if k < 0:
k = k + self.len
if self.strA[k] is not None:
s += self.format(self.strA[k])+"\r\n"
return s
class Verify(object):
def __init__(self):
pass
@staticmethod
def dataIntegrityServers(data):
sdata = data[1:2]
numrows = len(sdata)
check = 0
errors_str = ""
for row in range(numrows):
cvalue = sdata[row][3]
for row1 in range(row + 1, numrows):
if cvalue == sdata[row1][3]:
errors_str = errors_str + ("Duplicated TCP port: " + cvalue + "\nLine: " + str(row1 + 1) + "\n")
check = 1
return check, errors_str
@staticmethod
def dataIntegrityUnits(data):
sdata = data[1:2]
numrows = len(sdata)
check = 0
errors_str = ""
for row in range(numrows):
cvalue = sdata[row][2]
cunit = sdata[row][1]
for row1 in range(row+1, numrows):
if cvalue == sdata[row1][2] and cunit == sdata[row1][1]:
errors_str = errors_str + ("Duplicated unit name: " + cvalue + "\n" + "Line: " + str(row1+1) + "\n")
check = 1
return check, errors_str
@staticmethod
def dataIntegrityChannels(data):
# DO NOT MESS WITH ORDER
datype_list = ['bool', 'unsigned_short', 'short', 'float', 'integer', 'unsigned_integer', 'double', 'string']
modbustype_list = ['coils', 'discrete_inputs', 'holding_registers', 'analog_inputs']
sdata = data[1:]
numrows = len(sdata)
units_id = []
channels = []
check = 0
errors_str = ""
for row in range(numrows):
cvalue = sdata[row][2]
cunit = sdata[row][1]
for row1 in range(row+1, numrows):
if cvalue == sdata[row1][2] and cunit == sdata[row1][1]:
errors_str = errors_str + ("Duplicated channel name: " + cvalue + "\n"
+ "Line: " + str(row1+1) + "\n")
check = 1
# check if data types is valid
if sdata[row][5].lower() not in datype_list:
errors_str = errors_str + ("Data type is not valid: " + sdata[row][5] + "\n"
+ "Line: " + str(row+1) + "\n")
check = 1
if sdata[row][8].lower() not in modbustype_list:
errors_str = errors_str + ("Modbus type is not valid: " + sdata[row][8] + "\n"
+ "Line: " + str(row+1) + "\n")
check = 1
# check if datatype is consistent with modbus datatype
# from 0 to 2 in datatype_list length must be ==1
if (sdata[row][5].lower() in datype_list[:2]) and sdata[row][7] != '1':
errors_str = errors_str + ("Lenght of data not valid: " + sdata[row][7] + "\n"
+ "Line: " + str(row+1) + "\n")
check = 1
# from 3 to 4 in datatyp_list length must be == 2
elif (sdata[row][5].lower()in datype_list[3:5]) and sdata[row][7] != '2':
errors_str = errors_str + ("Lenght of data not valid: " + sdata[row][7] + "\n"
+ "Line: " + str(row+1) + "\n")
check = 1
elif sdata[row][5].lower() == 'double' and sdata[row][7] != '4': # double
errors_str = errors_str + ("Lenght of data not valid: " + sdata[row][7] + "\n"
+ "Line: " + str(row+1) + "\n")
check = 1
if sdata[row][1] != '':
# unit_id, modbus address, modbus length
channel = [int(sdata[row][1]), int(sdata[row][6]), int(sdata[row][7])]
channels.append(channel)
if sdata[row][1] != '' and int(sdata[row][1]) not in units_id:
units_id.append(int(sdata[row][1])) # unist
addresses = [None] * max(units_id) # cria lista com espaco para todas a unidades
for unit in units_id: # cria espaco de adressos total
adress_size = 0
for channel in channels:
if unit == channel[0]:
if channel[2] + channel[1] > adress_size:
adress_size = channel[2] + channel[1]
addresses[unit - 1] = ([None] * adress_size)
for address in channels:
for i in range(address[1], address[1] + address[2]):
unit = address[0]
if addresses[unit-1][i] != 1:
addresses[unit-1][i] = 1
else:
errors_str = errors_str + 'Modbus address busy at: unit' + str(unit)+', address: '+str(i)+'\n'
check = 1
return check, errors_str
|
from numpy import *
import pylab
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plot
set_printoptions(precision = 3)
#Datos: distribución normal multivariada en 3d
mean = [1,5,10]
cov = [[-1,1,2], [-2,3,1],[4,0,3]]
d = random.multivariada_normal(mean,cov,1000)
#representació gráfica de los datos
fig1 = plot.figure()
sp = fig1.gca(projection = '3d')
sp.scatter(d[:,0],d[:,1],d[:,2])
plot.show()
#ANALISIS PCA:
#Paso 1: Calcular la matriz de covarianza de los datos (N x N):
d1= d - d.mean(0)
matcov = dot(d1.transpose(), d1)
#Paso 2: Obtener los valores y vectores propios(Diagonalización) de la matrix de covarianza:
valp1,vecp1 = linalg.eig(matcov)
#Paso 3: Dedidir que vectores son los relevantes representando los valores propios en orden decreciente
ind_creciente = argsort(valp1) # orden creciente
ind_decre = ind_creciente [::–1 ] #orden de creciente
val_decre= valp1[ind_decre] # valores propios en orden decreciente
vec_decre= vecp1[:,ind_decre] # ordena r tambien vectores propios
pylab.plot(val_decre,’o–’)
pylab.show( )
# proyectar la nueva base definida por los vectores propios
d_PCA = zeros((d.shape[0],d.shape[1]))
for i in range(d.shape[0]):
for j in range(d.shape[1]):
d_PCA[i,j] = dot(d[i,:], vecp1[:,j])
# recuperar datos originales invirtiendo la proyección (reconstrucción)
d_recon = zeros ((d.shape[0], d.shape[1]))
for i in range(d.shape[0]):
for j in range (d.shape[1]):
d_recon[i] += d_PCA[i, j]*vecp1[:,j]
#comprobar que se recuperan los datos originales:
allclose(d,d_recon)
# Proyectar datos a la nueva base definida por los dos vectores propios con mayor valor propio(espacio PCA 2D)
d_PCA2 = zeros((d.shape[0],2))
for i in range(d.shape[0]):
for i in range(2):
d_PCA2[i,j] = dot(d[i,:],vec_decre[:,j])
#reconstruir datos invirtiendo la proyección PCA 2D
d_recon2 = zeros((d.shape[0], d.shape[1]))
for i in range(d.shape[0]):
for j in range(2):
d_recon2[i] += d_PCA2[i, j]*vec_decre[:,j]
#representación gráfica de los datos:
fig2 = plot.figure()
sp2 = fig2.gca(projection = '3d')
sp2.scatter(d_recon2[:,0], d_recon2[:,1], d_recon2[:,2],c='r',marker='x')
plot.show()
|
#1/2/3
import numpy as np
import pandas as pd
site=('https://raw.githubusercontent.com/guipsamora/pandas_exercises/master/04_Apply/Students_Alcohol_Consumption/student-mat.csv')
df = pd.read_csv(site)
#4
df_slice = df.loc[:,'school':'guardian']
#5/6/8
str_func = lambda x: x.capitalize()
df['Mjob'], df['Fjob'] = (df['Mjob'].apply(str_func),
df['Fjob'].apply(str_func))
#7
print(df.tail(3))
#9
def majority(_df_):
if _df_ >= 17:
return True
else:
return False
df['legal_drinker'] = df['age'].apply(majority)
#10
def mult_10(_df_):
if type(_df_) == int:
return _df_*10
else:
return _df_
df_10 = df.applymap(mult_10)
print(df_10.head(10))
|
import os
#imput
densidad=int(os.sys.argv[1])
altura=int(os.sys.argv[2])
gravedad=float(os.sys.argv[3])
#processing
presion=(densidad*altura*gravedad)
#output
if (presion>42):
print("presion en estado critico para el producto")
if(presion<42 and presion>30):
print("tengan cuidado")
if(presion<20):
print("todo ok")
|
#!/usr/bin/python
"""
unpickle.py: A subset of unpickling code from pickle.py.
- We don't want to ship the pickler.
- We only need to handle the v2 protocol
- We only need to handle the parts of the protocol that we use.
For reference, the _RuntimeType hierarchy seems to require 15 unique
instructions + PROTO and STOP, which are trivial.
"""
import marshal
import sys
mloads = marshal.loads
# Copied from types.py
class _C:
def _m(self): pass
ClassType = type(_C)
# NOTE: I think INST and OBJ aren't used? We want NEWOBJ.
class _EmptyClass:
pass
# Pickle opcodes. See pickletools.py for extensive docs. The listing
# here is in kind-of alphabetical order of 1-character pickle code.
# pickletools groups them by purpose.
MARK = '(' # push special markobject on stack
STOP = '.' # every pickle ends with STOP
POP = '0' # discard topmost stack item
POP_MARK = '1' # discard stack top through topmost markobject
DUP = '2' # duplicate top stack item
FLOAT = 'F' # push float object; decimal string argument
INT = 'I' # push integer or bool; decimal string argument
BININT = 'J' # push four-byte signed int
BININT1 = 'K' # push 1-byte unsigned int
LONG = 'L' # push long; decimal string argument
BININT2 = 'M' # push 2-byte unsigned int
NONE = 'N' # push None
PERSID = 'P' # push persistent object; id is taken from string arg
BINPERSID = 'Q' # " " " ; " " " " stack
REDUCE = 'R' # apply callable to argtuple, both on stack
STRING = 'S' # push string; NL-terminated string argument
BINSTRING = 'T' # push string; counted binary string argument
SHORT_BINSTRING = 'U' # " " ; " " " " < 256 bytes
UNICODE = 'V' # push Unicode string; raw-unicode-escaped'd argument
BINUNICODE = 'X' # " " " ; counted UTF-8 string argument
APPEND = 'a' # append stack top to list below it
BUILD = 'b' # call __setstate__ or __dict__.update()
GLOBAL = 'c' # push self.find_class(modname, name); 2 string args
DICT = 'd' # build a dict from stack items
EMPTY_DICT = '}' # push empty dict
APPENDS = 'e' # extend list on stack by topmost stack slice
GET = 'g' # push item from memo on stack; index is string arg
BINGET = 'h' # " " " " " " ; " " 1-byte arg
INST = 'i' # build & push class instance
LONG_BINGET = 'j' # push item from memo on stack; index is 4-byte arg
LIST = 'l' # build list from topmost stack items
EMPTY_LIST = ']' # push empty list
OBJ = 'o' # build & push class instance
PUT = 'p' # store stack top in memo; index is string arg
BINPUT = 'q' # " " " " " ; " " 1-byte arg
LONG_BINPUT = 'r' # " " " " " ; " " 4-byte arg
SETITEM = 's' # add key+value pair to dict
TUPLE = 't' # build tuple from topmost stack items
EMPTY_TUPLE = ')' # push empty tuple
SETITEMS = 'u' # modify dict by adding topmost key+value pairs
BINFLOAT = 'G' # push float; arg is 8-byte float encoding
TRUE = 'I01\n' # not an opcode; see INT docs in pickletools.py
FALSE = 'I00\n' # not an opcode; see INT docs in pickletools.py
# Protocol 2
PROTO = '\x80' # identify pickle protocol
NEWOBJ = '\x81' # build object by applying cls.__new__ to argtuple
EXT1 = '\x82' # push object from extension registry; 1-byte index
EXT2 = '\x83' # ditto, but 2-byte index
EXT4 = '\x84' # ditto, but 4-byte index
TUPLE1 = '\x85' # build 1-tuple from stack top
TUPLE2 = '\x86' # build 2-tuple from two topmost stack items
TUPLE3 = '\x87' # build 3-tuple from three topmost stack items
NEWTRUE = '\x88' # push True
NEWFALSE = '\x89' # push False
LONG1 = '\x8a' # push long from < 256 bytes
LONG4 = '\x8b' # push really big long
# An instance of _Stop is raised by Unpickler.load_stop() in response to
# the STOP opcode, passing the object that is the result of unpickling.
class _Stop(Exception):
def __init__(self, value):
self.value = value
class Unpickler(object):
def __init__(self, file):
"""This takes a file-like object for reading a pickle data stream.
The protocol version of the pickle is detected automatically, so no
proto argument is needed.
The file-like object must have two methods, a read() method that
takes an integer argument, and a readline() method that requires no
arguments. Both methods should return a string. Thus file-like
object can be a file object opened for reading, a StringIO object,
or any other custom object that meets this interface.
"""
self.readline = file.readline
self.read = file.read
self.memo = {}
def load(self):
"""Read a pickled object representation from the open file.
Return the reconstituted object hierarchy specified in the file.
"""
self.mark = object() # any new unique object
self.stack = []
self.append = self.stack.append
read = self.read
dispatch = self.dispatch
try:
while 1:
key = read(1)
dispatch[key](self)
except _Stop as stopinst:
return stopinst.value
# Return largest index k such that self.stack[k] is self.mark.
# If the stack doesn't contain a mark, eventually raises IndexError.
# This could be sped by maintaining another stack, of indices at which
# the mark appears. For that matter, the latter stack would suffice,
# and we wouldn't need to push mark objects on self.stack at all.
# Doing so is probably a good thing, though, since if the pickle is
# corrupt (or hostile) we may get a clue from finding self.mark embedded
# in unpickled objects.
def marker(self):
stack = self.stack
mark = self.mark
k = len(stack)-1
while stack[k] is not mark: k = k-1
return k
dispatch = {}
def load_eof(self):
raise EOFError
dispatch[''] = load_eof
def load_proto(self):
proto = ord(self.read(1))
if not 0 <= proto <= 2:
raise ValueError, "unsupported pickle protocol: %d" % proto
dispatch[PROTO] = load_proto
def load_persid(self):
pid = self.readline()[:-1]
self.append(self.persistent_load(pid))
dispatch[PERSID] = load_persid
def load_binpersid(self):
pid = self.stack.pop()
self.append(self.persistent_load(pid))
dispatch[BINPERSID] = load_binpersid
def load_none(self):
self.append(None)
dispatch[NONE] = load_none
def load_false(self):
self.append(False)
dispatch[NEWFALSE] = load_false
def load_true(self):
self.append(True)
dispatch[NEWTRUE] = load_true
def load_int(self):
data = self.readline()
if data == FALSE[1:]:
val = False
elif data == TRUE[1:]:
val = True
else:
try:
val = int(data)
except ValueError:
val = long(data)
self.append(val)
dispatch[INT] = load_int
def load_binint(self):
self.append(mloads('i' + self.read(4)))
dispatch[BININT] = load_binint
def load_binint1(self):
self.append(ord(self.read(1)))
dispatch[BININT1] = load_binint1
def load_binint2(self):
self.append(mloads('i' + self.read(2) + '\000\000'))
dispatch[BININT2] = load_binint2
def load_long(self):
self.append(long(self.readline()[:-1], 0))
dispatch[LONG] = load_long
# Commented out because decode_long() depends on _binascii.
#def load_long1(self):
#def load_long4(self):
def load_float(self):
self.append(float(self.readline()[:-1]))
dispatch[FLOAT] = load_float
# Commented out because of struct.unpack.
#def load_binfloat(self):
def load_string(self):
rep = self.readline()[:-1]
for q in "\"'": # double or single quote
if rep.startswith(q):
if len(rep) < 2 or not rep.endswith(q):
raise ValueError, "insecure string pickle"
rep = rep[len(q):-len(q)]
break
else:
raise ValueError, "insecure string pickle"
self.append(rep.decode("string-escape"))
dispatch[STRING] = load_string
def load_binstring(self):
len = mloads('i' + self.read(4))
self.append(self.read(len))
dispatch[BINSTRING] = load_binstring
def load_unicode(self):
self.append(unicode(self.readline()[:-1],'raw-unicode-escape'))
dispatch[UNICODE] = load_unicode
def load_binunicode(self):
len = mloads('i' + self.read(4))
self.append(unicode(self.read(len),'utf-8'))
dispatch[BINUNICODE] = load_binunicode
def load_short_binstring(self):
len = ord(self.read(1))
self.append(self.read(len))
dispatch[SHORT_BINSTRING] = load_short_binstring
def load_tuple(self):
k = self.marker()
self.stack[k:] = [tuple(self.stack[k+1:])]
dispatch[TUPLE] = load_tuple
def load_empty_tuple(self):
self.stack.append(())
dispatch[EMPTY_TUPLE] = load_empty_tuple
def load_tuple1(self):
self.stack[-1] = (self.stack[-1],)
dispatch[TUPLE1] = load_tuple1
def load_tuple2(self):
self.stack[-2:] = [(self.stack[-2], self.stack[-1])]
dispatch[TUPLE2] = load_tuple2
def load_tuple3(self):
self.stack[-3:] = [(self.stack[-3], self.stack[-2], self.stack[-1])]
dispatch[TUPLE3] = load_tuple3
def load_empty_list(self):
self.stack.append([])
dispatch[EMPTY_LIST] = load_empty_list
def load_empty_dictionary(self):
self.stack.append({})
dispatch[EMPTY_DICT] = load_empty_dictionary
def load_list(self):
k = self.marker()
self.stack[k:] = [self.stack[k+1:]]
dispatch[LIST] = load_list
def load_dict(self):
k = self.marker()
d = {}
items = self.stack[k+1:]
for i in xrange(0, len(items), 2):
key = items[i]
value = items[i+1]
d[key] = value
self.stack[k:] = [d]
dispatch[DICT] = load_dict
# INST and OBJ differ only in how they get a class object. It's not
# only sensible to do the rest in a common routine, the two routines
# previously diverged and grew different bugs.
# klass is the class to instantiate, and k points to the topmost mark
# object, following which are the arguments for klass.__init__.
def _instantiate(self, klass, k):
args = tuple(self.stack[k+1:])
del self.stack[k:]
instantiated = 0
if (not args and
type(klass) is ClassType and
not hasattr(klass, "__getinitargs__")):
try:
value = _EmptyClass()
value.__class__ = klass
instantiated = 1
except RuntimeError:
# In restricted execution, assignment to inst.__class__ is
# prohibited
pass
if not instantiated:
try:
value = klass(*args)
except TypeError, err:
raise TypeError, "in constructor for %s: %s" % (
klass.__name__, str(err)), sys.exc_info()[2]
self.append(value)
def load_inst(self):
module = self.readline()[:-1]
name = self.readline()[:-1]
klass = self.find_class(module, name)
self._instantiate(klass, self.marker())
dispatch[INST] = load_inst
def load_obj(self):
# Stack is ... markobject classobject arg1 arg2 ...
k = self.marker()
klass = self.stack.pop(k+1)
self._instantiate(klass, k)
dispatch[OBJ] = load_obj
def load_newobj(self):
args = self.stack.pop()
cls = self.stack[-1]
obj = cls.__new__(cls, *args)
self.stack[-1] = obj
dispatch[NEWOBJ] = load_newobj
def load_global(self):
module = self.readline()[:-1]
name = self.readline()[:-1]
klass = self.find_class(module, name)
self.append(klass)
dispatch[GLOBAL] = load_global
def find_class(self, module, name):
# Subclasses may override this
__import__(module)
mod = sys.modules[module]
klass = getattr(mod, name)
return klass
def load_reduce(self):
stack = self.stack
args = stack.pop()
func = stack[-1]
value = func(*args)
stack[-1] = value
dispatch[REDUCE] = load_reduce
def load_pop(self):
del self.stack[-1]
dispatch[POP] = load_pop
def load_pop_mark(self):
k = self.marker()
del self.stack[k:]
dispatch[POP_MARK] = load_pop_mark
def load_dup(self):
self.append(self.stack[-1])
dispatch[DUP] = load_dup
def load_get(self):
self.append(self.memo[self.readline()[:-1]])
dispatch[GET] = load_get
def load_binget(self):
i = ord(self.read(1))
self.append(self.memo[repr(i)])
dispatch[BINGET] = load_binget
def load_long_binget(self):
i = mloads('i' + self.read(4))
self.append(self.memo[repr(i)])
dispatch[LONG_BINGET] = load_long_binget
def load_put(self):
self.memo[self.readline()[:-1]] = self.stack[-1]
dispatch[PUT] = load_put
def load_binput(self):
i = ord(self.read(1))
self.memo[repr(i)] = self.stack[-1]
dispatch[BINPUT] = load_binput
def load_long_binput(self):
i = mloads('i' + self.read(4))
self.memo[repr(i)] = self.stack[-1]
dispatch[LONG_BINPUT] = load_long_binput
def load_append(self):
stack = self.stack
value = stack.pop()
list = stack[-1]
list.append(value)
dispatch[APPEND] = load_append
def load_appends(self):
stack = self.stack
mark = self.marker()
list = stack[mark - 1]
list.extend(stack[mark + 1:])
del stack[mark:]
dispatch[APPENDS] = load_appends
def load_setitem(self):
stack = self.stack
value = stack.pop()
key = stack.pop()
dict = stack[-1]
dict[key] = value
dispatch[SETITEM] = load_setitem
def load_setitems(self):
stack = self.stack
mark = self.marker()
dict = stack[mark - 1]
for i in xrange(mark + 1, len(stack), 2):
dict[stack[i]] = stack[i + 1]
del stack[mark:]
dispatch[SETITEMS] = load_setitems
def load_build(self):
stack = self.stack
state = stack.pop()
inst = stack[-1]
setstate = getattr(inst, "__setstate__", None)
if setstate:
setstate(state)
return
slotstate = None
if isinstance(state, tuple) and len(state) == 2:
state, slotstate = state
if state:
try:
d = inst.__dict__
try:
for k, v in state.iteritems():
d[intern(k)] = v
# keys in state don't have to be strings
# don't blow up, but don't go out of our way
except TypeError:
d.update(state)
except RuntimeError:
# XXX In restricted execution, the instance's __dict__
# is not accessible. Use the old way of unpickling
# the instance variables. This is a semantic
# difference when unpickling in restricted
# vs. unrestricted modes.
# Note, however, that cPickle has never tried to do the
# .update() business, and always uses
# PyObject_SetItem(inst.__dict__, key, value) in a
# loop over state.items().
for k, v in state.items():
setattr(inst, k, v)
if slotstate:
for k, v in slotstate.items():
setattr(inst, k, v)
dispatch[BUILD] = load_build
def load_mark(self):
self.append(self.mark)
dispatch[MARK] = load_mark
def load_stop(self):
value = self.stack.pop()
raise _Stop(value)
dispatch[STOP] = load_stop
def load_v2_subset(f):
"""Turn a pickle into an object.
Handles a subset of the v2 protocol.
"""
return Unpickler(f).load()
|
from random import choice
from time import sleep
STUDENTS = [
'Name 1',
'Name 2',
'Name 3',
]
def rien_ne_va_plus(hot_seats, safe_students):
if hot_seats == []:
hot_seats = STUDENTS.copy()
safe_students = []
print(f"Students on the hot seats for the next question:\n\t{', '.join(hot_seats)}\n")
sleep(1)
print(f"Safe students (for now):\n\t{'Nobody 😈' if safe_students == [] else ', '.join(safe_students)}\n")
sleep(1)
the_chosen_one = choice(hot_seats)
hot_seats.remove(the_chosen_one)
safe_students.append(the_chosen_one)
print("The chosen one is", end=" ")
for i in range(3):
print('.', end="")
sleep(1)
print(f" {choice(['🎉', '🥳', '🎊'])} {the_chosen_one.upper()} {choice(['🎉', '🥳', '🎊'])}")
return hot_seats, safe_students
|
rzymskie ={ 1:'I', 2:'II', 3:'III', 4:"IV", 5:"V", 6:"VI", 7:"VII", 8:"VIII", 9:'IX', 10:"X"}
cyfra = input("podaj liczbę: ")
#po_rzymsku = rzymskie[liczba]
#print(po_rzymsku)
#cyfra 28
cyfra_dziesiatek = int(cyfra[-2])# przedostatnia cyfra, przdostatni znak zamieniona na cyfrę
cyfra_jedności= int(cyfra[-1])
jednosci_rzymskie=rzymskie[cyfra_jedności]
dziesiatki_rzymskie='X'*cyfra_dziesiatek
print(dziesiatki_rzymskie+jednosci_rzymskie) |
#!/usr/bin/python
""" Script to make light budget calculations for permitted cable lengths for a
given TAP or appropriate TAP for current link. """
from decimal import Decimal, getcontext
def menu():
""" High level menu for available options. """
option = raw_input("""\nWhat would you like to do:
1 - Calculate the max allowed coupler loss for inserting a TAP into a link
2 - Calculate the max allowed cable length for a given TAP split ratio in a link
3 - Display ethernet fiber standards and max cabling distance
4 - Exit
Enter your selection: """)
if option not in ('1', '2', '3', '4'):
print "That is not a valid input"
menu()
if option == '1':
max_split()
elif option == '2':
max_cable()
elif option == '3':
ethernet_table()
elif option == '4':
print "Goodbye"
exit()
else:
print 'Something went wrong!'
exit()
def max_split():
""" Determine the maximum split ratio that can be used on a given link. """
getcontext().prec = 5
sender = Decimal(raw_input("\nwhat is the sender transmit power (dB): "))
receiver = Decimal(raw_input("\nWhat is the receiver sensitivity (dB): "))
link_loss_budget = sender - receiver
print "\nThe Power Link Loss Budget for this link is %sdB" % link_loss_budget
mode = raw_input("""\nSingle Mode or Multi Mode fiber?
1 - Single Mode
2 - Multi Mode
Enter the number of your selection: """)
if mode not in ('1', '2'):
print "\nThat is not a valid selection"
menu()
connectors = Decimal(raw_input("\nHow many connectors are in the path of the link: "))
if mode == '1':
connector_loss = Decimal('0.2') * connectors
mode_type = "Single Mode"
wave = raw_input("""\nWhat is the wavelength being used?
1 - 1310nm
2 - 1550nm
Enter the number of your selection: """)
if wave not in ('1', '2'):
print "\nThat is not a valid selection"
menu()
if wave == '1':
wavelength = 1310
else:
wavelength = 1550
else:
connector_loss = Decimal('0.5') * connectors
mode_type = "Multi Mode"
wave = raw_input("""\nWhat is the wavelength being used?
1 - 850nm
2 - 1300nm
Enter the number of your selection: """)
if wave not in ('1', '2'):
print "\nThat is not a valid selection"
menu()
if wave == '1':
wavelength = 850
else:
wavelength = 1300
print ("\nThe total loss introduced for the %s link by connectors "
"is %sdB\n" % (mode_type, connector_loss))
cable = int(raw_input("What is the cable length from the sender to the receiver in meters: "))
if mode_type == 'Single Mode' and wavelength == 1310:
attenuation = Decimal('0.4')
elif mode_type == 'Single Mode' and wavelength == 1500:
attenuation = Decimal('0.3')
elif mode_type == 'Multi Mode' and wavelength == 850:
attenuation = Decimal('3.0')
elif mode_type == 'Multi Mode' and wavelength == 1300:
attenuation = Decimal('1.0')
else:
print "Something went wrong."
cable_loss = Decimal(cable / 1000.000) * attenuation
print """\nThe loss introduced by the length of cable for the %s %s link
is %sdB based on %sdB/km fiber attenuation.
\n""" % (mode_type, wavelength, cable_loss, attenuation)
total_cable_loss = connector_loss + cable_loss
print "The total connection loss is %sdB\n" % total_cable_loss
allowable_loss = link_loss_budget - total_cable_loss
print """The allowable coupler loss for a TAP is a %sdB
maximum at the monitor port\n""" % allowable_loss
choice = raw_input("""Reference which TAP insertion loss values?
1 - Industry Standard
2 - Cubro Average
Enter your selection: """)
if choice not in ('1', '2'):
print "\nThat is not a valid selection"
menu()
if choice == '1':
match_industry(mode_type, allowable_loss)
if choice == '2':
match_cubro(mode_type, allowable_loss)
def match_industry(mode, loss):
""" Determine available TAP options using industry standard values."""
#Maximum recommended values
taps_mm = {'50/50': {'Network': '4.5', 'Monitor': '4.5'},
'60/40': {'Network': '3.1', 'Monitor': '5.1'},
'70/30': {'Network': '2.4', 'Monitor': '6.3'},
'80/20': {'Network': '1.8', 'Monitor': '8.1'},
'90/10': {'Network': '1.3', 'Monitor': '11.5'}}
taps_sm = {'50/50': {'Network': '3.7', 'Monitor': '3.7'},
'60/40': {'Network': '2.8', 'Monitor': '4.8'},
'70/30': {'Network': '2.0', 'Monitor': '6.1'},
'80/20': {'Network': '1.3', 'Monitor': '8.0'},
'90/10': {'Network': '0.8', 'Monitor': '12.0'}}
usable = []
if mode == 'Single Mode':
for split in taps_sm:
if float(taps_sm[split]['Monitor']) < float(loss):
usable.append(split)
elif mode == 'Multi Mode':
for split in taps_mm:
if float(taps_mm[split]['Monitor']) < float(loss):
usable.append(split)
else:
print "\nSomething went wrong"
print """\nThe following split ratios are acceptable for this link
%s""" % usable
menu()
def match_cubro(mode, loss):
""" Determine available TAP options for a given link using Cubro values."""
#Adjusted average Cubro values
taps_mm = {'50/50': {'Network': '4.5', 'Monitor': '4.5'},
'60/40': {'Network': '3.1', 'Monitor': '5.1'},
'70/30': {'Network': '2.4', 'Monitor': '6.3'},
'80/20': {'Network': '1.8', 'Monitor': '8.1'},
'90/10': {'Network': '1.3', 'Monitor': '11.5'}}
taps_sm = {'50/50': {'Network': '3.6', 'Monitor': '3.5'},
'60/40': {'Network': '2.8', 'Monitor': '4.8'},
'70/30': {'Network': '2.0', 'Monitor': '6.1'},
'80/20': {'Network': '1.3', 'Monitor': '8.0'},
'90/10': {'Network': '0.8', 'Monitor': '12.0'}}
usable = []
if mode == 'Single Mode':
for split in taps_sm:
if float(taps_sm[split]['Monitor']) < float(loss):
usable.append(split)
elif mode == 'Multi Mode':
for split in taps_mm:
if float(taps_mm[split]['Monitor']) < float(loss):
usable.append(split)
else:
print "\nSomething went wrong"
print """\nThe following split ratios are acceptable for this link
%s""" % usable
menu()
def max_cable():
""" Function to determine max cable length for a given link + connectors."""
getcontext().prec = 5
sender = Decimal(raw_input("\nwhat is the sender transmit power (dB): "))
receiver = Decimal(raw_input("\nWhat is the receiver sensitivity (dB): "))
link_loss_budget = sender - receiver
print "\nThe Power Link Loss Budget for this link is %sdB" % link_loss_budget
mode = raw_input("""\nSingle Mode or Multi Mode fiber?
1 - Single Mode
2 - Multi Mode
Enter the number of your selection: """)
if mode not in ('1', '2'):
print "\nThat is not a valid selection."
menu()
connectors = Decimal(raw_input("\nHow many connectors are in the path of the link: "))
if mode == '1':
connector_loss = Decimal('0.2') * connectors
mode_type = "Single Mode"
print """\nWhat is the wavelength being used?
1 - 1310nm
2 - 1550nm"""
wave = raw_input("\nEnter the number of your selection: ")
if wave not in ('1', '2'):
print "\nThat is not a valid selection."
if wave == '1':
wavelength = 1310
else:
wavelength = 1550
else:
connector_loss = Decimal('0.5') * connectors
mode_type = "Multi Mode"
wave = raw_input("""\nWhat is the wavelength being used?
1 - 850nm
2 - 1300nm
Enter the number of your selection: """)
if wave not in ('1', '2'):
print "That is not a valid selection."
menu()
if wave == '1':
wavelength = 850
else:
wavelength = 1300
print ("\nThe total loss introduced for the %s link by "
"connectors is %sdB\n" % (mode_type, connector_loss))
split = raw_input("""\nWhat is the split ratio of the TAP?
1 - 50/50
2 - 60/40
3 - 70/30
4 - 80/20
5 - 90/10
Enter the number of your selection: """)
if split not in ('1', '2', '3', '4', '5'):
print "That is not a valid input for split ratio"
menu()
split_ratios = {'1': '50/50',
'2': '60/40',
'3': '70/30',
'4': '80/20',
'5': '90/10'}
ratio = split_ratios[split]
taps_mm = {'50/50': {'Network': '4.5', 'Monitor': '4.5'},
'60/40': {'Network': '3.1', 'Monitor': '5.1'},
'70/30': {'Network': '2.4', 'Monitor': '6.3'},
'80/20': {'Network': '1.8', 'Monitor': '8.1'},
'90/10': {'Network': '1.3', 'Monitor': '11.5'}}
taps_sm = {'50/50': {'Network': '3.7', 'Monitor': '3.7'},
'60/40': {'Network': '2.8', 'Monitor': '4.8'},
'70/30': {'Network': '2.0', 'Monitor': '6.1'},
'80/20': {'Network': '1.3', 'Monitor': '8.0'},
'90/10': {'Network': '0.8', 'Monitor': '12.0'}}
if mode_type == 'Single Mode':
for value in taps_sm:
if ratio == value:
network = Decimal(taps_sm[value]['Network'])
monitor = Decimal(taps_sm[value]['Monitor'])
elif mode_type == 'Multi Mode':
for value in taps_mm:
if ratio == value:
network = Decimal(taps_mm[value]['Network'])
monitor = Decimal(taps_mm[value]['Monitor'])
else:
print 'Something went wrong'
total_loss_net = link_loss_budget - connector_loss - network
total_loss_mon = link_loss_budget - connector_loss - monitor
if mode_type == 'Single Mode' and wavelength == 1310:
attenuation = Decimal('0.4')
elif mode_type == 'Single Mode' and wavelength == 1500:
attenuation = Decimal('0.3')
elif mode_type == 'Multi Mode' and wavelength == 850:
attenuation = Decimal('3.0')
elif mode_type == 'Multi Mode' and wavelength == 1300:
attenuation = Decimal('1.0')
else:
print "Something went wrong."
cable_net = 1
cable_loss_net = Decimal(cable_net * (attenuation / 1000))
while total_loss_net - cable_loss_net > 0:
cable_net += 1
cable_loss_net = Decimal(cable_net * (attenuation / 1000))
cable_mon = 1
cable_loss_mon = Decimal(cable_mon * (attenuation / 1000))
while total_loss_mon - cable_loss_mon > 0:
cable_mon += 1
cable_loss_mon = Decimal(cable_mon * (attenuation / 1000))
cable_by_eth_standard(mode_type, cable_net, cable_mon)
def cable_by_eth_standard(mode_type, cable_net, cable_mon):
""" Determines what the maximum cable length could be given a Ethernet
fiber standard."""
if mode_type == 'Multi Mode':
standard_type = raw_input("""\nWhat is the Ethernet Standard in use?
1 - OM1-SX
2 - OM1-LX
3 - OM2
4 - OM3
5 - OM4
Enter the number of your selection: """)
if standard_type not in ('1', '2', '3', '4', '5'):
print "That is not a valid selection."
menu()
standard_table = {'1': 'OM1-SX',
'2': 'OM1-LX',
'3': 'OM2',
'4': 'OM3',
'5': 'OM4'}
standard = standard_table[standard_type]
speed = raw_input("""\nWhat speed is the link?
1 - 100M
2 - 1G
3 - 10G
4 - 40G
5 - 100G
Enter the number of your selection: """)
if speed not in ('1', '2', '3', '4', '5'):
print "That is not a valid selection."
menu()
speed_table = {'1': '100M',
'2': '1G',
'3': '10G',
'4': '40G',
'5': '100G'}
link_speed = speed_table[speed]
table = {
'Single Mode':{'100M': 2000,
'1G': 5000,
'10G': 10000,
'40G': 'Unknown',
'100G': 'Unknown'},
'Multi Mode': {'OM1-SX': {'100M': 2000,
'1G': 275,
'10G': 33},
'OM1-LX': {'100M': 2000,
'1G': 550,
'10G': 33},
'OM2': {'100M': 2000,
'1G': 550,
'10G': 82},
'OM3': {'100M': 2000,
'1G': 550,
'10G': 300,
'40G': 100,
'100G': 100},
'OM4': {'100M': 2000,
'1G': 550,
'10G': 400,
'40G': 150,
'100G': 150}
}}
if mode_type == 'Single Mode':
try:
max_standard_length = table['Single Mode'][link_speed]
if cable_net > max_standard_length:
cable_net = max_standard_length
if cable_mon > max_standard_length:
cable_mon = max_standard_length
except (KeyError, ValueError) as reason:
print ("That standard does not support that speed.", reason)
if mode_type == 'Multi Mode':
try:
max_standard_length = table['Multi Mode'][standard][link_speed]
if cable_net > max_standard_length:
cable_net = max_standard_length
if cable_mon > max_standard_length:
cable_mon = max_standard_length
except KeyError as reason:
print ("That standard does not support that speed.", reason)
print ("\nThe maximum combined cable length from sender to TAP and from "
"TAP to receiver is %s meters" % cable_net)
print ("\nThe maximum combined cable length from sender to TAP and from "
"TAP monitor to tool is %s meters" % cable_mon)
menu()
def ethernet_table():
""" Display table of fiber standards. """
print """Ethernet Fiber Standards and max cabling distance:
________________________________________________________________________________________________________________
| | Core/ | | FastEthernet | 1G Ethernet | 1G Ethernet | 10G | 40G | 100G |
| Name | Cladding | Type | 100BaseFX | 1000Base-SX | 1000Base-LX | 10GBase | 40GBase | 100GBase |
| ________|____________|______|______________|_______________|_______________|___________|___________|___________|
| OM1 | 62.5/125 | MM | 2000M | 275M | 550M* | 33M | NA | NA |
|_________|____________|______|______________|_______________|_______________|___________|___________|___________|
| OM2 | 62.5/125 | MM | 2000M | 550M | 550M* | 82M | NA | NA |
|_________|____________|______|______________|_______________|_______________|___________|___________|___________|
| OM3 | 50/125 | MM | 2000M | 550M | 550M | 300M | 100M | 100M |
|_________|____________|______|______________|_______________|_______________|___________|___________|___________|
| OM4 | 50/125 | MM | 2000M | 550M | 550M | 400M | 150M | 150M |
|_________|____________|______|______________|_______________|_______________|___________|___________|___________|
| | | | | 5km @ | 5km @ | 10km @ | | |
| SM | 9/125 | SM | 2000M | 1310nm | 1310nm | 1310nm | | |
|_________|____________|______|______________|_______________|_______________|___________|___________|___________|
*mode condition patch cable required
"""
menu()
if __name__ == '__main__':
menu()
|
class Node(object):
def __init__(self, data = None, next_node = None):
self.data = data
self.next = next_node
def __str__(self):
return str(self.data)
def get_data(self):
return self.data
def print_list(node):
while node:
print(node.get_data())
node = node.next |
class Config(object):
DEBUG = True
SQLALCHEMY_DATABASE_URI = "mysql://dev:dev@localhost/ssi"
SQLALCHEMY_ECHO = False
SECRET_KEY = "secret" |
from StringIO import StringIO
import tornado.gen
import tornado.testing
import tornado.web
from tornado.httpclient import HTTPResponse, HTTPRequest
from mainhandler import MainHandler
class MainHandlerTest(tornado.testing.AsyncHTTPTestCase):
"Test fixture for MainHandler class"
def __init__(self, *args, **kwargs):
"Initialise fixture"
super(MainHandlerTest, self).__init__(*args, **kwargs)
self._datastore = MockDataStore()
self._mock_google_response = None
self._mock_yahoo_response = None
def get_app(self):
"Return a Tornado application instance that will be used for the tests"
servicesDict={'datastore': self._datastore}
return tornado.web.Application([
(r"/", MainHandler, servicesDict)
])
def testSimpleGet(self):
"Test simple GET"
self._datastore.mock_google_response = HTTPResponse(HTTPRequest('http://www.google.com'),
code=200,
headers={'Content-Length': 24},
buffer=StringIO('<html><body>I Am Google</body></html>'))
self._datastore.mock_yahoo_response = HTTPResponse(HTTPRequest('http://search.yahoo.com'),
code=200,
headers={'Content-Length': 20},
buffer=StringIO('<html><body>I Am Groot</body></html>'))
response = self.fetch('/')
self.assertEqual(response.code, 200)
self.assertIn('<h1>This is the Home Page!</h1>', response.body)
self.assertIn('<p>24 bytes retrieved from backend 1, 20 bytes from backend 2</p>', response.body)
self.assertNotIn('Error', response.body)
class MockDataStore(object):
"Mock datastore"
def __init__(self):
"Initialise mock store"
self.mock_google_response = None
self.mock_yahoo_response = None
@tornado.gen.coroutine
def get_google(self):
"Mock get google content"
raise tornado.gen.Return(self.mock_google_response)
@tornado.gen.coroutine
def get_yahoo(self):
"Mock get yahoo content"
raise tornado.gen.Return(self.mock_yahoo_response)
|
import hashlib
import imghdr
import sec
import db_op
__all__ = ['get_type_by_stream', 'save_file', 'get_hashcode', 'get_default',
'get_image']
_SAVE_PATH = '/Yagra/upload/'
_DEFAULT_IMG = '/Yagra/web/static/rex.jpeg'
def get_type_by_stream(stream):
"""Check the data stream and return what type of image it is."""
return imghdr.what('', stream)
def save_file(data, username):
"""Save the image data into file and record the file path."""
filepath = _SAVE_PATH + username
with open(filepath, 'wb') as f:
f.write(data)
db_op.add_image(get_hashcode(username), username)
def get_hashcode(username):
"""Return MD5 hex digest of the lower case input string."""
return hashlib.md5(username.lower()).hexdigest()
def get_default():
"""Return the file path of the default image."""
return _DEFAULT_IMG
def get_image(hashcode):
"""Get the image file path by hash code."""
if sec.check_hashcode(hashcode):
images = db_op.get_image(hashcode)
if len(images) == 1:
filename = images[0][1]
return _SAVE_PATH + filename
return None
|
# Linear Regression Machine Learning Program
#
# Sources used:
# - https://towardsdatascience.com/master-machine-learning-multiple-linear-regression-from-scratch-with-python-ac716a9b78a4
# Sean Taylor Thomas
import numpy as np
import matplotlib.pyplot as plt
# from matplotlib import rcParams
# rcParams['figure.figsize'] = (14,7)
# rcParams['axes.spines.top'] = False
# rcParams['axes.spins.right'] = False
def import_data(filename):
""" Take data from txt file"""
dataset = list()
with open(filename) as f:
lines = f.readlines()
for line in lines:
dataset.append(line.split())
return dataset
def str_column_to_float(dataset, column):
""" Convert string column to float """
for row in dataset:
row[column] = float(row[column].strip())
class LinearRegression:
""" Implementation of linear regression using gradient descent"""
def __init__(self, l_rate = 0.7, iterations=1000):
self.l_rate = l_rate
self.iterations = iterations
self.weights = None
self.bias = None
self.loss =[]
@staticmethod
def _mean_squared_error(y, y_hat):
""" Evaluating loss at each iteration
y = array of known values
y_hat = array of predicted values
returns float representing error"""
error = 0
for i in range(len(y)):
error += (y[i] - y_hat[i]) **2
return error / len(y)
def fit(self, X, y):
self.weights = np.zeros(X.shape[1])
self.bias = 0
for i in range(self.iterations):
y_hat = np.dot(X, self.weights) + self.bias
loss = self._mean_squared_error(y, y_hat)
self.loss.append(loss)
deriv_w = (1 / X.shape[0]) * (2 * np.dot(X.T, (y_hat - y)))
deriv_d = (1 / X.shape[0]) * (2 * np.sum(y_hat - y))
self.weights -= self.l_rate * deriv_w
self.bias -= self.l_rate * deriv_d
def predict(self, X):
return np.dot(X, self.weights) + self.bias
from sklearn.datasets import load_diabetes
data = load_diabetes()
x = data.data
y = data.target
filename = 'housing.data'
x = import_data(filename)
# put data in x and target (dependent var) data in y
for i in range(len(x[0])):
str_column_to_float(x, i)
y = list()
for row in x:
y.append(row[-1])
row.remove(row[-1]) # separate x (independent vars) from y (dependent var)
# put into numpy arrays and normalize data
x = np.array(x)
y = np.array(y)
xnorm = np.linalg.norm(x)
x = x / xnorm
# split data into training and testing data
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, t_test = train_test_split(x,y, test_size = .2, random_state = 42)
model = LinearRegression()
model.fit(x_train, y_train)
predictions = model.predict(x_test)
print(x_test)
print(predictions)
xs = np.arange(len(model.loss))
ys = model.loss
# Plotting our loss over iterations
plt.plot(xs, ys, lw=3, c='#0033a3')
plt.title('Loss per iteration(MSE)', size=20)
plt.xlabel('Iteration', size=14)
plt.ylabel('Loss', size=14)
plt.show()
# test over different learning rates
# losses = {}
# for lr in [.7,0.5, 0.1, 0.01, 0.001]:
# model = LinearRegression(l_rate=lr)
# model.fit(x_train, y_train)
# losses[f'LR={str(lr)}'] = model.loss
#
# xs = np.arange(len(model.loss))
# plt.plot(xs, losses['LR=0.7'], lw=3, label=f"LR = 0.7, Final = {losses['LR=0.7'][-1]:.2f}")
# plt.plot(xs, losses['LR=0.5'], lw=3, label=f"LR = 0.5, Final = {losses['LR=0.5'][-1]:.2f}")
# plt.plot(xs, losses['LR=0.1'], lw=3, label=f"LR = 0.1, Final = {losses['LR=0.1'][-1]:.2f}")
# plt.plot(xs, losses['LR=0.01'], lw=3, label=f"LR = 0.01, Final = {losses['LR=0.01'][-1]:.2f}")
# plt.plot(xs, losses['LR=0.001'], lw=3, label=f"LR = 0.001, Final = {losses['LR=0.001'][-1]:.2f}")
# plt.title('Loss per iteration (MSE) across l_rates', size=20)
# plt.xlabel('Iteration', size=14)
# plt.ylabel('Loss', size=14)
# plt.legend()
# plt.show()
# User predictions:
num_cols = len(x[0])
user_input = input("Would you like to provide input for prediction? y/n")
iter1 = 0
x1 = list() # user x
while user_input == 'y' and iter1 < num_cols:
user_x = input("Attribute %d : " % iter1)
if not(user_x == '' or user_x == " " or user_x == "\n"):
x1.append(float(user_x))
iter1 += 1
if (user_input == 'y'):
x1 = x1 / xnorm
user_prediction = model.predict(x1)
print(x1)
print("Prediction : ", user_prediction)
|
from collections import deque
queue = deque(["Eric", "John", "Michael"])
queue.append("Ben")
queue.append("Helen")
print queue
print queue.popleft()
print queue |
import numpy as np
# Creating an 1d - array
li = [1, 2, 3]
arr = np.array(li)
print(arr)
# Creating an 2d - array
li = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
arr = np.array(li)
print(arr)
# Creating an array of a number sequence
arr = np.arange(0, 10)
print(arr)
arr = np.arange(0, 10, step=2)
print(arr)
# Creating an 1-d array with zeros
arr = np.zeros(3)
print(arr)
# Creating an 2-d array with zeros
my_tuple = ((5, 5))
arr = np.zeros(my_tuple)
print(arr)
# Creating an 1-d array with ones
arr = np.ones(8)
print(arr)
# Creating an 2-d array with ones
arr = np.ones((3, 5))
print(arr)
# Creating identity matrix
arr = np.eye(5)
print(arr)
# Creating an array
# initialize in a number
# finalizes in a number
# specifying the numbers of elements between initial and final number
initial = 0
final = 1
n_numbers = 3
arr = np.linspace(initial, final, n_numbers)
print(arr)
# Creating random numbers
# between 0 and 1
# with equal problably to be selected
# extrated from a uniform distribution
# 1-dimensional
n_numbers = 5
arr = np.random.rand(n_numbers)
print(arr)
# n-dimensional
arr = np.random.rand(10, 5)
print(arr)
# Creating random numbers
# between 0 and 1
# extracted from a normal distribution
# 1-dimensional
arr = np.random.rand(5)
print(arr)
# n-dimensional
arr = np.random.rand(10, 5)
print(arr)
# Creating random numbers
# integers
# 10 random integers between 0 and 99
arr = np.random.randint(0, 100, 10)
# Round the numbers of the arrays
arr = np.random.rand(5) * 100
arr_2 = np.round(arr, decimals=0)
print(arr_2)
# Reshape
arr = np.random.rand(25)
print(arr)
tpl: tuple = (5,5)
arr_2 = arr.reshape(tpl)
print(arr_2)
print(arr_2.shape) # shape attribute
# Find the max/min value of an array
arr = np.random.rand(2)
max_value = arr.max()
min_value = arr.min()
print(arr)
print(max_value)
print(arr, min_value)
# Find the index of the max/min value of an array
arr = np.random.rand(2)
max_value = arr.argmax()
min_value = arr.argmin()
print(arr)
print(max_value)
print(min_value)
print(max_value)
print(min_value)
"""
Indexing and Slicing arrays
"""
# Select element by index
arr = np.arange(0, 30, 3)
number = arr[4]
print(number)
# Slicing: selecet multiple elements
# like a list
arr = np.arange(0, 30, 3)
numbers = arr[0:4] # first 4 - 0 == 4 index elements
print(numbers)
numbers = arr[:4] # first 4 index elements
print(numbers)
numbers = arr[4:] # elements grather or equal than 4 index
print(numbers)
# attributing values to a slice of an array
arr_2 = arr.copy()
arr_2[4:] = 100
print(arr_2)
arr_2 = arr.copy()
arr_2[4:] = 100
print(arr_2)
# Slicing n-dim arrays
arr = np.arange(50).reshape(5, 10)
print(arr)
print(arr.shape)
def compare_arrays(arr, arr_2, arr_3):
print(arr_2, id(arr_2))
print(arr_3, id(arr_3))
arr_boolean = arr_2 == arr_3 # compara values
boolean: bool = arr_boolean.all() # true if all is true
print(arr_boolean)
print(boolean)
arr_2[:] = 100 # setting 100 to all array elements
print(arr_2)
print(arr)
# way 01: arr.[lines][columns]
arr_2 = arr.copy()[:3][:] # copy function to avoid point to arr when alter arr_2 or arr_3
arr_3 = arr.copy()[:3]
compare_arrays(arr, arr_2, arr_3)
# way 02:
# comma notation
arr_2 = arr.copy()[1:4, ]
arr_3 = arr.copy()[1:4, :]
compare_arrays(arr, arr_2, arr_3)
# Select items by Logic operations in arrays
arr = np.arange(100).reshape(10, 10)
bol = arr > 50
arr_2 = arr.copy()[bol]
print(arr)
print(bol)
print(arr_2)
"""
Numpy Array Operations
"""
arr = np.arange(0, 16)
# sum
arr_2 = arr + arr
print(arr_2)
# sub
arr_2 = arr - arr
print(arr_2)
# multiplication
arr_2 = arr * arr
print(arr_2)
# division
arr_2 = arr / arr
"""
Error message equivalent to ZeroDivisionError in array operation (which not raise an error, and returns nan instead in 0/0)
<ipython-input-105-1a13d9f299b5>:1: RuntimeWarning: invalid value encountered in true_divide
arr_2 = arr / arr
[nan 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
"""
# Index by index division
arr_3 = 1 / arr
"""
Error message equivalent to ZeroDivisionError in array operation (which not raise an error, and returns inf instead in 1/0)
"""
print(arr_2)
# Exponentiation: index by index
# Are the same with +, - * and / operations
arr_2 = arr ** 2
print(arr_2)
# square root
arr_2 = np.sqrt(arr)
# exponentiation of all array
arr_2 = np.exp(arr)
# mean
mean: np.float64 = np.mean(arr)
# standard deviation
std: np.float64 = np.std(arr)
# sin
arr_2: np.float64 = np.sin(arr)
# the major value of the array
max_value: np.int64 = np.max(arr)
max_value: np.int64 = arr.max()
# the mininum value of the array
min_value: np.int64 = np.min(arr)
min_value: np.int64 = arr.min() |
def is_palindrome_permutation(strng):
cache = set()
for char in strng.lower():
if char in cache:
cache.remove(char)
else:
cache.add(char)
return len(cache) <= 1
is_palindrome_permutation('RACECAR') |
import cv2
def bgr8_to_jpeg(value):
if value is None:
return bytes()
return bytes(cv2.imencode('.jpg', value)[1]) |
from soda.execution.table import Table
class Column:
def __init__(self, table: "Table", column_name: str):
from soda.sodacl.column_configurations_cfg import ColumnConfigurationsCfg
self.data_source_scan = table.data_source_scan
self.table = table
self.column_name = str(column_name)
self.column_configurations_cfg: ColumnConfigurationsCfg = None
def set_column_configuration_cfg(self, column_configurations_cfg: "ColumnConfigurationsCfg"):
self.column_configurations_cfg = column_configurations_cfg
@classmethod
def get_partition_name(cls, column):
return column.column_name if isinstance(column, Column) else None
|
import numpy as np
import sys
from ..mike_model.tariff import Tariff
class Customer:
"""Can be resident, strata body, or ENO representing aggregation of residents."""
def __init__(self, name, study, timeseries):
self.name = name
self.study = study
self.ts = timeseries
self.tariff_data = self.study.tariff_data
self.en_capex_repayment = 0
self.en_opex = 0
self.bat_capex_repayment = 0
self.exports = np.zeros(self.ts.get_num_steps())
self.imports = np.zeros(self.ts.get_num_steps())
# self.local_exports = np.zeros(ts.get_num_steps()) # not used, available for local trading
self.solar_allocation = np.zeros(self.ts.get_num_steps()) # used for allocation of local generation
self.local_consumption = np.zeros(self.ts.get_num_steps())
self.flows = np.zeros(self.ts.get_num_steps())
self.cash_flows = np.zeros(self.ts.get_num_steps())
self.import_charge = np.zeros(self.ts.get_num_steps())
self.local_solar_bill = 0
self.total_payment = 0
# TODO My linter wants everything instantiated within the init
self.load = None
self.coincidence = None
self.tariff_id = None
self.scenario = None
self.tariff = None
self.generation = None
self.demand_charge = None
self.npv = None
self.energy_bill = None
# as 1-d np.array
def initialise_customer_load(self, customer_load):
"""Set customer load, energy flows and cashflows to zero."""
self.load = customer_load
# used for calculating self-consumption and self sufficiency
self.coincidence = np.zeros(self.ts.get_num_steps())
def initialise_customer_tariff(self, customer_tariff_id, scenario):
self.tariff_id = customer_tariff_id
self.scenario = scenario
self.tariff = Tariff(tariff_id=self.tariff_id, scenario=scenario)
def initialise_customer_pv(self, pv_generation): # 1-D array
self.generation = pv_generation
def calc_static_energy(self):
"""Calculate Customer imports and exports for whole time period"""
self.flows = self.generation - self.load
self.exports = self.flows.clip(0)
self.imports = (-1 * self.flows).clip(0)
# # Calculate local quota here??
# self.solar_allocation = np.minimum(self.imports, self.local_quota) # for use of local generation
# for btm_p and btm_s arrangements:
self.local_consumption = np.minimum(self.generation, self.load)
def calc_dynamic_energy(self, step):
"""Calculate Customer imports and exports for single timestep"""
# Used for scenarios with batteries
# -------------------------------------------------------------------------------
# Calculate energy flow without battery, then modify by calling battery.dispatch:
# -------------------------------------------------------------------------------
self.flows[step] = self.generation[step] - self.load[step]
if self.has_battery:
self.flows[step] = self.battery.dispatch(generation=self.generation[step],
load=self.load[step],
step=step)
else:
self.flows[step] = self.generation[step] - self.load[step]
self.exports[step] = self.flows[step].clip(0)
self.imports[step] = (-1 * self.flows[step]).clip(0)
# Calculate local quota here??
# # Solar allocation is for solar_instantaneous tariff
# self.solar_allocation[step] = np.minimum(self.imports[step], self.local_quota[step])
# Local Consumption is PV self-consumed by customer (which is charged for in btm_p arrangement)
self.local_consumption[step] = np.minimum(self.generation[step], self.load[step])
def calc_demand_charge(self):
if self.tariff.is_demand:
max_demand = np.multiply(self.imports, self.tariff.demand_period_array).max() * 2 # convert kWh to kW
self.demand_charge = max_demand * self.tariff.demand_tariff * self.ts.get_num_days()
# Use nominal pf to convert to kVA?
if self.tariff.demand_type == 'kVA':
self.demand_charge = self.demand_charge / self.tariff.assumed_pf
else:
self.demand_charge = 0
def calc_cash_flow(self):
"""Calculate receipts and payments for customer.
self.cashflows is net volumetric import & export charge,
self.energy_bill is total elec bill, ic fixed charges
self.total_payment includes opex & capex repayments"""
if any(s in self.tariff.solar_rate_name for s in ['self_con', 'Self_Con', 'sc', 'SC']):
# IFF solar tariff paid to secondary solar retailer for self-consumed generation
# and export FiT paid for exported generation
# NB cost of exported self generation is received from retailer and passed to PV seller, so zero net effect
# Energy flows treated as if PV is owned by customer
self.local_solar_bill = (np.multiply(self.local_consumption, self.tariff.solar_import_tariff) + \
np.multiply(self.exports, self.tariff.export_tariff)).sum()
else:
self.local_solar_bill = 0.0
if self.tariff.is_dynamic:
# ------------------------------------
# calculate tariffs and costs stepwise
# ------------------------------------
for step in np.arange(0, self.ts.get_num_steps()):
# print(step)
# --------------------------------------------------------------
# Solar Block Daily Tariff : Calculate energy used at solar rate
# --------------------------------------------------------------
# Fixed daily allocation (set as % of annual generation) charged at solar rate,
# residual is at underlying, e.g. TOU
if 'Solar_Block_Daily' in self.tariff.tariff_type:
print('Solar_Block_Daily NOT SUPPORTED')
sys.exit('Solar_Block_Daily NOT SUPPORTED')
# SOLAR BLOCK DAILY REMOVED
# steps_today = ts.steps_today(step)
# # Cumulative Energy for this day:
# cumulative_energy = self.imports[steps_today].sum()
# if len(steps_today) <= 1:
# previous_energy = 0
# else:
# previous_energy = self.imports[steps_today[:-1]].sum()
# # Allocate local solar allocation depending on cumulative energy relative to quota:
# if cumulative_energy <= self.daily_local_quota:
# self.solar_allocation[step] = self.imports[step]
# elif previous_energy < self.daily_local_quota \
# and cumulative_energy > self.daily_local_quota:
# self.solar_allocation[step] = self.daily_local_quota - previous_energy
# else:
# self.solar_allocation[step] = 0
else:
# ---------------------------------------------------------
# For Block Tariffs, calc volumetric charges for each block
# ---------------------------------------------------------
# Block Quarterly Tariff
# ----------------------
if self.tariff.tariff_type == 'Block_Quarterly':
steps_since_reset = np.mod((step - self.tariff.block_billing_start),
self.tariff.steps_in_block) # to include step0
cumulative_energy = self.imports[
step - steps_since_reset:step + 1].sum() # NB only adds to step
if steps_since_reset == 0:
previous_energy = 0
else:
previous_energy = self.imports[step - steps_since_reset:step].sum() # NB adds to step-1
# Block Daily Tariff
# -------------------
elif self.tariff.tariff_type == 'Block_Daily':
steps_today = self.ts.steps_today(step)
cumulative_energy = self.imports[steps_today].sum()
if len(steps_today) <= 1:
previous_energy = 0
else:
previous_energy = self.imports[steps_today[:-1]].sum()
if cumulative_energy - previous_energy - self.imports[step] > 0.01:
print('accumulation error')
# All Block Tariffs:
# -----------------
if cumulative_energy <= self.tariff.high_1:
self.import_charge[step] = self.imports[step] * self.tariff.block_rate_1
elif previous_energy < self.tariff.high_1 and cumulative_energy <= self.tariff.high_2:
self.import_charge[step] = (self.tariff.high_1 - previous_energy) * self.tariff.block_rate_1 + \
(cumulative_energy - self.tariff.high_1) * self.tariff.block_rate_2
elif previous_energy > self.tariff.high_1 and cumulative_energy <= self.tariff.high_2:
self.import_charge[step] = self.imports[step] * self.tariff.block_rate_2
elif previous_energy < self.tariff.high_2 and cumulative_energy > self.tariff.high_2:
self.import_charge[step] = (self.tariff.high_2 - previous_energy) * self.tariff.block_rate_2 + \
(cumulative_energy - self.tariff.high_2) * self.tariff.block_rate_3
elif previous_energy >= self.tariff.high_2:
self.import_charge[step] = self.imports[step] * self.tariff.block_rate_3
elif previous_energy < self.tariff.high_1 and cumulative_energy > self.tariff.high_2:
self.import_charge[step] = (self.tariff.high_1 - previous_energy) * self.tariff.block_rate_1 + \
(
self.tariff.high_2 - self.tariff.high_1) * self.tariff.block_rate_2 + \
(cumulative_energy - self.tariff.high_2) * self.tariff.block_rate_3
# -------------------------------------------------------------
# calculate costs using array for static and underlying tariffs
# -------------------------------------------------------------
if self.tariff.tariff_type == 'Solar_Block_Daily' or not self.tariff.is_dynamic:
self.import_charge = np.multiply((self.imports - self.solar_allocation), self.tariff.import_tariff)
# For all dynamic and static tariffs:
# -----------------------------------
self.cash_flows = self.import_charge \
+ np.multiply(self.solar_allocation, self.tariff.solar_import_tariff) \
- np.multiply(self.exports, self.tariff.export_tariff)
# - np.multiply(self.local_exports, self.tariff.local_export_tariff) could be added for LET / P2P
# (These are all 1x17520 Arrays.)
self.energy_bill = self.cash_flows.sum() + self.tariff.fixed_charge * self.ts.get_num_days() + self.demand_charge
if self.name == 'retailer':
self.total_payment = self.energy_bill
else:
# capex, opex in $, energy in c (because tariffs in c/kWh)
self.total_payment = self.energy_bill + \
self.local_solar_bill + \
(self.pv_capex_repayment +
self.en_capex_repayment +
self.en_opex +
self.bat_capex_repayment) * 100
# --------
# Calc NPV
# --------
self.npv = -sum(self.total_payment / (1 + self.scenario.a_rate / 12) ** t
for t in np.arange(1, 12 * self.scenario.a_term)) |
from django.db.models.signals import class_prepared
def patch_user(sender, *args, **kwargs):
authmodels = 'django.contrib.auth.models'
if sender.__name__ == 'User' and sender.__module__ == authmodels:
# patch the length
sender._meta.get_field('username').max_length = 80
# patch the help text
help_text = "Required. 80 characters or fewer."
sender._meta.get_field('username').help_text = help_text
# remove the unique constraint
sender._meta.get_field('username').unique = False
class_prepared.connect(patch_user)
# Monkey patch the default admin login form with our custom form
def patch_admin_login():
from django import forms
from django.contrib import admin
from django.contrib import auth
ERROR_MESSAGE = "Please enter a correct organization, username, and password."
def patched_clean(self):
organization = self.cleaned_data.get('organization')
username = self.cleaned_data.get('username')
password = self.cleaned_data.get('password')
message = ERROR_MESSAGE
if all([organization, username, password]):
self.user_cache = auth.authenticate(organization=organization,
username=username,
password=password)
if not self.user_cache:
raise forms.ValidationError(message)
if not self.user_cache.is_active or not self.user_cache.is_staff:
raise forms.ValidationError(message)
self.check_for_test_cookie()
return self.cleaned_data
org_field = forms.CharField(max_length=80)
admin.forms.AdminAuthenticationForm.base_fields['organization'] = org_field
admin.forms.AdminAuthenticationForm.clean = patched_clean
patch_admin_login()
|
# Created by MechAviv
# Quest ID :: 61145
# Mysterious Merchant Matilda
sm.setSpeakerID(9201451)
sm.removeEscapeButton()
sm.flipDialogue()
sm.sendNext("Hi! My name is #bMatilda#k.\r\nI sell lots of handy stuff. And not like those OTHER people that say that.\r\n You have the look of someone about to do something stupid and dangerous. #bI can help!#k")
sm.setSpeakerID(9201451)
sm.removeEscapeButton()
sm.flipDialogue()
sm.sendSay("How about letting me sell you some stuff that might keep you less dead?\r\n#i4143000# #i4140001# #i4142000# #i2501000# #i2500000# #i2320000#\r\nAll you need are #e#bmesos#n#k to get my nifty items.")
sm.setSpeakerID(9201451)
sm.removeEscapeButton()
sm.flipDialogue()
sm.sendSay("#bCome visit me in town. Any town!#k\r\nI like to stay mobile.")
sm.startQuest(61145)
sm.completeQuest(61145)
|
from django.db import models
from django.contrib.auth.models import User
class Ban( models.Model ):
id = models.AutoField( primary_key = True )
user = models.OneToOneField( User )
ip_address = models.IPAddressField()
start_dtm = models.DateTimeField()
end_dtm = models.DateTimeField()
permaban = models.BooleanField()
reason = models.TextField()
def __unicode__( self ):
return self.user.name
class Meta:
db_table = 'rpf_ban'
app_label= 'rpf'
|
# 배열 array의 i번째 숫자부터 j번째 숫자까지 자르고 정렬했을 때, k번째에 있는 수를 구하려 합니다.
# 예를 들어 array가 [1, 5, 2, 6, 3, 7, 4], i = 2, j = 5, k = 3이라면
# array의 2번째부터 5번째까지 자르면 [5, 2, 6, 3]입니다.
# 1에서 나온 배열을 정렬하면 [2, 3, 5, 6]입니다.
# 2에서 나온 배열의 3번째 숫자는 5입니다.
# 배열 array, [i, j, k]를 원소로 가진 2차원 배열 commands가 매개변수로 주어질 때,
# commands의 모든 원소에 대해 앞서 설명한 연산을 적용했을 때 나온 결과를 배열에 담아 return 하도록 solution 함수를 작성해주세요.
def solution(array, commands):
answer = []
for i in range(len(commands)):
tmp =[]
tmp.append(array[commands[i][0]-1:commands[i][1]])
tmp[0].sort()
answer.append(tmp[0][commands[i][2]-1])
return answer
print(solution([1,5,2,6,3,7,4],[[2,5,3],[4,4,1],[1,7,3]]))
# def solution(array, commands):
# return list(map(lambda x:sorted(array[x[0]-1:x[1]])[x[2]-1], commands))
|
import gym
import gym.spaces as spaces
import Game
class CustomEnv(gym.Env):
def __init__(self):
self.pygame = Game.Pygame2D()
self.action_space = spaces.Discrete(180)
rows_player_obs = [5] * 15
penality_player_obs = [1] * 7
board_player_obs = [1] * 25
normal_pit_obs = [4] * 5 * 5
#al massimo ci possono essere 3*5 tessere nel discard pit per una singola tessera
discard_pit_obs = [3*5] * 5
one_player_obs = rows_player_obs + penality_player_obs + board_player_obs + \
normal_pit_obs + discard_pit_obs
self.observation_space = spaces.MultiDiscrete(one_player_obs)
def reset(self):
del self.pygame
self.pygame = Game.Pygame2D()
obs = self.pygame.observe()
return obs
def step(self, action):
self.pygame.action(action)
obs = self.pygame.observe()
reward = self.pygame.evaluete()
done = self.pygame.is_done()
return obs,reward,done,{}
def render(self, mode='human'):
print(self.pygame.view()) |
from details.models import Person
from django.forms import Textarea, CheckboxSelectMultiple
from django.forms.models import ModelMultipleChoiceField
from django.utils.translation import ugettext as _
from django.contrib import admin
from django.conf import settings
from django.db import models
from common.admintools import export_xlsx, printable_html
class PersonAdminAbstract(admin.ModelAdmin):
change_form_template = 'admin/my_change_form.html'
list_display = ('person_id','demographics_gender','demographics_age','person_creationDate','person_updateDate','person_user',)
list_filter = ('demographics_gender','demographics_age',)
search_fields = ['person_id',]
readonly_fields = ('person_id', 'person_creationDate', 'person_updateDate', 'person_user',)
fieldsets = [
('Demographics',{
'classes': ('suit-tab suit-tab-2demographics',),
'fields': ['demographics_gender','demographics_age','demographics_weight','demographics_weight']
}),
]
suit_form_tabs = [
(u'2demographics', u'2. Demographics')
]
radio_fields = {
'demographics_gender': admin.VERTICAL
}
actions = [export_xlsx,]
formfield_overrides = dict((
(models.TextField,dict((( 'widget',Textarea(attrs=dict(rows=5, cols=120,style='width: 600px;') )),) )),
(models.ManyToManyField,dict((('widget',CheckboxSelectMultiple),)))
),)
class Media:
css = dict(all=['generic.css','fixadmin.css'])
js = ('generic.js','models/person.js')
def save_model(self, request, obj, form, change):
if obj.pk==None: obj.person_user = request.user
super(PersonAdminAbstract, self).save_model(request, obj, form, change)
def queryset(self, request):
qs = super(PersonAdminAbstract, self).queryset(request)
groups = request.user.groups.all()
qs = qs.filter( person_user__groups = groups ).distinct()
return qs
def get_actions(self, request):
actions = super(PersonAdminAbstract, self).get_actions(request)
user = request.user
#if not user.groups.filter(name=settings.HTML_EXPORTER_PROFILE_GROUP).exists(): del actions['printable_html']
if not user.groups.filter(name=settings.EXCEL_EXPORTER_PROFILE_GROUP).exists(): del actions['export_xlsx']
return actions
def construct_change_message(self, request, form, formsets):
message = super(PersonAdminAbstract, self).construct_change_message(request, form, formsets)
change_message = []
if form.changed_data:
values = []
for x in form.changed_data:
field = form.fields[x]
initial = form.initial[x]
value = form.cleaned_data[x]
if isinstance(field, ModelMultipleChoiceField):
value = [int(y.pk) for y in value]
initial = [int(y) for y in initial]
values.append( _("<b>%s</b>: <span style='color:#4682B4' >%s</span> -> <span style='color:#00A600' >%s</span>" % (x, str(initial), str(value)) ) )
change_message.append( '<ul><li>%s</li></ul>' % '</li><li>'.join(values) )
message += ' '.join(change_message)
return message
|
"""
Model for the adventure.
"""
# pylint: disable=too-few-public-methods
from django.db import models
from .mixins import TimestampMixin, DescriptionNotesMixin
class Adventure(models.Model, TimestampMixin, DescriptionNotesMixin):
"""
Model for the adventure.
"""
name = models.CharField(max_length=128)
setting = models.ForeignKey('Setting', models.PROTECT,
related_name='adventures')
edition = models.ForeignKey('Edition', models.PROTECT,
related_name='adventures')
author = models.ForeignKey('Author', models.PROTECT,
related_name='adventures')
publisher = models.ForeignKey('Publisher', models.PROTECT,
related_name='adventures')
date = models.DateField()
characters = models.ManyToManyField('Character', related_name='adventures')
monsters = models.ManyToManyField('Monster', related_name='adventures')
items = models.ManyToManyField('Item', related_name='adventures')
format = models.CharField(max_length=128)
min_level = models.IntegerField()
max_level = models.IntegerField()
min_characters = models.IntegerField()
max_characters = models.IntegerField()
|
import json
import pandas as pd
import numpy as np
from tqdm import tqdm
def get_spdat_feat_types(df):
'''
Get lists of features containing the single-valued categorical and noncategorical feature names in the SPDAT data
:param df: Pandas DataFrame containing client SPDAT question info
:return: List of single-valued categorical features, list of noncategorical features
'''
sv_cat_feats = []
noncat_feats = []
for column in df.columns:
if df[column].dtype == 'object':
sv_cat_feats.append(column)
else:
noncat_feats.append(column)
return sv_cat_feats, noncat_feats
def get_spdat_data(spdat_path, gt_end_date):
'''
Read SPDAT data from raw SPDAT file and output a dataframe containing clients' answers to the questions.
:param spdat_path: The file path of the raw SPDAT data
:param gt_end_date: the date used for ground truth calculation
:return: A DataFrame in which each row is a client's answers to SPDAT questions
'''
def single_client_record(client_df):
'''
Helper function for SPDAT data preprocessing. Processes records for a single client.
:param client_df: Raw SPDAT data for 1 client
:return: DataFrame with 1 row detailing client's answers to SPDAT questions
'''
client_answers = dict.fromkeys(questions, [np.nan]) # The columns will be SPDAT questions
for row in client_df.itertuples():
question = getattr(row, 'QuestionE')
if question in questions:
answer = str(getattr(row, 'ScoreValue'))
answer = float(answer) if answer.isnumeric() else answer
client_answers[question] = [answer] # Set values to client's answers
return pd.DataFrame.from_dict(client_answers)
tqdm.pandas()
# Read JSON file containing SPDAT information. Remove line breaks.
with open(spdat_path, 'rb') as f:
json_str = f.read().decode('utf-16').replace('\r', '').replace('\n', '')
spdats = json.loads(json_str)['VISPDATS'] # Convert to object and get the list of SPDATs
df = pd.DataFrame(spdats) # Convert JSON object to pandas DataFrame
df.fillna(0, inplace=True)
# Remove records that were created after the ground truth end date
df['SPDAT_Date'] = pd.to_datetime(df['SPDAT_Date'], errors='coerce')
df = df[df['SPDAT_Date'] <= gt_end_date]
# Replace questions with ellipses with their corresponding descriptions
df.loc[df['QuestionE'].str.contains('...'), 'QuestionE'] = df['DescriptionE']
# For questions that have part (a), (b), (c), etc., append their question roots.
question_roots = []
last_question_root = ''
last_component_numeric = False
for row in df.itertuples():
component = str(getattr(row, 'Component'))
if component.isnumeric():
last_question_root = str(getattr(row, 'QuestionE'))
last_component_numeric = True
else:
if last_component_numeric:
if last_question_root not in question_roots:
question_roots.append(last_question_root)
last_component_numeric = False
df.set_value(row.Index, 'QuestionE', last_question_root + getattr(row, 'QuestionE'))
questions = df['QuestionE'].unique() # Get list of unique questions across all SPDAT versions
questions = [q for q in questions if q not in question_roots]
# Build a DataFrame in which each row is a client's answer to SPDAT questions
df_clients = df.groupby('ClientID').progress_apply(single_client_record)
df_clients.columns = df_clients.columns.str.replace('%', '')
df_clients.columns = df_clients.columns.str.replace('\r', '')
df_clients.columns = df_clients.columns.str.replace('\n', '')
df_clients = df_clients.droplevel(level=1, axis='index') # Ensure index is ClientID
print("# of clients with SPDAT = " + str(df_clients.shape[0]))
sv_cat_feats, noncat_feats = get_spdat_feat_types(df_clients) # Classify SPDAT questions as features
# Replace "0.0" with "Unknown" for categorical features
df_clients[sv_cat_feats] = df_clients[sv_cat_feats].replace(to_replace=0, value='Unknown')
return df_clients, sv_cat_feats, noncat_feats
|
## Ch09 P9.6
from car import Car
myCar = Car(50)
myCar.addGas(20)
myCar.drive(100)
print(myCar.getGasLevel()) |
def spiralNumbers(m):
mx = [[0 for i in range(m)] for j in range(m)]
cnt = 1
for i in range(m):
mx[0][i] = cnt
cnt += 1
n = m - 1
while cnt < m ** 2:
for j in range(m // 2):
for i in range(n):
mx[i + j + 1][m - j - 1] = cnt
cnt += 1
for i in range(n):
mx[m - j - 1][m - j - i - 2] = cnt
cnt += 1
n -= 1
for i in range(n):
mx[m - j - i - 2][j] = cnt
cnt += 1
for i in range(n):
mx[j + 1][j + i + 1] = cnt
cnt += 1
n -= 1
return mx
# рекурсионная формула на Py2
# def spiralNumbers(n, m=0, s=1):
# if m == 0:
# m = n
# if n == 1 == m:
# return [[s]]
#
# # Calculate spiral numbers without first row
# S = spiralNumbers(m - 1, n, s + n)
#
# # Create first row and add the transpose of the rest
# return [range(s, s + n)] + zip(*S[::-1])
print(spiralNumbers(5))
|
#!/usr/bin/env python
# coding: utf-8
# In[17]:
import cv2
import numpy as np
import glob
import matplotlib.pyplot as plt
import PIL
import time
import os
# In[49]:
img_dir = os.path.join(r"Images","*g")
img_dir = glob.glob(img_dir)
image_l = []
# In[50]:
def MSE(image1_gray_resized_np,image2_gray_resized_np):
return np.square(image1_gray_resized_np - image2_gray_resized_np).mean()
# In[51]:
def load_img_and_convert(str):
find_mse = lambda x,y:MSE(x,y)
img = cv2.imread(str)
img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
img = np.asarray(img)
img = cv2.resize(img,(224,224))
if len(image_l)==0:
image_l.append(img)
print("1")
else:
iso = list(map(lambda x:find_mse(x,img),image_l))
check = all(map(lambda x:x>102,iso))
# print(check,iso)
if check:
image_l.append(img)
# In[52]:
def plot_image():
_,axs = plt.subplots(image_l.shape[0]//3 + 1,3,figsize = (12,12))
axs = axs.flatten()
for img,ax in zip(image_l,axs):
ax.imshow(cv2.cvtColor(img,cv2.COLOR_GRAY2BGR))
plt.axis("off")
plt.show()
# In[53]:
for i in img_dir:
try:
load_img_and_convert(i)
except Exception as e:
print(e)
# In[54]:
print(len(image_l),len(img_dir))
image_l = np.asarray(image_l)
print(image_l.shape)
# In[55]:
plot_image()
|
# Handle all the exceptions!
#Setup
actor = {"name": "John Cleese", "rank": "awesome"}
#Function to modify, should return the last name of the actor [try except block]
def get_last_name():
try:
return actor["last_name"]
except:
namelist=[]
namelist= actor["name"].split()
return namelist[1]
#Test code
get_last_name()
print ("All exceptions caught! Good job!")
print ("The actor's last name is %s" % get_last_name()) |
HTTP_HEADER_LIST = [
"REMOTE_ADDR",
"REMOTE_HOST",
"X_FORWARDED_FOR",
"TZ",
"QUERY_STRING",
"CONTENT_LENGTH",
"CONTENT_TYPE",
"LC_CTYPE",
"SERVER_PROTOCOL",
"SERVER_SOFTWARE",
]
MASKED_DATA = "XXXXXXXXX"
CONTENT_TYPE_JSON = "application/json"
CONTENT_TYPE_METHOD_MAP = {CONTENT_TYPE_JSON: "_get_json_data"}
CLIENT_ERROR_SET = {
"AttributeError",
"IntegrityError",
"KeyError",
"ValidationError",
}
BUILTIN_ERROR_MESSAGE = {
"Http404": "Not found",
"PermissionDenied": "Permission denied.",
}
MODEL_VIEWSET_METHODNAMES = ["create", "retrieve", "list", "update", "destroy"]
RESPONSE_KEY_DATA = "data"
RESPONSE_KEY_ERROR = "error"
RESPONSE_KEY_IS_SUCCESS = "is_success"
|
# Copyright (c) 2010 Jeremy Thurgood <firxen+boto@gmail.com>
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish, dis-
# tribute, sublicense, and/or sell copies of the Software, and to permit
# persons to whom the Software is furnished to do so, subject to the fol-
# lowing conditions:
#
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABIL-
# ITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT
# SHALL THE AUTHOR BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
# IN THE SOFTWARE.
# NOTE: These tests only cover the very simple cases I needed to test
# for the InstanceGroup fix.
import xml.sax
from boto import handler
from boto.emr import emrobject
from boto.resultset import ResultSet
from tests.compat import unittest
JOB_FLOW_EXAMPLE = b"""
<DescribeJobFlowsResponse
xmlns="http://elasticmapreduce.amazonaws.com/doc/2009-01-15">
<DescribeJobFlowsResult>
<JobFlows>
<member>
<ExecutionStatusDetail>
<CreationDateTime>2009-01-28T21:49:16Z</CreationDateTime>
<StartDateTime>2009-01-28T21:49:16Z</StartDateTime>
<State>STARTING</State>
</ExecutionStatusDetail>
<BootstrapActions>
<member>
<BootstrapActionConfig>
<ScriptBootstrapAction>
<Args/>
<Path>s3://elasticmapreduce/libs/hue/install-hue</Path>
</ScriptBootstrapAction>
<Name>Install Hue</Name>
</BootstrapActionConfig>
</member>
</BootstrapActions>
<VisibleToAllUsers>true</VisibleToAllUsers>
<SupportedProducts>
<member>Hue</member>
</SupportedProducts>
<Name>MyJobFlowName</Name>
<LogUri>mybucket/subdir/</LogUri>
<Steps>
<member>
<ExecutionStatusDetail>
<CreationDateTime>2009-01-28T21:49:16Z</CreationDateTime>
<State>PENDING</State>
</ExecutionStatusDetail>
<StepConfig>
<HadoopJarStep>
<Jar>MyJarFile</Jar>
<MainClass>MyMailClass</MainClass>
<Args>
<member>arg1</member>
<member>arg2</member>
</Args>
<Properties/>
</HadoopJarStep>
<Name>MyStepName</Name>
<ActionOnFailure>CONTINUE</ActionOnFailure>
</StepConfig>
</member>
</Steps>
<JobFlowId>j-3UN6WX5RRO2AG</JobFlowId>
<Instances>
<Placement>
<AvailabilityZone>us-east-1a</AvailabilityZone>
</Placement>
<SlaveInstanceType>m1.small</SlaveInstanceType>
<MasterInstanceType>m1.small</MasterInstanceType>
<Ec2KeyName>myec2keyname</Ec2KeyName>
<InstanceCount>4</InstanceCount>
<KeepJobFlowAliveWhenNoSteps>true</KeepJobFlowAliveWhenNoSteps>
</Instances>
</member>
</JobFlows>
</DescribeJobFlowsResult>
<ResponseMetadata>
<RequestId>9cea3229-ed85-11dd-9877-6fad448a8419</RequestId>
</ResponseMetadata>
</DescribeJobFlowsResponse>
"""
JOB_FLOW_COMPLETED = b"""
<DescribeJobFlowsResponse xmlns="http://elasticmapreduce.amazonaws.com/doc/2009-03-31">
<DescribeJobFlowsResult>
<JobFlows>
<member>
<ExecutionStatusDetail>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<LastStateChangeReason>Steps completed</LastStateChangeReason>
<StartDateTime>2010-10-21T01:03:59Z</StartDateTime>
<ReadyDateTime>2010-10-21T01:03:59Z</ReadyDateTime>
<State>COMPLETED</State>
<EndDateTime>2010-10-21T01:44:18Z</EndDateTime>
</ExecutionStatusDetail>
<BootstrapActions/>
<Name>RealJobFlowName</Name>
<LogUri>s3n://example.emrtest.scripts/jobflow_logs/</LogUri>
<Steps>
<member>
<StepConfig>
<HadoopJarStep>
<Jar>s3n://us-east-1.elasticmapreduce/libs/script-runner/script-runner.jar</Jar>
<Args>
<member>s3n://us-east-1.elasticmapreduce/libs/state-pusher/0.1/fetch</member>
</Args>
<Properties/>
</HadoopJarStep>
<Name>Setup Hadoop Debugging</Name>
<ActionOnFailure>TERMINATE_JOB_FLOW</ActionOnFailure>
</StepConfig>
<ExecutionStatusDetail>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<StartDateTime>2010-10-21T01:03:59Z</StartDateTime>
<State>COMPLETED</State>
<EndDateTime>2010-10-21T01:04:22Z</EndDateTime>
</ExecutionStatusDetail>
</member>
<member>
<StepConfig>
<HadoopJarStep>
<Jar>/home/hadoop/contrib/streaming/hadoop-0.20-streaming.jar</Jar>
<Args>
<member>-mapper</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-InitialMapper.py</member>
<member>-reducer</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-InitialReducer.py</member>
<member>-input</member>
<member>s3://example.emrtest.data/raw/2010/10/20/*</member>
<member>-input</member>
<member>s3://example.emrtest.data/raw/2010/10/19/*</member>
<member>-input</member>
<member>s3://example.emrtest.data/raw/2010/10/18/*</member>
<member>-input</member>
<member>s3://example.emrtest.data/raw/2010/10/17/*</member>
<member>-input</member>
<member>s3://example.emrtest.data/raw/2010/10/16/*</member>
<member>-input</member>
<member>s3://example.emrtest.data/raw/2010/10/15/*</member>
<member>-input</member>
<member>s3://example.emrtest.data/raw/2010/10/14/*</member>
<member>-output</member>
<member>s3://example.emrtest.crunched/</member>
</Args>
<Properties/>
</HadoopJarStep>
<Name>testjob_Initial</Name>
<ActionOnFailure>TERMINATE_JOB_FLOW</ActionOnFailure>
</StepConfig>
<ExecutionStatusDetail>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<StartDateTime>2010-10-21T01:04:22Z</StartDateTime>
<State>COMPLETED</State>
<EndDateTime>2010-10-21T01:36:18Z</EndDateTime>
</ExecutionStatusDetail>
</member>
<member>
<StepConfig>
<HadoopJarStep>
<Jar>/home/hadoop/contrib/streaming/hadoop-0.20-streaming.jar</Jar>
<Args>
<member>-mapper</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step1Mapper.py</member>
<member>-reducer</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step1Reducer.py</member>
<member>-input</member>
<member>s3://example.emrtest.crunched/*</member>
<member>-output</member>
<member>s3://example.emrtest.step1/</member>
</Args>
<Properties/>
</HadoopJarStep>
<Name>testjob_step1</Name>
<ActionOnFailure>TERMINATE_JOB_FLOW</ActionOnFailure>
</StepConfig>
<ExecutionStatusDetail>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<StartDateTime>2010-10-21T01:36:18Z</StartDateTime>
<State>COMPLETED</State>
<EndDateTime>2010-10-21T01:37:51Z</EndDateTime>
</ExecutionStatusDetail>
</member>
<member>
<StepConfig>
<HadoopJarStep>
<Jar>/home/hadoop/contrib/streaming/hadoop-0.20-streaming.jar</Jar>
<Args>
<member>-mapper</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step2Mapper.py</member>
<member>-reducer</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step2Reducer.py</member>
<member>-input</member>
<member>s3://example.emrtest.crunched/*</member>
<member>-output</member>
<member>s3://example.emrtest.step2/</member>
</Args>
<Properties/>
</HadoopJarStep>
<Name>testjob_step2</Name>
<ActionOnFailure>TERMINATE_JOB_FLOW</ActionOnFailure>
</StepConfig>
<ExecutionStatusDetail>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<StartDateTime>2010-10-21T01:37:51Z</StartDateTime>
<State>COMPLETED</State>
<EndDateTime>2010-10-21T01:39:32Z</EndDateTime>
</ExecutionStatusDetail>
</member>
<member>
<StepConfig>
<HadoopJarStep>
<Jar>/home/hadoop/contrib/streaming/hadoop-0.20-streaming.jar</Jar>
<Args>
<member>-mapper</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step3Mapper.py</member>
<member>-reducer</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step3Reducer.py</member>
<member>-input</member>
<member>s3://example.emrtest.step1/*</member>
<member>-output</member>
<member>s3://example.emrtest.step3/</member>
</Args>
<Properties/>
</HadoopJarStep>
<Name>testjob_step3</Name>
<ActionOnFailure>TERMINATE_JOB_FLOW</ActionOnFailure>
</StepConfig>
<ExecutionStatusDetail>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<StartDateTime>2010-10-21T01:39:32Z</StartDateTime>
<State>COMPLETED</State>
<EndDateTime>2010-10-21T01:41:22Z</EndDateTime>
</ExecutionStatusDetail>
</member>
<member>
<StepConfig>
<HadoopJarStep>
<Jar>/home/hadoop/contrib/streaming/hadoop-0.20-streaming.jar</Jar>
<Args>
<member>-mapper</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step4Mapper.py</member>
<member>-reducer</member>
<member>s3://example.emrtest.scripts/81d8-5a9d3df4a86c-step4Reducer.py</member>
<member>-input</member>
<member>s3://example.emrtest.step1/*</member>
<member>-output</member>
<member>s3://example.emrtest.step4/</member>
</Args>
<Properties/>
</HadoopJarStep>
<Name>testjob_step4</Name>
<ActionOnFailure>TERMINATE_JOB_FLOW</ActionOnFailure>
</StepConfig>
<ExecutionStatusDetail>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<StartDateTime>2010-10-21T01:41:22Z</StartDateTime>
<State>COMPLETED</State>
<EndDateTime>2010-10-21T01:43:03Z</EndDateTime>
</ExecutionStatusDetail>
</member>
</Steps>
<JobFlowId>j-3H3Q13JPFLU22</JobFlowId>
<Instances>
<SlaveInstanceType>m1.large</SlaveInstanceType>
<MasterInstanceId>i-64c21609</MasterInstanceId>
<Placement>
<AvailabilityZone>us-east-1b</AvailabilityZone>
</Placement>
<InstanceGroups>
<member>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<InstanceRunningCount>0</InstanceRunningCount>
<StartDateTime>2010-10-21T01:02:09Z</StartDateTime>
<ReadyDateTime>2010-10-21T01:03:03Z</ReadyDateTime>
<State>ENDED</State>
<EndDateTime>2010-10-21T01:44:18Z</EndDateTime>
<InstanceRequestCount>1</InstanceRequestCount>
<InstanceType>m1.large</InstanceType>
<Market>ON_DEMAND</Market>
<LastStateChangeReason>Job flow terminated</LastStateChangeReason>
<InstanceRole>MASTER</InstanceRole>
<InstanceGroupId>ig-EVMHOZJ2SCO8</InstanceGroupId>
<Name>master</Name>
</member>
<member>
<CreationDateTime>2010-10-21T01:00:25Z</CreationDateTime>
<InstanceRunningCount>0</InstanceRunningCount>
<StartDateTime>2010-10-21T01:03:59Z</StartDateTime>
<ReadyDateTime>2010-10-21T01:03:59Z</ReadyDateTime>
<State>ENDED</State>
<EndDateTime>2010-10-21T01:44:18Z</EndDateTime>
<InstanceRequestCount>9</InstanceRequestCount>
<InstanceType>m1.large</InstanceType>
<Market>ON_DEMAND</Market>
<LastStateChangeReason>Job flow terminated</LastStateChangeReason>
<InstanceRole>CORE</InstanceRole>
<InstanceGroupId>ig-YZHDYVITVHKB</InstanceGroupId>
<Name>slave</Name>
</member>
</InstanceGroups>
<NormalizedInstanceHours>40</NormalizedInstanceHours>
<HadoopVersion>0.20</HadoopVersion>
<MasterInstanceType>m1.large</MasterInstanceType>
<MasterPublicDnsName>ec2-184-72-153-139.compute-1.amazonaws.com</MasterPublicDnsName>
<Ec2KeyName>myubersecurekey</Ec2KeyName>
<InstanceCount>10</InstanceCount>
<KeepJobFlowAliveWhenNoSteps>false</KeepJobFlowAliveWhenNoSteps>
</Instances>
</member>
</JobFlows>
</DescribeJobFlowsResult>
<ResponseMetadata>
<RequestId>c31e701d-dcb4-11df-b5d9-337fc7fe4773</RequestId>
</ResponseMetadata>
</DescribeJobFlowsResponse>
"""
class TestEMRResponses(unittest.TestCase):
def _parse_xml(self, body, markers):
rs = ResultSet(markers)
h = handler.XmlHandler(rs, None)
xml.sax.parseString(body, h)
return rs
def _assert_fields(self, response, **fields):
for field, expected in fields.items():
actual = getattr(response, field)
self.assertEquals(expected, actual,
"Field %s: %r != %r" % (field, expected, actual))
def test_JobFlows_example(self):
[jobflow] = self._parse_xml(JOB_FLOW_EXAMPLE,
[('member', emrobject.JobFlow)])
self._assert_fields(jobflow,
creationdatetime='2009-01-28T21:49:16Z',
startdatetime='2009-01-28T21:49:16Z',
state='STARTING',
instancecount='4',
jobflowid='j-3UN6WX5RRO2AG',
loguri='mybucket/subdir/',
name='MyJobFlowName',
availabilityzone='us-east-1a',
slaveinstancetype='m1.small',
masterinstancetype='m1.small',
ec2keyname='myec2keyname',
keepjobflowalivewhennosteps='true')
def test_JobFlows_completed(self):
[jobflow] = self._parse_xml(JOB_FLOW_COMPLETED,
[('member', emrobject.JobFlow)])
self._assert_fields(jobflow,
creationdatetime='2010-10-21T01:00:25Z',
startdatetime='2010-10-21T01:03:59Z',
enddatetime='2010-10-21T01:44:18Z',
state='COMPLETED',
instancecount='10',
jobflowid='j-3H3Q13JPFLU22',
loguri='s3n://example.emrtest.scripts/jobflow_logs/',
name='RealJobFlowName',
availabilityzone='us-east-1b',
slaveinstancetype='m1.large',
masterinstancetype='m1.large',
ec2keyname='myubersecurekey',
keepjobflowalivewhennosteps='false')
self.assertEquals(6, len(jobflow.steps))
self.assertEquals(2, len(jobflow.instancegroups))
|
'''
Surprisingly there are only three numbers that can be written as the sum of fourth powers of their digits:
1634 = 14 + 64 + 34 + 44
8208 = 84 + 24 + 04 + 84
9474 = 94 + 44 + 74 + 44
As 1 = 14 is not a sum it is not included.
The sum of these numbers is 1634 + 8208 + 9474 = 19316.
Find the sum of all the numbers that can be written as the sum of fifth powers of their digits.
'''
def sum_of_digits(n, p):
sum = 0
while n > 0:
sum += (n % 10) ** p
n /= 10
return sum
print sum(n for n in xrange(2, 200000) if sum_of_digits(n, 5) == n)
|
# Prim algorithm
# input where n is weight of each edge
# 0,2,1,0,0
# 2,0,1,2,3
# 1,1,0,0,4
# 0,2,0,0,2
# 0,3,4,2,0
import random as rand
def printGraph(g):
for row in g:
print (row)
print ("---------------------------\n")
def fillGraph (inputfile):
graph = []
f = open(inputfile,"r+")
numberOfVertexes = 0
for row in f:
row = row.split(',')
row = [int(x) for x in row]
graph.append(row)
numberOfVertexes += 1
f.close()
return graph, numberOfVertexes
def findEdge (g,n,T,N):
menor = 0xFFFFFFFF
for row in T:
for column in N:
element = g[row][column]
if element < menor and element != 0:
menor = element
y = row
x = column
return x,y
def prim (g, n):
Tmin = set() # set of minimum tree
T = set() # set of visited vertexes
N = set() # set of non-visited vertexes
for idx in range(n):
N.add(idx)
i = rand.randrange(0,n)
cost = 0
T.add(i)
N.remove(i)
while len(T) != n:
ex, ey = findEdge(g,n,T,N)
T.add(ex)
N.remove(ex)
Tmin.add(ex)
Tmin.add(ey)
print (ey,'->',ex,':',g[ex][ey])
cost = cost + g[ex][ey]
print ("Custo da árvore geradora mínima:",cost)
def main():
inputfile = "graphs/g3.txt" # Open file
g, n = fillGraph(inputfile) # Fill graph
print ("Grafo Original: ")
printGraph(g) # Print graph
prim(g,n)
main() |
from setuptools import setup, find_packages
setup(
name='pyIID',
version='',
packages=find_packages(exclude=['doc', 'benchmarks', 'extra', 'scripts', 'examples' ,]),
url='',
license='',
author='christopher',
author_email='',
description='', requires=['scipy']
)
|
import torch
a = torch.rand((16, 1024, 14, 24))
b = torch.rand((16, 1024, 14, 24))
c = torch.cat([a, b], dim=1)
print(c.shape) |
import torch
import torch.nn as nn
from torch.autograd import Variable
"""
Generator network
"""
class _netG(nn.Module):
def __init__(self, opt, nclasses):
super(_netG, self).__init__()
self.ndim = 2*opt.ndf
self.ngf = opt.ngf
self.nz = opt.nz
self.gpu = opt.gpu
self.nclasses = nclasses
self.main = nn.Sequential(
nn.ConvTranspose2d(self.nz+self.ndim+nclasses+1, self.ngf*8, 2, 1, 0, bias=False),
nn.BatchNorm2d(self.ngf*8),
nn.ReLU(True),
nn.ConvTranspose2d(self.ngf*8, self.ngf*4, 4, 2, 1, bias=False),
nn.BatchNorm2d(self.ngf*4),
nn.ReLU(True),
nn.ConvTranspose2d(self.ngf*4, self.ngf*2, 4, 2, 1, bias=False),
nn.BatchNorm2d(self.ngf*2),
nn.ReLU(True),
nn.ConvTranspose2d(self.ngf*2, self.ngf, 4, 2, 1, bias=False),
nn.BatchNorm2d(self.ngf),
nn.ReLU(True),
nn.ConvTranspose2d(self.ngf, 3, 4, 2, 1, bias=False),
nn.Tanh()
)
def forward(self, input):
batchSize = input.size()[0]
input = input.view(-1, self.ndim+self.nclasses+1, 1, 1)
noise = torch.FloatTensor(batchSize, self.nz, 1, 1).normal_(0, 1)
if self.gpu>=0:
noise = noise.cuda()
noisev = Variable(noise)
output = self.main(torch.cat((input, noisev),1))
return output
"""
Discriminator network
"""
class _netD(nn.Module):
def __init__(self, opt, nclasses):
super(_netD, self).__init__()
self.opt = opt
self.ndf = opt.ndf
self.feature = nn.Sequential(
nn.Conv2d(3, self.ndf, 3, 1, 1),
nn.BatchNorm2d(self.ndf),
nn.LeakyReLU(0.2, inplace=True),
nn.MaxPool2d(2,2),
nn.Conv2d(self.ndf, self.ndf*2, 3, 1, 1),
nn.BatchNorm2d(self.ndf*2),
nn.LeakyReLU(0.2, inplace=True),
nn.MaxPool2d(2,2),
nn.Conv2d(self.ndf*2, self.ndf*4, 3, 1, 1),
nn.BatchNorm2d(self.ndf*4),
nn.LeakyReLU(0.2, inplace=True),
nn.MaxPool2d(2,2),
nn.Conv2d(self.ndf*4, self.ndf*2, 3, 1, 1),
nn.BatchNorm2d(self.ndf*2),
nn.LeakyReLU(0.2, inplace=True),
nn.MaxPool2d(4,4)
)
self.classifier_s = nn.Sequential(
nn.Linear(self.ndf*2, 1),
nn.Sigmoid())
if opt.auxLoss:
self.classifier_c = nn.Sequential(nn.Linear(self.ndf*2, nclasses))
def forward(self, input):
output = self.feature(input)
output_s = self.classifier_s(output.view(-1, self.ndf*2))
output_s = output_s.view(-1)
if self.opt.auxLoss:
output_c = self.classifier_c(output.view(-1, self.ndf*2))
return output_s, output_c
else:
return output_s, None
"""
Feature extraction network
"""
class _netF(nn.Module):
def __init__(self, opt):
super(_netF, self).__init__()
self.opt = opt
self.ndf = opt.ndf
self.feature = nn.Sequential(
nn.Conv2d(3, self.ndf, 5, 1, 0),
nn.ReLU(inplace=True),
nn.MaxPool2d(2, 2),
nn.Conv2d(self.ndf, self.ndf, 5, 1, 0),
nn.ReLU(inplace=True),
nn.MaxPool2d(2, 2),
nn.Conv2d(self.ndf, self.ndf*2, 5, 1,0),
nn.ReLU(inplace=True)
)
if self.opt.vae:
self.mu = nn.Linear(self.ndf*2, self.ndf*2)
self.var = nn.Linear(self.ndf*2, self.ndf*2)
def forward(self, input):
output = self.feature(input)
output = output.view(-1, 2*self.ndf)
if self.opt.vae:
mu = self.mu(output)
var = self.var(output)
std = torch.exp(0.5*var)
eps = torch.randn_like(std)
return eps.mul(std).add_(mu), mu, var
return output, None, None
"""
Classifier network
"""
class _netC(nn.Module):
def __init__(self, opt, nclasses):
super(_netC, self).__init__()
self.ndf = opt.ndf
self.main = nn.Sequential(
nn.Linear(2*self.ndf, 2*self.ndf),
nn.ReLU(inplace=True),
nn.Linear(2*self.ndf, nclasses),
)
def forward(self, input):
output = self.main(input)
return output
|
# -*- coding=utf-8 -*-
#---------------------------------------
# 程序：豆瓣相册爬虫
# 版本：0.2
# 作者：Will
# 日期：2014-07-17
# 语言：Python 2.7
# 功能：将相册中照片全部抓下来
# 改进：优先抓取大图；用户只需输入相册编号，自动计算所有页
#---------------------------------------
import urllib
import re
import datetime
import time
import urllib2
import random
import cookielib
def getPicHtml(html):
reg = r'href="(http://www.douban.com/photos/photo.+\/)"'
imgre = re.compile(reg)
imglist = re.findall(imgre,html)
for imgurl in imglist:
print "Now downloadPage is %r" % imgurl
newHtml = getHtml(imgurl)
getImg(newHtml)
def getHtml(url):
user_agents = [
'Mozilla/5.0 (Windows; U; Windows NT 5.1; it; rv:1.8.1.11) Gecko/20071127 Firefox/2.0.0.11',
'Opera/9.25 (Windows NT 5.1; U; en)',
'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; .NET CLR 1.1.4322; .NET CLR 2.0.50727)',
'Mozilla/5.0 (compatible; Konqueror/3.5; Linux) KHTML/3.5.5 (like Gecko) (Kubuntu)',
'Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.8.0.12) Gecko/20070731 Ubuntu/dapper-security Firefox/1.5.0.12',
'Lynx/2.8.5rel.1 libwww-FM/2.14 SSL-MM/1.4.1 GNUTLS/1.2.9',
"Mozilla/5.0 (X11; Linux i686) AppleWebKit/535.7 (KHTML, like Gecko) Ubuntu/11.04 Chromium/16.0.912.77 Chrome/16.0.912.77 Safari/535.7",
"Mozilla/5.0 (X11; Ubuntu; Linux i686; rv:10.0) Gecko/20100101 Firefox/10.0 ",
]
agent = random.choice(user_agents)
req_header = {'User-Agent':agent}
mycookie = urllib2.HTTPCookieProcessor(cookielib.CookieJar())
openner = urllib2.build_opener(mycookie)
request = urllib2.Request(url,None,req_header)
response = urllib2.urlopen(request)
html = response.read()
return html
def getImg(html):
reg = r'src="(.+photo\/photo\/public.+\.jpg)"'
imgre = re.compile(reg)
imglist = re.findall(imgre,html)
for imgurl in imglist:
reg_large = r'<a href="http://www.douban.com.+large'
largere = re.compile(reg_large)
largelist = re.findall(largere,html)
if len(largelist)>0:
strinfo = re.compile('photo/photo')
imgurl = strinfo.sub('photo/large',imgurl)
print "picture url is %s" % imgurl
x = time.strftime('%Y%m%d%H%M%S',time.localtime(time.time()))+str(datetime.datetime.now().microsecond)
local = 'E://myimage//'
urllib.urlretrieve(imgurl,local+'%s.jpg' % x)
# in order to avid being 403
# hava another try latter
time.sleep(random.randint(0, 5))
def getIndex(html):
reg_index = r'<span class="count">\((.+)\)</span>'
indexre = re.compile(reg_index)
indexlist = re.findall(indexre,html)
indexnum = indexlist[0]
num = filter(str.isdigit,indexnum)
return num
albumId = raw_input('please enter the albumId: ')
albumUrl = "http://www.douban.com/photos/album/"+albumId
print "Now we start at %r" % albumUrl
html = getHtml(albumUrl)
getPicHtml(html);
#one page include 18 pic max
total = int(getIndex(html))
index = total/18
for x in range(1,index+1):
index = str(x * 18)
albumUrl = "http://www.douban.com/photos/album/"+albumId+"/?start="+index
print "Now we goon to the next page"
print "Now we come to %r" % albumUrl
html = getHtml(albumUrl)
getPicHtml(html);
print "%d pictures done,enjoy yourslef." % total
|
import sys
n = int(sys.stdin.readline())
for i in range(n):
a, b = list(sys.stdin.readline().strip())
a = ord(a) - ord('a')
b = int(b) - 1
t = 0
if 0<=a+2<=7 and 0<=b+1<=7:
t+=1
if 0<=a+2<=7 and 0<=b-1<=7:
t+=1
if 0<=a-2<=7 and 0<=b+1<=7:
t+=1
if 0<=a-2<=7 and 0<=b-1<=7:
t+=1
if 0<=a+1<=7 and 0<=b+2<=7:
t+=1
if 0<=a+1<=7 and 0<=b-2<=7:
t+=1
if 0<=a-1<=7 and 0<=b+2<=7:
t+=1
if 0<=a-1<=7 and 0<=b-2<=7:
t+=1
print t
|
from rest_framework import mixins
from rest_framework import viewsets
class CreateListRetrieveViewset(
mixins.ListModelMixin,
mixins.CreateModelMixin,
mixins.RetrieveModelMixin,
viewsets.GenericViewSet,
):
pass
class CreateViewset(
mixins.CreateModelMixin, viewsets.GenericViewSet,
):
pass
class ListRetrieveViewset(
mixins.ListModelMixin, mixins.RetrieveModelMixin, viewsets.GenericViewSet,
):
pass
class RetrieveViewset(
mixins.RetrieveModelMixin, viewsets.GenericViewSet,
):
pass
class ListViewset(
mixins.ListModelMixin, viewsets.GenericViewSet,
):
pass
class UpdateViewset(
mixins.UpdateModelMixin, viewsets.GenericViewSet,
):
pass
class CreateListRetrieveUpdateViewset(
mixins.ListModelMixin,
mixins.CreateModelMixin,
mixins.RetrieveModelMixin,
mixins.UpdateModelMixin,
viewsets.GenericViewSet,
):
pass
|
#!/usr/bin/env python
"""
The n^(th) term of the sequence of triangle numbers is given by,
t_(n) = 1/2n(n+1); so the first ten triangle numbers are:
1, 3, 6, 10, 15, 21, 28, 36, 45, 55, ...
By converting each letter in a word to a number corresponding to its
alphabetical position and adding these values we form a word value.
For example, the word value for SKY is 19 + 11 + 25 = 55 = t_(10). If the
word value is a triangle number then we shall call the word a triangle word.
Using euler42.txt, a 16K text file containing nearly two-thousand common
English words, how many are triangle words?
"""
def wordsum(word):
return sum([ord(c) - ord('A') + 1 for c in word])
def trinum(n):
if n & 1: return ((n / 2) + 1) * n
else: return (n / 2) * (n + 1)
trinums = [trinum(n) for n in range(100)]
with open("../data/euler42.txt") as f:
wordsums = [wordsum(n.strip('"')) for n in f.read().split(",")]
print sum([i in trinums for i in wordsums]), "words are triangle words."
|
# -*- coding: utf-8 -*-
import numpy as np
"""Function used to compute the loss."""
def compute_loss_mse(y, tx, w):
"""MAE"""
e = y - tx.dot(w)
return (np.linalg.norm(e) ** 2) / len(y)
def compute_loss_mae(y, tx, w):
"""MSE"""
e = y - tx.dot(w)
mae = 0.5 * (np.linalg.norm(e, 1)) / len(y)
return mae
|
API_HOSTS = {
"test": "http://192.168.1.100:11002/wp-json/wc/v3/",
"dev": "",
"prod": ""
}
DB_HOST = {
} |
import sys #sys is built in library(the bread and butter)
try: #underneath the block try block, you "try" a piece of code that you think might give you an error
#In my case, I didn't install request when running
import requests
except ImportError:
#Write specific error
#We are looking for an ImportError. If there is an import error, we want to stop the script
sys.exit("requests was not properly installed. Try again. Are you sure you are in venv?")
#exit() exit our script if the block of code underneath except is ran
#Stops script dead, much like an error and sends messaged typed
def get_fantasy_points(player,pos):
#we write a little function to get a player fantasy points from JSON object
#Our JSON is a list of dictionaries with dictionaries nested within
if player.get("position")==pos:
#check if our player has the correct position with the if block
#pos is our new variable to be used instead of position
return player.get("fantasy_points").get("ppr")
#If they do, we chain two get methods to get back our desired result.
#get. is pretty straightforward
pos="WR"
year="2019"
week= 1
res=requests.get('https://www.fantasyfootballdatapros.com/api/players/{0}/{1}'.format(year, week))
#We build our API endpoint using the built in method format
#The endpoint requires a season number and and week number which we set abouve
if res.ok:
#Status code 200, true or ok(500 or 404 denied)
#Pass URL into our request.get method
#Requests module has a function called get which allows us to make an HTTP GET request
#Remember, a GET request is what you do everyday when you request a resource form a webpage
#Instead here, we are requesting a JSON object that we can use in our code
print("Season {0}, week{1} VOR for {2}s".format(year, week, pos))
print('-'*40)
#Season{0} reference back to api url
#We print out to the terminal some info about our script
#numbers are matched to format() order
#Strings can be multiplied just like integers
#'-'*40 means give us '-' 40 times, please make sense later.
data = res.json()
#.json() to convert our response to JSON so we can use it in code
wr_fantasy_points=[get_fantasy_points(player,pos) for player in data]
#We use our little helper function to extract fantasy_points for each of our player objects
#fantasy_points is how it looks on api
#newly created json object is just a python list now
wr_fantasy_points=list(filter(lambda x: x is not None, wr_fantasy_points))
#filter out any values which have the value of None
mean = lambda x: sum(x)/len(x)
#we write a lambda and save it as a variable in order to calculate average of a list
#when in doubt, always assume you can something to a variable
#We can reference this function by using mean()
replacement_value=mean(wr_fantasy_points)
for player in data:
if player.get("position")==pos:
vor=player.get("fantasy_points").get("ppr")-replacement_value
print(
player.get("player_name"), "had a VOR of", vor
)
|
#!/usr/bin/python
# The MIT License (MIT)
#
# Copyright (c) 2017 Massimiliano Patacchiola
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
#ATTENTION: to work it requires to lunch the iCub world:
# yarpserver
# ./iCub_SIM
# ./iKinGazeCtrl --from configSim.ini
# yarpdev --device opencv_grabber
# yarp connect /grabber /icubSim/texture/screen
#
# For the cartesian controller of the left arm
# ./simCartesianControl
# ./iKinCartesianSolver --context simCartesianControl --part left_arm
# PocketSphinx valid Commands are:
# The prefix [iCub] or [hey] is optional
# learn <object name>
# this is a <object name>
# forget <object name>
# what is this
# find the <object name>
# stop detection
# look at me
from speech_recognition import SpeechRecognizer
from icub import iCub
import cv2
import random
import time
import os
import sys
def initialise():
# Initialise the speech recognition engine and the iCub controller
my_speech = SpeechRecognizer(
hmm_path="/home/massimiliano/pyERA/examples/ex_icub_trust_cognitive_architecture/sphinx/model/en-us/en-us",
language_model_path="/home/massimiliano/pyERA/examples/ex_icub_trust_cognitive_architecture/sphinx/model/en-us/en-us.lm.bin",
dictionary_path="/home/massimiliano/pyERA/examples/ex_icub_trust_cognitive_architecture/sphinx/data/icub.dic",
grammar_path="/home/massimiliano/pyERA/examples/ex_icub_trust_cognitive_architecture/sphinx/data/icub.gram",
rule_name='icub.basicCmd',
fsg_name="icub")
# iCub initialization
my_icub = iCub(icub_root='/icubSim')
# Load acapela configuration from file
my_icub.set_acapela_credential("./acapela_config.csv")
account_login, application_login, application_password, service_url = my_icub.get_acapela_credential()
print("[ACAPELA]Acapela configuration parameters:")
print("Account Login: " + str(account_login))
print("Application Login: " + str(application_login))
print("Account Password: " + str(application_password))
print("Service URL: " + str(service_url))
print("")
# Return the objects
return my_speech, my_icub
def speech_to_action(speech_string):
""" Take the sentence from the speech recognition and plan an action
<action> = (learn new object | watch | inspect | find | search | look | what | start | stop);
<target> = (ball | cup | book | dog | chair | table | at me | is this | movement detection);
@param speech_string:
@return:
"""
if speech_string.find('learn') > -1 or speech_string.find('this is a') > -1:
response_list = ['I like to learn! This is a ',
'Ok, this is a ',
'I learned a new object, ',
'']
object_name = speech_string.rsplit(None, 1)[-1]
response_string = response_list[random.randint(0, len(response_list)-1)] + object_name
state = 'learn'
elif speech_string.find('what is this') > -1:
response_string = ""
state = 'what'
elif speech_string.find('find the') > -1 or speech_string.find('search the') > -1:
object_name = speech_string.rsplit(None, 1)[-1]
object_path = "./objects/" + str(object_name) + ".png"
if not os.path.isfile(object_path):
print("[SPEECH-TO-ACTION][WARNING] " + "this file does not exist: " + str(object_path) + "\n")
response_string = "Sorry I do not know this object!"
state = 'key'
else:
response_list = ["Ok, now I'm looking for a ",
'Ok I will track the ',
'Ready to track the ']
response_string = response_list[random.randint(0, len(response_list)-1)] + object_name
state = 'movedetect on'
elif speech_string.find('stop detection') > -1:
response_list = ["Ok, no more movements",
'Ok I will stop it',
"I'm gonna stop it!"]
response_string = response_list[random.randint(0, len(response_list)-1)]
state = 'movedetect off'
elif speech_string.find('look at me') > -1:
response_list = ["Ok!",
'Sure!']
response_string = response_list[random.randint(0, len(response_list)-1)]
state = 'look'
else:
response_list = ["Sorry I did not understand.",
'Sorry, can you repeat?',
'Repeat again please.']
response_string = response_list[random.randint(0,len(response_list)-1)]
state = 'key'
return response_string, state
def main():
inputfile = ''
outputfile = ''
informant_name = ''
if len(sys.argv) == 1 or len(sys.argv) > 4:
print("python familiarization.py <inputfile> <outputfilename> <informant_name>")
elif len(sys.argv) == 4:
inputfile = sys.argv[1]
outputfile = sys.argv[2]
informant_name = sys.argv[3]
print("Input file: " + str(inputfile))
print("Output file: " + str(outputfile))
print("Informant Name: " + str(informant_name))
STATE = 'show'
speech_string = ""
fovea_offset = 40 # side of the fovea square
my_speech, my_icub = initialise()
is_connected = my_icub.check_connection()
if is_connected:
print("[STATE Init] intenet connection present.")
else:
print("[STATE Init][ERROR] internet connection not present!!!")
my_icub.say_something(text="I'm ready!")
cv2.namedWindow('main')
while True:
if STATE == 'record':
#image = my_icub.return_left_camera_image(mode='BGR')
my_speech.record_audio("/tmp/audio.wav", seconds=3, extension='wav', harddev='3,0')
raw_file_path = my_speech.convert_to_raw(file_name="/tmp/audio.wav", file_name_raw="/tmp/audio.raw", extension='wav')
speech_string = my_speech.return_text_from_audio("/tmp/audio.raw")
print("[STATE " + str(STATE) + "] " + "Speech recognised: " + speech_string)
STATE = 'understand'
elif STATE == 'understand':
response_string, local_state = speech_to_action(speech_string)
print("[STATE " + str(STATE) + "] " + "Speech recognised: " + speech_string)
print("[STATE " + str(STATE) + "] " + "Next state: " + local_state)
my_icub.say_something(text=response_string)
STATE = local_state
elif STATE == 'show':
left_image = my_icub.return_left_camera_image(mode='BGR')
img_cx = int(left_image.shape[1] / 2)
img_cy = int(left_image.shape[0] / 2)
cv2.rectangle(left_image,
(img_cx-fovea_offset, img_cy-fovea_offset),
(img_cx+fovea_offset, img_cy+fovea_offset),
(0, 255, 0), 1)
cv2.imshow('main', left_image)
STATE = 'key'
elif STATE == 'movedetect on':
object_name = response_string.rsplit(None, 1)[-1]
print("[STATE " + str(STATE) + "] " + "start tracking of: " + str(object_name) + "\n")
object_path = "./objects/" + str(object_name) + ".png"
if my_icub.is_movement_detection():
my_icub.stop_movement_detection()
time.sleep(0.5)
my_icub.start_movement_detection(template_path=object_path, delay=1.0)
else:
my_icub.start_movement_detection(template_path=object_path, delay=1.0)
STATE = 'key'
elif STATE == 'movedetect off':
print("[STATE " + str(STATE) + "] " + "stop movement tracking" + "\n")
my_icub.stop_movement_detection()
time.sleep(0.5)
my_icub.reset_head_pose()
STATE = 'key'
elif STATE == 'look':
print("[STATE " + str(STATE) + "] " + "gaze reset" + "\n")
my_icub.reset_head_pose()
STATE = 'key'
elif STATE == 'learn':
object_name = response_string.rsplit(None, 1)[-1]
print("[STATE " + str(STATE) + "] " + "Learning new object: " + object_name + "\n")
left_image = my_icub.return_left_camera_image(mode='BGR')
#left_image = image
img_cx = int(left_image.shape[1] / 2)
img_cy = int(left_image.shape[0] / 2)
left_image = left_image[img_cy-fovea_offset:img_cy+fovea_offset,
img_cx-fovea_offset:img_cx+fovea_offset]
my_icub.learn_object_from_histogram(left_image, object_name)
print("[STATE " + str(STATE) + "] " + "Writing new template in ./objects/" + object_name + ".png" + "\n")
cv2.imwrite('./objects/' + str(object_name) + '.png', left_image)
STATE = 'key'
elif STATE == 'what':
print("[STATE " + str(STATE) + "] " + "Recalling object from memory..." + "\n")
left_image = my_icub.return_left_camera_image(mode='BGR')
#left_image = image
img_cx = int(left_image.shape[1] / 2)
img_cy = int(left_image.shape[0] / 2)
left_image = left_image[img_cy-25:img_cy+25, img_cx-25:img_cx+25]
object_name = my_icub.recall_object_from_histogram(left_image)
if object_name is None:
my_icub.say_something("My memory is empty. Teach me something!")
else:
print("[STATE " + str(STATE) + "] " + "Name returned: " + str(object_name) + "\n")
response_list = ["Let me see. I think this is a ",
"Let me think. It's a ",
"Just a second. It may be a ",
"It should be a "]
response_string = response_list[random.randint(0, len(response_list) - 1)]
my_icub.say_something(response_string + str(object_name))
STATE = 'key'
elif STATE == 'key':
key_pressed = cv2.waitKey(10) # delay in millisecond
if key_pressed==113: #q=QUIT
print("[STATE " + str(STATE) + "] " + "Button (q)uit pressed..." + "\n")
STATE = "close"
elif key_pressed==110: #n=
print("[STATE " + str(STATE) + "] " + "Button (n) pressed..." + "\n")
elif key_pressed==102: #f=
print("[STATE " + str(STATE) + "] " + "Button (f) pressed..." + "\n")
elif key_pressed == 114: # r=RECORD
print("[STATE " + str(STATE) + "] " + "Button (r)ecord pressed..." + "\n")
STATE = "record"
else:
STATE = 'show'
elif STATE == 'close':
my_icub.say_something(text="See you soon, bye bye!")
my_icub.stop_movement_detection()
my_icub.close()
cv2.destroyAllWindows()
break
if __name__ == "__main__":
main()
|
from django.shortcuts import render, redirect
from django.http import Http404
from django.contrib import messages
from django.core.mail import send_mail
from Modelos.models import (
empresas,
activi_comerciales,
productos,
servicios,
usuarios,
)
from Global.usuario import Usuario
from Cliente.carrito import Carrito
# Vista para ver el html de error, si una página no existe
def error_404_view(request, exception):
return render(request, "error/404.html", {"error": "La página no exite"})
def error_view(request):
return render(request, "error/404.html", {"error": "La página no exite"})
# Vista que retorna el html de inicio de sesión
def vwInicio(request):
user_session = Usuario(request)
try:
if request.session["usuario"]["rol_id"] == 2:
return redirect("controlNegocio")
elif request.session["usuario"]["rol_id"] == 3:
return redirect("admin-web")
except:
pass
list_categorias = activi_comerciales.objects.filter(visible=True).order_by("nombre")
return render(request, "index.html", {"categorias": list_categorias})
# Vista que retorna el html de login
def vwTplLogin(request):
user_session = Usuario(request)
try:
if request.session["usuario"]["rol_id"] == 1:
return redirect("index")
elif request.session["usuario"]["rol_id"] == 2:
return redirect("controlNegocio")
elif request.session["usuario"]["rol_id"] == 3:
return redirect("admin-web")
except:
pass
return render(request, "autenticacion/login.html")
# Vista que me permita logear, guardando los datos del cliente en una variable session
def vwLogin(request):
user_session = Usuario(request)
try:
if request.session["usuario"]["rol_id"] == 1:
return redirect("index")
elif request.session["usuario"]["rol_id"] == 2:
return redirect("controlNegocio")
elif request.session["usuario"]["rol_id"] == 3:
return redirect("admin-web")
except:
pass
try:
usuario = usuarios.objects.get(correo=request.POST["txtUsuario"])
# Identifica si el usuario se encuentra habilitado, para iniciar sessión
if not usuario.estado:
messages.error(request, "La cuenta que estás intentando ingresar no es valida")
return redirect("index")
if usuario.credenciales == request.POST["txtCredenciales"]:
# Guardar el usuario y carrito en una variable session
user_session.add(usuario)
cart_session = Carrito(request)
return redirect("index")
else:
messages.error(request, "La contraseña es incorrecta " + usuario.nom_usuario)
return redirect("login")
except:
messages.error(request, "La cuenta que estás ingresando no se encuentra registrada")
return redirect("login")
# Vista que permite cerrar sessión, eliminando la variable session del usuario y guardando los datos del carrito en la base de datos
def vwLogout(request):
# Cerrar sessión para cualquier usuario
try:
if not request.session["usuario"]:
messages.info(request, "Debes iniciar sessión")
return redirect("login")
except:
pass
user_session = Usuario(request)
if request.session["usuario"]["rol_id"] == 1:
cart_session = Carrito(request)
# Eliminar los valores de carrito y usuario session
cart_session.clear()
user_session.clear()
return redirect("index")
# Vista que retorna el html para registrar un cliente
def vwTplRegistrar(request):
user_session = Usuario(request)
try:
if request.session["usuario"]["rol_id"] == 1:
return redirect("index")
elif request.session["usuario"]["rol_id"] == 2:
return redirect("controlNegocio")
elif request.session["usuario"]["rol_id"] == 3:
return redirect("admin-web")
except:
pass
return redirect("solicitar-cuenta")
# Vista que retorna el html más la lista de empresas segun su id
def vwTplListaNegocios(request, negocio_id):
user_session = Usuario(request)
try:
if request.session["usuario"]["rol_id"] == 2:
return redirect("controlNegocio")
elif request.session["usuario"]["rol_id"] == 3:
return redirect("admin-web")
except:
pass
list_negocios = empresas.objects.filter(activi_comercial_id=negocio_id, estado="Habilitada")
return render(request, "empresa/tplListaNegocios.html", {"empresas": list_negocios})
# Vista que carga la información del negocio según su id
def vwTplInfoNegocio(request, empresa_id):
user_session = Usuario(request)
try:
if request.session["usuario"]["rol_id"] == 2:
return redirect("controlNegocio")
except:
pass
list_negocios = empresas.objects.get(pk=empresa_id, estado="Habilitada")
return render(request, "empresa/tplInfoNegocio.html", {"empresa": list_negocios})
# Vista que carga los productos y servicos de la empresa según su id
def vwTplPrSrNegocio(request, empresa_id):
user_session = Usuario(request)
try:
if request.session["usuario"]["rol_id"] == 2:
return redirect("controlNegocio")
elif request.session["usuario"]["rol_id"] == 3:
return redirect("admin-web")
except:
pass
em_fotos_servicio = servicios.objects.filter(empresa_id=empresa_id, visible=True, eliminado=False)
em_fotos_producto = productos.objects.filter(empresa_id=empresa_id, visible=True, eliminado=False)
empresa = empresas.objects.get(pk=empresa_id, estado="Habilitada")
return render(request, "empresa/tplPrSrNegocio.html", {"empresa": empresa, "em_fotos_servicio": em_fotos_servicio, "em_fotos_producto": em_fotos_producto})
|
from pathlib import Path
from django.urls import path
from . import views
from .models import Record
activity_short = Path(__file__).parts[-2]
app_name = activity_short
urlpatterns = [
path('', views.FilterRecord.as_view(), name='index'),
path('record/', views.GetRecord.as_view(), name='grecord'),
path('frecords/', views.FilterRecord.as_view(), name='frecords'),
path('frecords/thanks', views.FilterRecord.as_view(thanks= True), name='thanks'),
path('export/', views.Export.as_view(), name='export'),
]
|
"""
delete.py
"""
import requests
from .exceptions import AgaveFilesError
from ..utils import handle_bad_response_status_code
def files_delete(tenant_url, access_token, file_path):
""" Remove a file or direcotry from a remote system
"""
# Set request url.
endpoint = "{0}/{1}/{2}".format(tenant_url, "files/v2/media/system",
file_path)
# Make request.
try:
headers = {"Authorization": "Bearer {0}".format(access_token)}
params = {"pretty": "true"}
resp = requests.delete(endpoint, headers=headers, params=params)
except Exception as err:
raise AgaveFilesError(err)
# Handle bad status code.
handle_bad_response_status_code(resp)
|
def numPaths(y, x):
if y==0 and x==0:
return 1
if y<0 or x<0:
return 0
right = numPaths(y, x-1)
down = numPaths(y-1, x)
return right+down
def test1():
y = 2
x = 3
res = numPaths(y, x)
print("res: ", res)
test1() |
from tqdm import tqdm
import numpy as np
import os ; os.environ['HDF5_DISABLE_VERSION_CHECK']='2'
import tensorflow as tf
import tensorflow_datasets as tfds
# from codecs import open
ds, info = tfds.load('imdb_reviews/subwords8k',
with_info=True,
as_supervised=True)
train_examples, test_examples = ds['train'], ds['test']
encoder = info.features['text'].encoder
UFFER_SIZE = 10000
BATCH_SIZE = 128
train_dataset = (train_examples
.shuffle(10000)
.padded_batch(BATCH_SIZE, padded_shapes=([None], [])))
test_dataset = (test_examples
.padded_batch(BATCH_SIZE, padded_shapes=([None], [])))
GLOVE_DIR = 'glove6b/'
GLOVE_EMBEDDING_DIM = 100
unk_word_embedding = np.zeros(GLOVE_EMBEDDING_DIM)
embeddings_index = {}
with open(GLOVE_DIR + f'glove.6B.{GLOVE_EMBEDDING_DIM}d.txt', encoding='utf-8', errors='ignore') as glove_file:
for i, line in tqdm(enumerate(glove_file)):
word, *word_embedding = line.split()
word_embedding = np.array(word_embedding, dtype='float32')
embeddings_index[word] = word_embedding
unk_word_embedding += word_embedding
unk_word_embedding = unk_word_embedding / i
embedding_matrix = np.zeros((encoder.vocab_size, GLOVE_EMBEDDING_DIM))
for i, word in enumerate(encoder._subwords):
embedding_vector = embeddings_index.get(word.rstrip('_'), unk_word_embedding)
embedding_matrix[i] = embedding_vector
model = tf.keras.Sequential([
tf.keras.layers.Embedding(encoder.vocab_size, GLOVE_EMBEDDING_DIM),
tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(64)),
tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32)),
tf.keras.layers.Dense(32, activation='relu'),
tf.keras.layers.Dense(1)
])
model.layers[0].set_weights([embedding_matrix])
model.layers[0].trainable = False
model.compile(loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),
optimizer="adam",
metrics=['accuracy'])
model.summary()
fit_data = model.fit(train_dataset, epochs=5,
validation_data=test_dataset,
validation_steps=30)
print('Test accuracy: {:.4f}'.format(test_data[1]))
# Plot training & validation accuracy values
plt.plot(fit_data.history['accuracy'])
plt.plot(fit_data.history['val_accuracy'])
plt.title('Model accuracy')
plt.ylabel('Accuracy')
plt.xlabel('Epoch')
plt.legend(['Train', 'Test'], loc='upper left')
plt.show()
# Plot training & validation loss values
plt.plot(fit_data.history['loss'])
plt.plot(fit_data.history['val_loss'])
plt.title('Model loss')
plt.ylabel('Loss')
plt.xlabel('Epoch')
plt.legend(['Train', 'Test'], loc='upper left')
plt.show()
|
import random
a = [4,5,2]
#값에 access
a[0]
a[1]
a[2]
# 리스트에 랜덤한 value 5 insert append
'''
Data Structure
자료구조 지만 많이 사용되기 때문에 basic part에서 설명함.
선형구조
-initialiaztion
-init
a = []
a = [1, 2, 3, 4]
-Data add
append 함수를 사용
for i in range(1,101):
a.append(i)
-check length
len(a)
-delete
del a[2]
-insert
a.insert(index, number)
-slicing
a[:3]
a[:-1]
Q. 리스트 중 최대값과 최소값을 구하가
#리스트 내포
a = [k * k for k in range(10)]
#튜플
a = (1,2,3)
한번 값을 할당 하면 바꿀수 없다. list 와 비슷하지만 메모리 측면에서 더 효율적으로 사용할 수도 있다.
'''
|
#!/usr/bin/env python3
"""
Takes input a relatedness file, a fam file, and a list of individuals and extracts the sub-matrix from the relatedness file
for the given individuals
Jean-Tristan Brandenburg
"""
import sys
import pandas as pd
import numpy as np
import argparse
EOL=chr(10)
def errorMessage10(phe):
print("""
A problem has been detected in file <%s> column <%s>.
There is some invalid data. I regret I can't tell you which row.
Please check -- the data should be numeric only.
If there is missing data, please use NA
"""%(sys.argv[1],phe))
def parseArguments():
parser = argparse.ArgumentParser(description='fill in missing bim values')
parser.add_argument('--rel',type=str,required=True,help="File of relatdness matrix as gemma output")
parser.add_argument('--phenofile',type=str,required=True,help="fam file use for compute relatdness matrix")
parser.add_argument('--covfile',type=str,required=True,help="fam file use for compute relatdness matrix")
parser.add_argument('--pospheno',type=int,required=True,help="fam file use for compute relatdness matrix")
parser.add_argument('--relout',type=str,required=True,help="File with output pheno")
parser.add_argument('--phenofileout',type=str,required=True,help="File with output pheno")
parser.add_argument('--covfileout',type=str,required=True,help="File with output pheno")
args = parser.parse_args()
return args
args=parseArguments()
pospheno=args.pospheno
readpheno=open(args.phenofile)
NewHeader="FID IID\t"+readpheno.readline().split()[pospheno+1]
listeFIDKeep=[]
DicPheno={}
for Lines in readpheno :
SplL=Lines.split()
if SplL[1+pospheno]!='-9' and SplL[1+pospheno].upper()!="NA" :
listeFIDKeep.append(SplL[0]+" "+SplL[1])
DicPheno[SplL[0]+" "+SplL[1]]=SplL[0]+" "+SplL[1]+"\t"+SplL[1+pospheno]
readmat=open(args.rel)
linemat=readmat.readline()
listeFID=linemat.split('\t')
print(listeFID[1:5])
readmat.close()
ListePosKept=[0]
CmtFID=0
FinalIdList=[]
for FID in listeFID :
if FID in listeFIDKeep :
ListePosKept.append(CmtFID)
FinalIdList.append(FID)
CmtFID+=1
readmat=open(args.rel)
writemat=open(args.relout, 'w')
CmtL=0
print('begin : open and write maatrix pheno in file '+args.relout)
for Line in readmat :
Line=Line.replace('\n','')
if CmtL in ListePosKept :
Chaine=[]
SplLine=Line.split('\t')
for Pos in ListePosKept :
Chaine.append(SplLine[Pos])
writemat.write("\t".join(Chaine)+"\n")
CmtL+=1
readmat.close()
writemat.close()
print('end : open and write maatrix pheno in file '+args.relout)
print('begin : write pheno in file '+args.phenofileout)
WritePheno=open(args.phenofileout,'w')
WritePheno.write(NewHeader+'\n')
for FID in FinalIdList :
WritePheno.write(DicPheno[FID]+'\n')
WritePheno.close()
print('end : write pheno in file '+args.phenofileout)
readcov=open(args.covfile)
NewHeader=readcov.readline().replace('\n','')
DicCov={}
print('begin : red cov from file '+args.covfile)
for Lines in readcov :
SplL=Lines.split()
DicCov[SplL[0]+" "+SplL[1]]=Lines.replace('\n','')
readcov.close()
print('emd : red cov from file '+args.covfile)
print('begin : write cov '+args.covfileout)
writecov=open(args.covfileout, 'w')
writecov.write(NewHeader+'\n')
for FID in FinalIdList :
writecov.write(DicCov[FID]+'\n')
writecov.close()
print('end : write cov')
|
# -*- coding: utf-8 -*-
import h5py
import numpy as np
from sklearn.utils import shuffle
from keras.models import *
from keras.layers import *
import pandas as pd
from keras.preprocessing.image import *
# bottleneck产生测试特征
np.random.seed(2017)
X_train = []
X_test = []
y_pred = []
for filename in ["gap_InceptionV3.h5", "gap_Xception.h5", "gap_InceptionResNetV2.h5"]:
with h5py.File(filename, 'r') as h:
X_train.append(np.array(h['train']))
X_test.append(np.array(h['test']))
y_train = np.array(h['label'])
X_train = np.concatenate(X_train, axis=1)
X_test = np.concatenate(X_test, axis=1)
# 获取保存的模型
model = load_model('model_concat_cvd.h5')
y_pred = model.predict(X_test, verbose=1)
y_pred = y_pred.clip(min=0.005, max=0.995)
# 产生submission
df = pd.read_csv("sample_submission.csv")
gen = ImageDataGenerator()
test_generator = gen.flow_from_directory("/home/autel/Dataset/Cat_vs_Dog/test2", (224, 224), shuffle=False,
batch_size=16, class_mode=None)
for i, fname in enumerate(test_generator.filenames):
index = int(fname[fname.rfind('/')+1:fname.rfind('.')])
df.set_value(index-1, 'label', y_pred[i])
df.to_csv('model_concat_pred.csv', index=None)
df.head(10) |
list=["a","e","i","o","u","A","E","I","O","U"]
a=str(input("enter the value:"))
if (a in list):
print ("vowel")
else:
print ("consonant")
|
import pygame
class Settings():
'''Класс для хранения всех настроек классификатора рукописных чисел'''
def __init__(self):
'''Инициализирует настройки классификатора'''
#Параметры экрана
self.screen_width = 415
self.screen_height = 250
self.bg_color = (100, 150, 255)
#Параметры доски для рисования
self.blackboard_width = 250
self.blackboard_height = 250
self.blackboard_color = (0, 0, 0)
#Параметры мелка(карандаша)
self.crayon_color = (255, 255, 255)
self.crayon_width = 4
#Параметры надписей(цвет, шрифт)
self.title_color = (30, 30, 30)
self.title_font = pygame.font.SysFont(None, 25)
#Параметры цифр(цвет, шрифт)
self.number_color = (30, 30, 30)
self.number_font = pygame.font.SysFont(None, 35) |
"""
TIME LIMIT PER TEST: 3 seconds
MEMORY LIMIT PER TEST: 256 megabytes
INPUT: standard input
OUTPUT: standard output
"Contestant who earns a score equal to or greater than the k-th place finisher's score will advance to the next
round, as long as the contestant earns a positive score..." — an excerpt from contest rules.
A total of n participants took part in the contest (n ≥ k), and you already know their scores.
Calculate how many participants will advance to the next round.
INPUT
The first line of the input contains two integers n and k (1 ≤ k ≤ n ≤ 50) separated by a single space.
The second line contains n space-separated integers a1, a2, ..., an (0 ≤ ai ≤ 100), where ai is the score
earned by the participant who got the i-th place. The given sequence is non-increasing (that is, for all i
from 1 to n - 1 the following condition is fulfilled: ai ≥ ai + 1).
OUTPUT
Output the number of participants who advance to the next round.
"""
n, k = [int(a) for a in input().split()]
scores = [int(a) for a in input().split()]
accum = 0
for score in scores[:n]:
if score >= scores[k-1] and score > 0:
accum += 1
print(accum) |
import os
def clear(): return os.system('cls')
should_continue = True
def cipherUnrestricted(message, direction, caesarNumber):
cipheredMessage = ""
if direction == 'e':
for letter in message:
if letter.isalpha():
cipheredMessage += chr((ord(letter) -
97 + caesarNumber) % 26 + 97)
else:
characterNumber = ord(letter) - 48
if characterNumber < 0 or characterNumber > 9:
cipheredMessage += letter
else:
cipheredMessage += chr((characterNumber +
caesarNumber) % 10 + 48)
return cipheredMessage
elif direction == 'd':
for letter in message:
if letter.isalpha():
cipheredMessage += chr((ord(letter) -
97 - caesarNumber) % 26 + 97)
else:
characterNumber = ord(letter) - 48
if characterNumber < 0 or characterNumber > 9:
cipheredMessage += letter
else:
cipheredMessage += chr((characterNumber -
caesarNumber) % 10 + 48)
return cipheredMessage
while should_continue:
direction = input("Type 'e' for encryption or 'd' for decryption: ")
if direction != 'e' and direction != 'd':
print("Error: Invalid direction")
continue
clear()
mode = "Encryption mode" if direction == 'e' else "Decryption mode"
print(mode)
message = input("Enter the message: ")
caesarNumber = int(input("Enter the number of shifts: "))
print(cipherUnrestricted(message, direction, caesarNumber))
should_continue = input("Continue? (y/n): ") == 'y'
|
from random import *
from metodusok import *
from targy import *
targyak = Targy("teritve", "troli")
print(targyak)
also = bekerszam("Alsóhatár?: ",1,7)
felso = bekerszam("Felsőhatár?: ",5,10)
darab = bekerszam("Darab?: ",1,5)
szamok = []
for i in range(darab):
#veletlenszam = randint(also,felso)
szamok.append(veletlenszam(also,felso))
kiir(szamok)
|
aa8=int(input())
b6=[int(x) for x in input().split()]
zzz=0
for x in range(aa8):
for y in range(x):
if b6[y]<b6[x]:
yyy+=b6[j]
print(zzz)
|
# Created by Brian Mascitello to calculate a specific polynomial's root.
def mathproblem(x0):
""" function mathproblem(x0) finds a root of the nonlinear
function specified by f and fprime. y = 2 ** x - 3 ** (x / 2) - 1;
yprime = 0.693147 * (2 ** x) - (1.098612 * 3 ** (x / 2)) / 2; Result
x is the root. """
epsilon = 2.2204*10**-16
""" governs precision of convergence
where 2.2204*10**-16 = machine epsilion in python """
x = x0
xprevious = 0
k = 0
while abs(float(2 ** x - 3 ** (x / 2) - 1)) > epsilon*abs(float(2 ** x0 - 3 ** (x0 / 2) - 1)) and k < 20:
k = k+1
xprevious = x
x = float(x) - (float(2 ** x - 3 ** (x / 2) - 1)/float(0.693147 * (2 ** x) - (1.098612 * 3 ** (x / 2)) / 2))
change = abs(float(x - xprevious))
residual = 2 ** x - 3 ** (x / 2) - 1
print("Iteration: %d, Root: %f, Change: %f, Residual: %f" % (k,x,change,residual))
print("Root at",x,"\n")
return float(x)
print("y = 2 ** x - 3 ** (x / 2) - 1")
print("yprime = 0.693147 * (2 ** x) - (1.098612 * 3 ** (x / 2)) / 2")
print("Machine epsilon set as: 2.2204*10^-16")
x0 = float(input("Please enter your guess of the root: "))
mathproblem(x0)
|
from flask import Flask
import bot_nmap as botmap
import json
app = Flask(__name__)
@app.route('/nmap/<ip>',methods=['GET'])
def nmap(ip):
return json.dumps(botmap.getPorts(ip))
app.run(host='0.0.0.0',use_reloader=False)
|
import imp, os.path, sys, time
from watchdog.observers import Observer
from watchdog.events import PatternMatchingEventHandler
import mockingbeat
class MyHandler(PatternMatchingEventHandler):
patterns = []
@staticmethod
def dispatch(event):
if event.src_path == ifn:
load()
ifn = ofn = None
def load():
stdout = sys.stdout
with file(ofn, 'w') as sys.stdout:
try:
reload(mockingbeat)
mod = imp.load_source(ifn.rsplit('/', 1)[-1].split('.', 1)[0], ifn, file(ifn, 'r'))
except:
import traceback
traceback.print_exc()
sys.stdout = stdout
def main(_ifn, _ofn):
global ifn, ofn
ifn = os.path.abspath(_ifn)
ofn = _ofn
MyHandler.patterns.append(ifn)
load()
observer = Observer()
observer.schedule(MyHandler, os.path.dirname(ifn), recursive=True)
observer.start()
try:
while True:
time.sleep(0.1)
except KeyboardInterrupt:
observer.stop()
observer.join()
if __name__=='__main__':
main(*sys.argv[1:])
|
# Необходимо набрать из каждый пары ровно одно число так, чтобы сумма всех выбранных числе не делилась на 31
# и при этом была максимально возможной.
f = open("27v01_B.txt", 'r')
f_len = int(f.readline())
a = []
for i in range(f_len):
j, k = map(int, f.readline().split())
a.append([max(j, k), min(j, k), abs(j-k)])
f.close()
print(a)
f_sum = sum([a[i][0] for i in range(len(a))])
print(f_sum)
if f_sum % 31 == 0:
i_min = 0
for i in range(len(a)):
if a[i][2] == max(a[i][2], a[i_min][2]):
i_min = i
for i in range(len(a)):
if a[i][2] == min(a[i][2], a[i_min][2]): # bool and bool in a [max, min, difference]
print(a[i])
if a[i][2] % 31 != 0:
i_min = i
f_sum = f_sum + a[i_min][1] - a[i_min][0]
print(i_min, a[i_min])
print(f_sum)
|
from .views import AccessViewSet
def register(router):
router.register(r'access', AccessViewSet, base_name='access')
|
import math
import numpy as np, cv2
width = 640
height = 480
referencePoints = np.float32(
[[width/4,height/4],
[3*width/4,height/4],
[3*width/4,3*height/4],
[width/4,3*height/4]])
currentPoint = -1
calibrating = True
fullScreen = False
names = ['0', 'A risada mais engraçada Pânico na TV.avi', 'Sabe de nada inocente[1].avi'];
window_titles = ['first', 'second', 'third']
inputimage1 = cv2.imread("pp.jpg")
cap = [cv2.VideoCapture(i) for i in names]
frames = [None] * len(names);
gray = [None] * len(names);
ret = [None] * len(names);
rows1, cols1 = inputimage1.shape[:2]
pts1 = np.float32([[0,0],[cols1,0],[cols1,rows1],[0,rows1]])
pts2 = np.float32([[0,0],[639,0],[639,479],[0,479]])
image = np.zeros((height, width, 3), np.uint8)
def pointColor(n):
if n == 0:
return (0,0,255)
elif n == 1:
return (0,255,255)
elif n == 2:
return (255,255,0)
else:
return (0,255,0)
def mouse(event, x, y, flags, param):
global currentPoint
if event == cv2.EVENT_LBUTTONDOWN:
cp = 0
for point in referencePoints:
dist = math.sqrt((x-point[0])*(x-point[0])+(y-point[1])*(y-point[1]))
if dist < 4:
currentPoint = cp
break
else:
cp = cp + 1
if event == cv2.EVENT_LBUTTONUP:
currentPoint = -1
if currentPoint != -1:
referencePoints[currentPoint] = [x,y]
cv2.namedWindow("test", cv2.WINDOW_NORMAL)
cv2.setMouseCallback("test", mouse)
while True:
image[:] = (0,0,0)
if calibrating:
color = 0
for point in referencePoints:
cv2.circle(image, (int(point[0]), int(point[1])),5,pointColor(color), -1)
color = color + 1
ret, frame = cap.read()
M = cv2.getPerspectiveTransform(pts1,referencePoints)
M2 = cv2.getPerspectiveTransform(pts2,referencePoints)
cv2.warpPerspective(frame, M2, (width,height), image, borderMode=cv2.BORDER_TRANSPARENT)
#cv2.warpPerspective(inputimage1, M, (width,height), image, borderMode=cv2.BORDER_TRANSPARENT)
cv2.imshow("test", image)
key = cv2.waitKey(1) & 0xFF
if key == ord("c"):
calibrating = not calibrating
if key == ord("f"):
if fullScreen == False:
cv2.setWindowProperty("test", cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
else:
cv2.setWindowProperty("test", cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_NORMAL)
fullScreen = not fullScreen
if key == ord("q"):
break
cv2.destroyAllWindows() |
# Dependencies
import requests
from splinter import Browser
from webdriver_manager.chrome import ChromeDriverManager
import pandas as pd
from flask_pymongo import PyMongo
from pymongo import MongoClient
from bs4 import BeautifulSoup as bs
def get_mars_table():
#Get Mars Facts
mars_facts_url = 'https://space-facts.com/mars/'
mars_data = pd.read_html(mars_facts_url)
#convert to html table
clean_table = mars_data[0].set_index([0])
clean_table.index.name="Description"
clean_table = clean_table.rename(columns={1: ""})
mars_data_table =clean_table.to_html()
mars_data_table
clean_table
return mars_data_table
def scrape():
mars_facts_url = 'https://space-facts.com/mars/'
response = requests.get(mars_facts_url)
# Create BeautifulSoup object; parse with 'html.parser'
soup = bs(response.text, 'html.parser')
#Scrape the NASA Mars News Site and collect the latest News Title and Paragraph Text. Assign the text to variables that you can reference later.
mars_news_scraped = soup.find('div', id = 'facts' )
headline = mars_news_scraped.find('strong').text
mars_list = mars_news_scraped.find_all('li')[0]
news_text = mars_list.next_sibling.text
#open browser
executable_path = {'executable_path': ChromeDriverManager().install()}
browser = Browser('chrome', **executable_path, headless=False)
#Get Featured Image
image_url = 'https://data-class-jpl-space.s3.amazonaws.com/JPL_Space/index.html'
browser.visit(image_url)
image_html = browser.html
image_soup = bs(image_html, 'html.parser')
featured_image = image_soup.find('div', class_ = 'floating_text_area')
featured_image_url = 'https://data-class-jpl-space.s3.amazonaws.com/JPL_Space/' + featured_image.a['href']
#Get Mars Facts
mars_data = pd.read_html(mars_facts_url)
#convert to html table
mars_data_table = mars_data[0].to_html()
mars_db_data = {
'headline' : headline,
'headline_text':news_text,
'featured_image_url' : featured_image_url
}
#Connect to PyMongo/MongoDB to store data
conn = "mongodb://localhost:27017"
client = MongoClient(conn)
db = client.mars_db
collection = db.mars_data
collection.delete_many({})
collection.update({},mars_db_data, upsert=True)
#Grab Hemisphere links
hemispheres_url = 'https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars'
browser.visit(hemispheres_url)
hemisphere_image_url = {}
short_url = 'https://astrogeology.usgs.gov/'
short_img_url = 'https://astrogeology.usgs.gov'
hemispheres_html = browser.html
hemispheres_soup = bs(hemispheres_html, 'html.parser')
hemisphere_items = hemispheres_soup.find('div', class_='collapsible results').find_all('div', class_='item')
for hem_url in hemisphere_items:
browser.visit(short_url + hem_url.a['href'])
hemisphere_body = bs(browser.html, 'html.parser').find('body')
image_title = hemisphere_body.find('div', class_='content').find('h2', class_='title').text
image_url = hemisphere_body.find('img', class_='wide-image')['src']
hemisphere_image_url['title'] = image_title
hemisphere_image_url['img_url'] = short_img_url + image_url
collection.insert_one(hemisphere_image_url.copy())
browser.quit()
|
# Strings
#######################################################################################################################
#
# Anton and Artur are old friends. Today they practice in writing strings. Anton must write each string
# with the lengths exactly N , based on the alphabet of size M . And Arthur, on the contrary, should write each
# string with the lengths exactly M , based on the alphabet of size N . Guys spend 1 second to write a single
# string. They start writing at the same time.
# And now boys are interested in one question. Is it true, that they will finish together? (It is assumed
# that the guys don't pause during the writing of strings).
#
# Input
# First line of the input contains the number of test cases T . It is followed by T tets cases.
# Each test case has 1 line. Line contains two integer numbers N and M separated by a single space.
#
# Output
# For each test case output "YES" if Anton and Artur will finish at the same time. Else print "NO"
#
# Constraits
# 1 <= T <= 50
# 1 <= N, M <= 10^10000
#
# SAMPLE INPUT
# 3
# 1 1
# 1 3
# 100 500
#
# SAMPLE OUTPUT
# YES
# NO
# NO
#
# Explanation
# In the second case Anton should write three strings. But Artur should write only one string,
# and he will finish earlier.
#
#######################################################################################################################
|
from notes.infraestructure.adapter.sqlalchemy import SqlAlchemyAdapter
from notes.domain.entity.notes import Notes
class NotesSqlAlchemyRepository:
def __init__(self):
self.__adapter = SqlAlchemyAdapter()
self.__adapter.entity = Notes
def create(self, notes: Notes):
try:
return self.__adapter.create(notes)
except Exception as e:
raise e
def get_all(self):
return self.__adapter.find_all()
|
import unittest
from google_finance import GoogleFinance
class TddInPythonExample_Plotter(unittest.TestCase):
def test_savepng(self):
gf = GoogleFinance()
gf.plot()
def test_addidxcolumn(self):
gf = GoogleFinance()
reshaped = gf.addidxcolumn([
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407],
[-1, 240, 239, 240, 231, 3260407]
],1)
self.assertEqual(reshaped.shape, (9, 7))
self.assertEqual(reshaped[5,0], 5)
|
from ScenarioHelper import *
def main():
CreateScenaFile(
"t1310_1.bin", # FileName
"t1310", # MapName
"t1310", # Location
0x00BD, # MapIndex
"ed7161",
0x00002000, # Flags
("", "", "", "", "", ""), # include
0x00, # PlaceNameNumber
0x1A, # PreInitFunctionIndex
b'\x00\xff\xff', # Unknown_51
# Information
[440, 441, 705, 859, 1004, 1061, 1187, 1417, 1489, 0, 1539, 0, 3172, 3319, 3376, 3529, 0, 3586, 0, 124, 14, 0, 0],
)
BuildStringList((
"t1310_1", # 0
))
ChipFrameInfo(440, 0) # 0
ScpFunction((
"Function_0_1B8", # 00, 0
"Function_1_1B9", # 01, 1
"Function_2_2C1", # 02, 2
"Function_3_35B", # 03, 3
"Function_4_3EC", # 04, 4
"Function_5_425", # 05, 5
"Function_6_4A3", # 06, 6
"Function_7_589", # 07, 7
"Function_8_5D1", # 08, 8
"Function_9_603", # 09, 9
"Function_10_C64", # 0A, 10
"Function_11_CF7", # 0B, 11
"Function_12_D30", # 0C, 12
"Function_13_DC9", # 0D, 13
"Function_14_E02", # 0E, 14
"Function_15_E7C", # 0F, 15
"Function_16_F16", # 10, 16
"Function_17_F8B", # 11, 17
"Function_18_FDC", # 12, 18
"Function_19_10AE", # 13, 19
"Function_20_1136", # 14, 20
"Function_21_11B5", # 15, 21
"Function_22_129C", # 16, 22
"Function_23_12E4", # 17, 23
"Function_24_1322", # 18, 24
"Function_25_1B7B", # 19, 25
"Function_26_1C0E", # 1A, 26
"Function_27_1C47", # 1B, 27
"Function_28_1CF0", # 1C, 28
"Function_29_1D87", # 1D, 29
"Function_30_1DC0", # 1E, 30
"Function_31_1E5E", # 1F, 31
"Function_32_1E5F", # 20, 32
"Function_33_1EC6", # 21, 33
"Function_34_1F5C", # 22, 34
"Function_35_1FAD", # 23, 35
"Function_36_2019", # 24, 36
"Function_37_2034", # 25, 37
"Function_38_2090", # 26, 38
"Function_39_20C2", # 27, 39
"Function_40_2159", # 28, 40
"Function_41_21DE", # 29, 41
"Function_42_2209", # 2A, 42
"Function_43_2231", # 2B, 43
"Function_44_22DE", # 2C, 44
"Function_45_233B", # 2D, 45
"Function_46_23C7", # 2E, 46
"Function_47_24AC", # 2F, 47
"Function_48_24F4", # 30, 48
"Function_49_2538", # 31, 49
"Function_50_2E9B", # 32, 50
"Function_51_2F31", # 33, 51
"Function_52_2F6A", # 34, 52
"Function_53_2FEC", # 35, 53
"Function_54_307E", # 36, 54
"Function_55_30B7", # 37, 55
"Function_56_311F", # 38, 56
"Function_57_31B8", # 39, 57
"Function_58_31F1", # 3A, 58
"Function_59_3273", # 3B, 59
"Function_60_330B", # 3C, 60
"Function_61_33C6", # 3D, 61
"Function_62_3432", # 3E, 62
"Function_63_3529", # 3F, 63
"Function_64_3585", # 40, 64
"Function_65_35C3", # 41, 65
"Function_66_360B", # 42, 66
"Function_67_36A0", # 43, 67
"Function_68_36DE", # 44, 68
"Function_69_3763", # 45, 69
"Function_70_3F80", # 46, 70
"Function_71_4016", # 47, 71
"Function_72_404F", # 48, 72
"Function_73_40DD", # 49, 73
"Function_74_4175", # 4A, 74
"Function_75_41A8", # 4B, 75
"Function_76_41F0", # 4C, 76
"Function_77_4258", # 4D, 77
"Function_78_4291", # 4E, 78
"Function_79_435F", # 4F, 79
"Function_80_43FD", # 50, 80
"Function_81_4452", # 51, 81
"Function_82_44D7", # 52, 82
"Function_83_45CA", # 53, 83
"Function_84_45FC", # 54, 84
"Function_85_462E", # 55, 85
"Function_86_4693", # 56, 86
"Function_87_4705", # 57, 87
"Function_88_47A0", # 58, 88
))
def Function_0_1B8(): pass
label("Function_0_1B8")
Return()
# Function_0_1B8 end
def Function_1_1B9(): pass
label("Function_1_1B9")
Call(1, 0)
SetChrPos(0x11, 24500, -6000, -19000, 0)
SetChrPos(0x12, 27500, -6000, -19000, 0)
SetChrPos(0x10, 24500, -6000, -13000, 180)
SetChrPos(0x13, 27500, -6000, -13000, 180)
SetChrPos(0x14, 27500, -4000, -16000, 0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
OP_68(26000, -5000, -16000, 0)
MoveCamera(330, 21, 0, 0)
OP_6E(650, 0)
SetCameraDistance(14000, 0)
OP_68(26000, -5000, -16000, 8000)
MoveCamera(295, 30, 0, 8000)
OP_6E(650, 8000)
SetCameraDistance(17000, 8000)
FadeToBright(1000, 0)
BeginChrThread(0x12, 3, 1, 2)
label("loc_2A6")
Jc((scpexpr(EXPR_GET_RESULT, 0x3), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_2BD")
Sleep(1)
Jump("loc_2A6")
label("loc_2BD")
OP_6F(0x79)
OP_0D()
Return()
# Function_1_1B9 end
def Function_2_2C1(): pass
label("Function_2_2C1")
def lambda_2C6():
OP_9D(0xFE, 0x6B6C, 0xFFFFEC78, 0xFFFFB6F4, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_2C6)
SetChrFlags(0xFE, 0x20)
def lambda_2E8():
label("loc_2E8")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_2E8")
QueueWorkItem2(0xFE, 2, lambda_2E8)
Sleep(350)
SetChrChipByIndex(0xFE, 0x15)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
#C0001
ChrTalk(
0x12,
"#6P#7A──前辈！\x02",
)
#Auto
def lambda_328():
OP_9D(0xFE, 0x5FB4, 0xFFFFF254, 0xFFFFBBA4, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_328)
BeginChrThread(0x11, 3, 1, 3)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_2_2C1 end
def Function_3_35B(): pass
label("Function_3_35B")
Sleep(500)
Sound(809, 0, 100, 0)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x26)
SetChrSubChip(0xFE, 0x0)
def lambda_376():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFBD98, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_376)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
Sound(442, 0, 90, 0)
#C0002
ChrTalk(
0x11,
"#5P#5A哦！\x02",
)
#Auto
def lambda_3AF():
OP_96(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFCC0C, 0x4E20, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3AF)
BeginChrThread(0x10, 3, 1, 4)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_3_35B end
def Function_4_3EC(): pass
label("Function_4_3EC")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_3FF():
OP_9D(0xFE, 0x6A40, 0xFFFFEC78, 0xFFFFCD38, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3FF)
BeginChrThread(0x13, 3, 1, 5)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_4_3EC end
def Function_5_425(): pass
label("Function_5_425")
SetChrFlags(0xFE, 0x20)
def lambda_42F():
label("loc_42F")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_42F")
QueueWorkItem2(0xFE, 2, lambda_42F)
Sleep(350)
SetChrChipByIndex(0xFE, 0x1C)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
#C0003
ChrTalk(
0x13,
"#12P#6A交给你了！\x02",
)
#Auto
def lambda_470():
OP_9D(0xFE, 0x5FB4, 0xFFFFF254, 0xFFFFC694, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_470)
BeginChrThread(0x10, 3, 1, 6)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_5_425 end
def Function_6_4A3(): pass
label("Function_6_4A3")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x35)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_4BE():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_4BE)
Sleep(600)
#C0004
ChrTalk(
0x10,
"#11P#4S#5A呀！！#3S\x02",
)
#Auto
SetChrSubChip(0xFE, 0x1)
OP_82(0x64, 0x0, 0xBB8, 0x96)
PlayEffect(0x0, 0xFF, 0xFE, 0x5, 0, 700, 1000, 0, 0, 0, 1000, 1000, 1000, 0xFF, 0, 0, 0, 0)
Sound(442, 0, 100, 0)
Sound(547, 0, 40, 0)
BeginChrThread(0x14, 3, 1, 7)
BeginChrThread(0x11, 3, 1, 8)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
WaitChrThread(0x11, 3)
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x1), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
Return()
# Function_6_4A3 end
def Function_7_589(): pass
label("Function_7_589")
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_96(0xFE, 0x5AD2, 0xFFFFE890, 0xFFFFADF8, 0x4E20, 0x0)
Sound(443, 0, 100, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x54F6, 0xFFFFE890, 0xFFFF8FBC, 0x3E8, 0x7D0)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
Return()
# Function_7_589 end
def Function_8_5D1(): pass
label("Function_8_5D1")
SetChrChipByIndex(0xFE, 0x27)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x7D0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_8_5D1 end
def Function_9_603(): pass
label("Function_9_603")
OP_50(0x67, (scpexpr(EXPR_PUSH_LONG, 0x2), scpexpr(EXPR_ADD_SAVE), scpexpr(EXPR_END)))
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x11, 27500, -6000, -19000, 0)
SetChrPos(0x12, 24500, -6000, -10000, 180)
SetChrPos(0x13, 27500, -6000, -13000, 180)
SetChrPos(0x10, 21300, -6000, -16000, 90)
SetChrPos(0x14, 24500, -5500, -10200, 0)
SetChrFlags(0x14, 0x8)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x12, 0x9)
SetChrSubChip(0x12, 0x0)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(17000, 0)
OP_68(26000, -5000, -16000, 12000)
MoveCamera(305, 30, 0, 12000)
FadeToBright(1000, 0)
OP_0D()
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
BeginChrThread(0x12, 3, 1, 10)
label("loc_6FB")
Jc((scpexpr(EXPR_GET_RESULT, 0x3), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_712")
Sleep(1)
Jump("loc_6FB")
label("loc_712")
OP_4B(0x14, 0xFF)
RunExpression(0x0, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
FadeToDark(300, 0, 100)
OP_0D()
Menu(
0,
-1,
-1,
0,
(
"直接扣击\x01", # 0
"托球回传，由兰迪发动攻击\x01", # 1
)
)
MenuEnd(0x0)
OP_60(0x0)
FadeToBright(300, 0)
OP_0D()
OP_4C(0x14, 0xFF)
Jc((scpexpr(EXPR_GET_RESULT, 0x0), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_9DD")
MoveCamera(315, 25, 0, 1500)
SetCameraDistance(15000, 1500)
BeginChrThread(0x101, 3, 1, 18)
WaitChrThread(0x101, 3)
Sound(909, 0, 70, 0)
Sleep(500)
#C0005
ChrTalk(
0x10,
"#13400F#5P#N出界～！！\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x11, 0x8)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x13, 0xA)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x12, 0x9)
SetChrSubChip(0x12, 0x0)
OP_63(0x101, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
Sleep(1000)
#C0006
ChrTalk(
0x101,
"#12506F#6P糟糕，太着急了吗……\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
OP_93(0x13, 0xE1, 0x1F4)
#C0007
ChrTalk(
0x13,
"#12902F呵呵，承让了。\x02",
)
CloseMessageWindow()
#C0008
ChrTalk(
0x12,
"#13006F#5P#N真危险～\x02",
)
CloseMessageWindow()
OP_93(0x101, 0x5A, 0x1F4)
#C0009
ChrTalk(
0x101,
"#12500F抱歉！兰迪！\x02",
)
CloseMessageWindow()
OP_93(0x11, 0x10E, 0x1F4)
#C0010
ChrTalk(
0x11,
(
"#12800F#12P没事没事！\x01",
"接下来就是我们的反击了！\x02",
)
)
CloseMessageWindow()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x11, 27500, -6000, -20000, 0)
SetChrPos(0x13, 24500, -6000, -12000, 180)
SetChrPos(0x12, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0011
ChrTalk(
0x10,
(
"#13400F#5P……比赛结束！！\x02\x03",
"#13409F７比１２，\x01",
"瓦吉队获胜～！\x02",
)
)
CloseMessageWindow()
#C0012
ChrTalk(
0x101,
"#12506F#6P呼，输了呢……\x02",
)
CloseMessageWindow()
Jump("loc_C58")
label("loc_9DD")
OP_2C(0xA5, 0x1)
MoveCamera(315, 25, 0, 2000)
SetCameraDistance(15000, 2000)
BeginChrThread(0x101, 3, 1, 20)
WaitChrThread(0x101, 3)
Sound(909, 0, 70, 0)
Sleep(500)
#C0013
ChrTalk(
0x10,
"#13405F#5P#N哦哦！厉害啊，兰迪！\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x11, 0x8)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x13, 0xA)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x12, 0x9)
SetChrSubChip(0x12, 0x0)
#C0014
ChrTalk(
0x12,
"#13002F#11P#N唔……干得漂亮。\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
#C0015
ChrTalk(
0x13,
(
"#12906F#11P哎呀呀，身高差距\x01",
"实在是让人头疼呢。\x02",
)
)
CloseMessageWindow()
OP_93(0x11, 0x10E, 0x1F4)
#C0016
ChrTalk(
0x11,
(
"#12809F#12P传得好，罗伊德，\x01",
"你的判断力果然出色。\x02",
)
)
CloseMessageWindow()
OP_93(0x101, 0x5A, 0x1F4)
#C0017
ChrTalk(
0x101,
(
"#12509F#5P哈哈，我们只是暂时领先而已。\x02\x03",
"#12500F好！乘胜追击吧！！\x02",
)
)
CloseMessageWindow()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x11, 27500, -6000, -20000, 0)
SetChrPos(0x13, 24500, -6000, -12000, 180)
SetChrPos(0x12, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0018
ChrTalk(
0x10,
(
"#13400F#5P……比赛结束！！\x02\x03",
"#13409F１２比８，警察弟弟队获胜～！\x02",
)
)
CloseMessageWindow()
#C0019
ChrTalk(
0x101,
"#12500F#6P好！赢了！！\x02",
)
CloseMessageWindow()
label("loc_C58")
FadeToDark(1000, 0, -1)
OP_0D()
Return()
# Function_9_603 end
def Function_10_C64(): pass
label("Function_10_C64")
ClearChrFlags(0x14, 0x8)
Sound(802, 0, 60, 0)
def lambda_C74():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_C74)
SetChrChipByIndex(0xFE, 0x28)
SetChrSubChip(0xFE, 0x0)
Sleep(1000)
Sound(441, 0, 100, 0)
SetChrSubChip(0xFE, 0x1)
#C0020
ChrTalk(
0x12,
"#11P#5A呼！\x02",
)
#Auto
def lambda_CB6():
OP_9D(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFB6F4, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_CB6)
BeginChrThread(0x101, 3, 1, 11)
Sleep(500)
SetChrChipByIndex(0xFE, 0x9)
SetChrSubChip(0xFE, 0x0)
OP_9B(0x0, 0xFE, 0x0, 0xBB8, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_10_C64 end
def Function_11_CF7(): pass
label("Function_11_CF7")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_D0A():
OP_9D(0xFE, 0x6B6C, 0xFFFFEE6C, 0xFFFFB5C8, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_D0A)
BeginChrThread(0x11, 3, 1, 12)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_11_CF7 end
def Function_12_D30(): pass
label("Function_12_D30")
SetChrFlags(0xFE, 0x20)
def lambda_D3A():
label("loc_D3A")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_D3A")
QueueWorkItem2(0xFE, 2, lambda_D3A)
Sleep(350)
SetChrChipByIndex(0xFE, 0x25)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
#C0021
ChrTalk(
0x11,
"#6P#6A哦！\x02",
)
#Auto
def lambda_D74():
OP_9D(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFCC0C, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_D74)
BeginChrThread(0x13, 3, 1, 13)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sleep(1500)
SetChrChipByIndex(0xFE, 0x8)
SetChrSubChip(0xFE, 0x0)
OP_9B(0x0, 0xFE, 0x0, 0x7D0, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_12_D30 end
def Function_13_DC9(): pass
label("Function_13_DC9")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_DDC():
OP_9D(0xFE, 0x5FB4, 0xFFFFEC78, 0xFFFFCD38, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_DDC)
BeginChrThread(0x12, 3, 1, 14)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_13_DC9 end
def Function_14_E02(): pass
label("Function_14_E02")
SetChrFlags(0xFE, 0x20)
def lambda_E0C():
label("loc_E0C")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_E0C")
QueueWorkItem2(0xFE, 2, lambda_E0C)
Sleep(350)
#C0022
ChrTalk(
0x12,
"#11P#8A瓦吉！\x02",
)
#Auto
SetChrChipByIndex(0xFE, 0x15)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_E49():
OP_9D(0xFE, 0x6B6C, 0xFFFFF448, 0xFFFFC75C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_E49)
BeginChrThread(0x13, 3, 1, 15)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_14_E02 end
def Function_15_E7C(): pass
label("Function_15_E7C")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x30)
SetChrSubChip(0xFE, 0x0)
#C0023
ChrTalk(
0x13,
"#11P#5A嗯……！\x02",
)
#Auto
Sound(809, 0, 100, 0)
def lambda_EAB():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_EAB)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
def lambda_ED3():
OP_98(0xFE, 0x0, 0xFFFFFCE0, 0xFFFFF830, 0x2EE0, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_ED3)
BeginChrThread(0x11, 3, 1, 16)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sound(442, 0, 80, 0)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_15_E7C end
def Function_16_F16(): pass
label("Function_16_F16")
SetChrChipByIndex(0xFE, 0x27)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
Sound(809, 0, 100, 0)
def lambda_F2E():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x1388)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_F2E)
WaitChrThread(0x14, 1)
def lambda_F4F():
OP_9D(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFCD38, 0x3E8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_F4F)
BeginChrThread(0x12, 3, 1, 17)
Sound(441, 0, 80, 0)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_16_F16 end
def Function_17_F8B(): pass
label("Function_17_F8B")
WaitChrThread(0x14, 1)
SetChrFlags(0xFE, 0x20)
OP_93(0xFE, 0xB4, 0x0)
ClearChrFlags(0xFE, 0x20)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_FAF():
OP_9D(0xFE, 0x5FB4, 0xFFFFED40, 0xFFFFB5C8, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_FAF)
Sleep(300)
SetChrSubChip(0xFE, 0x0)
Sleep(200)
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x1), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
Return()
# Function_17_F8B end
def Function_18_FDC(): pass
label("Function_18_FDC")
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x21)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_FF4():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFBBA4, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_FF4)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 100, 0)
Sound(547, 0, 40, 0)
OP_82(0x64, 0x0, 0xBB8, 0x96)
PlayEffect(0x0, 0xFF, 0xFE, 0x5, 0, 700, 1000, 0, 0, 0, 1000, 1000, 1000, 0xFF, 0, 0, 0, 0)
#C0024
ChrTalk(
0x101,
"#5P#6A#4S嘿！！#3S\x02",
)
#Auto
BeginChrThread(0x14, 3, 1, 19)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
Return()
# Function_18_FDC end
def Function_19_10AE(): pass
label("Function_19_10AE")
SetChrFlags(0x13, 0x20)
def lambda_10B8():
label("loc_10B8")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_10B8")
QueueWorkItem2(0x13, 2, lambda_10B8)
SetChrFlags(0x12, 0x20)
def lambda_10CF():
label("loc_10CF")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_10CF")
QueueWorkItem2(0x12, 2, lambda_10CF)
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_96(0xFE, 0x68F6, 0xFFFFE890, 0xFFFFDDBE, 0x4E20, 0x0)
Sound(443, 0, 100, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x7A76, 0xFFFFE868, 0x1B58, 0x9C4, 0x3E8)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
EndChrThread(0x13, 0x2)
ClearChrFlags(0x13, 0x20)
EndChrThread(0x12, 0x2)
ClearChrFlags(0x12, 0x20)
Return()
# Function_19_10AE end
def Function_20_1136(): pass
label("Function_20_1136")
SetChrFlags(0xFE, 0x20)
def lambda_1140():
label("loc_1140")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_1140")
QueueWorkItem2(0xFE, 2, lambda_1140)
Sleep(350)
SetChrChipByIndex(0xFE, 0x20)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
#C0025
ChrTalk(
0x101,
"#5P#5A拜托了！\x02",
)
#Auto
def lambda_117E():
OP_9D(0xFE, 0x6B6C, 0xFFFFF448, 0xFFFFBF8C, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_117E)
BeginChrThread(0x11, 3, 1, 21)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x11, 3)
Return()
# Function_20_1136 end
def Function_21_11B5(): pass
label("Function_21_11B5")
Sleep(600)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x26)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_11D0():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_11D0)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 100, 0)
Sound(547, 0, 40, 0)
OP_82(0x64, 0x0, 0xBB8, 0x96)
PlayEffect(0x0, 0xFF, 0xFE, 0x5, 0, 700, 1000, 0, 0, 0, 1000, 1000, 1000, 0xFF, 0, 0, 0, 0)
#C0026
ChrTalk(
0x11,
"#5P#10A#4S噢噢噢噢噢！！#3S\x02",
)
#Auto
Sleep(600)
BeginChrThread(0x14, 3, 1, 22)
BeginChrThread(0x13, 3, 1, 23)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
WaitChrThread(0x13, 3)
Return()
# Function_21_11B5 end
def Function_22_129C(): pass
label("Function_22_129C")
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_96(0xFE, 0x6F9A, 0xFFFFE890, 0xFFFFCCCA, 0x4E20, 0x0)
Sound(443, 0, 100, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x7F76, 0xFFFFE7F0, 0x762, 0x1388, 0x3E8)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
Return()
# Function_22_129C end
def Function_23_12E4(): pass
label("Function_23_12E4")
SetChrChipByIndex(0xFE, 0x31)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
Sound(809, 0, 100, 0)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x7D0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_23_12E4 end
def Function_24_1322(): pass
label("Function_24_1322")
OP_50(0x68, (scpexpr(EXPR_PUSH_LONG, 0x2), scpexpr(EXPR_ADD_SAVE), scpexpr(EXPR_END)))
SetChrPos(0x101, 27500, -6000, -19000, 0)
SetChrPos(0x12, 24500, -6000, -19000, 0)
SetChrPos(0x10, 24500, -6000, -10000, 180)
SetChrPos(0x13, 27500, -6000, -13000, 180)
SetChrPos(0x11, 21300, -6000, -16000, 90)
SetChrPos(0x14, 24500, -5500, -10200, 0)
SetChrFlags(0x14, 0x8)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(17000, 0)
OP_68(26000, -5000, -16000, 13000)
MoveCamera(305, 30, 0, 13000)
FadeToBright(1000, 0)
OP_0D()
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
BeginChrThread(0x10, 3, 1, 25)
label("loc_141A")
Jc((scpexpr(EXPR_GET_RESULT, 0x3), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_1431")
Sleep(1)
Jump("loc_141A")
label("loc_1431")
OP_4B(0x14, 0xFF)
RunExpression(0x0, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
FadeToDark(300, 0, 100)
OP_0D()
Menu(
0,
-1,
-1,
0,
(
"预判为强力扣击，参与阻截\x01", # 0
"判断对方的真意，退至后场\x01", # 1
)
)
MenuEnd(0x0)
OP_60(0x0)
FadeToBright(300, 0)
OP_0D()
OP_4C(0x14, 0xFF)
Jc((scpexpr(EXPR_GET_RESULT, 0x0), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_17FF")
MoveCamera(315, 25, 0, 2000)
SetCameraDistance(15000, 2000)
BeginChrThread(0x13, 3, 1, 39)
WaitChrThread(0x13, 3)
Sound(909, 0, 70, 0)
Sleep(500)
#C0027
ChrTalk(
0x11,
(
"#12809F#5P#N伊莉娅小姐队得分！\x02\x03",
"#12803F话说回来，不愧是瓦吉啊……\x01",
"竟然击出如此狡诈的球。\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x12, 0x9)
SetChrSubChip(0x12, 0x0)
SetChrChipByIndex(0x13, 0xA)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
OP_93(0x13, 0x10E, 0x1F4)
#C0028
ChrTalk(
0x13,
(
"#12902F#12P呵呵，别说得这么难听嘛，\x01",
"这也是战术的一种。\x02",
)
)
CloseMessageWindow()
OP_93(0x10, 0x87, 0x1F4)
#C0029
ChrTalk(
0x10,
(
"#13404F#5P嗯，和他们这种单纯刻板的对手比赛，\x01",
"没有比这更好的战术了～\x02",
)
)
CloseMessageWindow()
OP_63(0x101, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
OP_63(0x12, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
Sleep(1000)
OP_93(0x12, 0x5A, 0x1F4)
#C0030
ChrTalk(
0x12,
(
"#13001F#5P罗、罗伊德警官……\x01",
"他们竟敢这样说我们！\x02",
)
)
CloseMessageWindow()
OP_93(0x101, 0x10E, 0x1F4)
#C0031
ChrTalk(
0x101,
(
"#12510F#12P唔唔……绝、绝不能输！\x02\x03",
"#12501F既然如此，诺艾尔，我们就靠意志来取胜吧！\x01",
"无论如何也要接住他们的球！\x02",
)
)
CloseMessageWindow()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrPos(0x101, 27500, -6000, -19000, 0)
SetChrPos(0x12, 24500, -6000, -19000, 0)
SetChrPos(0x10, 24500, -6000, -13000, 180)
SetChrPos(0x13, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0032
ChrTalk(
0x11,
(
"#12800F#5P……比赛结束！！\x02\x03",
"#12809F３比１２，\x01",
"伊莉娅小姐队获胜！！\x02",
)
)
CloseMessageWindow()
#C0033
ChrTalk(
0x101,
"#12506F#6P呜……还是不行吗……\x02",
)
CloseMessageWindow()
Jump("loc_1B6F")
label("loc_17FF")
OP_2C(0xA5, 0x1)
MoveCamera(315, 25, 0, 2000)
SetCameraDistance(15000, 2000)
BeginChrThread(0x13, 3, 1, 43)
WaitChrThread(0x13, 3)
Sleep(600)
Sound(909, 0, 70, 0)
Sleep(500)
#C0034
ChrTalk(
0x11,
(
"#12800F#5P#N罗伊德队得分！\x02\x03",
"#12809F哈哈，干得不错嘛！\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x12, 0x9)
SetChrSubChip(0x12, 0x0)
SetChrChipByIndex(0x13, 0xA)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
#C0035
ChrTalk(
0x13,
(
"#12906F#11P哎呀呀，没想到会被你识破。\x02\x03",
"#12902F平时那么单纯刻板，\x01",
"竟能做出如此出色的判断～\x02",
)
)
CloseMessageWindow()
#C0036
ChrTalk(
0x101,
(
"#12502F#6P以瓦吉的性格来说，\x01",
"在那种情况下肯定会采用取巧手段。\x02\x03",
"#12504F与其正面对攻，不如反其道而行。\x02",
)
)
CloseMessageWindow()
OP_93(0x12, 0x5A, 0x1F4)
#C0037
ChrTalk(
0x12,
"#13000F#5P成功了！罗伊德警官！\x02",
)
CloseMessageWindow()
OP_93(0x10, 0x5A, 0x1F4)
#C0038
ChrTalk(
0x10,
(
"#13400F#5P呵呵，似乎有些\x01",
"小看他们了呢。\x02",
)
)
CloseMessageWindow()
#C0039
ChrTalk(
0x13,
"#12904F哈哈，看来是这样啊。\x02",
)
CloseMessageWindow()
OP_93(0x101, 0x10E, 0x1F4)
#C0040
ChrTalk(
0x101,
(
"#12500F#12P好！诺艾尔！\x01",
"我们就保持这种状态，\x01",
"把握住比赛的节奏吧！\x02",
)
)
CloseMessageWindow()
#C0041
ChrTalk(
0x12,
"#13009F#5P嗯！明白了！！\x02",
)
CloseMessageWindow()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrPos(0x101, 27500, -6000, -19000, 0)
SetChrPos(0x12, 24500, -6000, -19000, 0)
SetChrPos(0x10, 24500, -6000, -13000, 180)
SetChrPos(0x13, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0042
ChrTalk(
0x11,
(
"#12800F#5P……比赛结束！！\x02\x03",
"#12809F１２比１１，\x01",
"罗伊德队获胜！！\x02",
)
)
CloseMessageWindow()
#C0043
ChrTalk(
0x101,
"#12512F#6P赢、赢了……勉强险胜啊！\x02",
)
CloseMessageWindow()
label("loc_1B6F")
FadeToDark(1000, 0, -1)
OP_0D()
Return()
# Function_24_1322 end
def Function_25_1B7B(): pass
label("Function_25_1B7B")
ClearChrFlags(0x14, 0x8)
Sound(802, 0, 60, 0)
def lambda_1B8B():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1B8B)
SetChrChipByIndex(0xFE, 0x32)
SetChrSubChip(0xFE, 0x0)
Sleep(1000)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
#C0044
ChrTalk(
0x10,
"#11P#5A嘿！\x02",
)
#Auto
def lambda_1BCD():
OP_9D(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFB6F4, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1BCD)
BeginChrThread(0x12, 3, 1, 26)
Sleep(500)
SetChrChipByIndex(0xFE, 0x3)
SetChrSubChip(0xFE, 0x0)
OP_9B(0x0, 0xFE, 0x0, 0xBB8, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_25_1B7B end
def Function_26_1C0E(): pass
label("Function_26_1C0E")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_1C21():
OP_9D(0xFE, 0x6B6C, 0xFFFFEDA4, 0xFFFFB5C8, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1C21)
BeginChrThread(0x101, 3, 1, 27)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_26_1C0E end
def Function_27_1C47(): pass
label("Function_27_1C47")
SetChrFlags(0xFE, 0x20)
def lambda_1C51():
label("loc_1C51")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_1C51")
QueueWorkItem2(0xFE, 2, lambda_1C51)
Sleep(350)
SetChrChipByIndex(0xFE, 0x20)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 60, 0)
#C0045
ChrTalk(
0x101,
"#6P#5A诺艾尔！\x02",
)
#Auto
def lambda_1C8F():
OP_9D(0xFE, 0x5FB4, 0xFFFFF448, 0xFFFFBBA4, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1C8F)
BeginChrThread(0x12, 3, 1, 28)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Sleep(1500)
SetChrChipByIndex(0xFE, 0xFF)
SetChrSubChip(0xFE, 0x0)
OP_93(0xFE, 0x0, 0x1F4)
OP_98(0xFE, 0x0, 0x0, 0xFFFFFC18, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_27_1C47 end
def Function_28_1CF0(): pass
label("Function_28_1CF0")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x2B)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_1D0B():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFBD98, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_1D0B)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 80, 0)
#C0046
ChrTalk(
0x12,
"#5P#5A嗯！！\x02",
)
#Auto
def lambda_1D4A():
OP_96(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFCC0C, 0x36B0, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1D4A)
BeginChrThread(0x13, 3, 1, 29)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_28_1CF0 end
def Function_29_1D87(): pass
label("Function_29_1D87")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_1D9A():
OP_9D(0xFE, 0x5FB4, 0xFFFFF448, 0xFFFFC75C, 0xC80, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1D9A)
BeginChrThread(0x10, 3, 1, 30)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_29_1D87 end
def Function_30_1DC0(): pass
label("Function_30_1DC0")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x35)
SetChrSubChip(0xFE, 0x0)
#C0047
ChrTalk(
0x10,
"#11P#5A接球！\x02",
)
#Auto
Sound(809, 0, 100, 0)
def lambda_1DED():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_1DED)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 80, 0)
def lambda_1E1B():
OP_96(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFB30C, 0x3A98, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1E1B)
BeginChrThread(0x12, 3, 1, 31)
BeginChrThread(0x101, 3, 1, 32)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_30_1DC0 end
def Function_31_1E5E(): pass
label("Function_31_1E5E")
Return()
# Function_31_1E5E end
def Function_32_1E5F(): pass
label("Function_32_1E5F")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_1E72():
OP_9D(0xFE, 0x5FB4, 0xFFFFEC78, 0xFFFFBD98, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1E72)
BeginChrThread(0x12, 3, 1, 33)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Sleep(500)
SetChrChipByIndex(0xFE, 0xFF)
SetChrSubChip(0xFE, 0x0)
OP_93(0xFE, 0x0, 0x1F4)
OP_98(0xFE, 0x0, 0x0, 0x5DC, 0xBB8, 0x0)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_32_1E5F end
def Function_33_1EC6(): pass
label("Function_33_1EC6")
SetChrFlags(0xFE, 0x20)
def lambda_1ED0():
label("loc_1ED0")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_1ED0")
QueueWorkItem2(0xFE, 2, lambda_1ED0)
Sleep(350)
SetChrChipByIndex(0xFE, 0x15)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_1EFB():
OP_9D(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFCC0C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1EFB)
BeginChrThread(0x13, 3, 1, 34)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Sleep(1700)
SetChrChipByIndex(0xFE, 0x9)
SetChrSubChip(0xFE, 0x0)
OP_93(0xFE, 0x0, 0x1F4)
OP_98(0xFE, 0x5DC, 0x0, 0x0, 0xBB8, 0x0)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_33_1EC6 end
def Function_34_1F5C(): pass
label("Function_34_1F5C")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
#C0048
ChrTalk(
0x13,
"#12P#5A看招吧……！\x02",
)
#Auto
def lambda_1F87():
OP_9D(0xFE, 0x5FB4, 0xFFFFEC78, 0xFFFFC568, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1F87)
BeginChrThread(0x10, 3, 1, 35)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_34_1F5C end
def Function_35_1FAD(): pass
label("Function_35_1FAD")
SetChrFlags(0xFE, 0x20)
def lambda_1FB7():
label("loc_1FB7")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_1FB7")
QueueWorkItem2(0xFE, 2, lambda_1FB7)
Sleep(350)
SetChrChipByIndex(0xFE, 0x34)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_1FE2():
OP_9D(0xFE, 0x6B6C, 0xFFFFF448, 0xFFFFC75C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_1FE2)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x1), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
Return()
# Function_35_1FAD end
def Function_36_2019(): pass
label("Function_36_2019")
Sleep(500)
SetChrChipByIndex(0xFE, 0x3)
SetChrSubChip(0xFE, 0x0)
OP_93(0xFE, 0xB4, 0x1F4)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_36_2019 end
def Function_37_2034(): pass
label("Function_37_2034")
BeginChrThread(0x10, 3, 1, 36)
SetChrChipByIndex(0xFE, 0xFF)
SetChrSubChip(0xFE, 0x0)
OP_98(0xFE, 0x0, 0x0, 0x5DC, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
SetChrChipByIndex(0xFE, 0x22)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x7D0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_37_2034 end
def Function_38_2090(): pass
label("Function_38_2090")
SetChrChipByIndex(0xFE, 0x2C)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x7D0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_38_2090 end
def Function_39_20C2(): pass
label("Function_39_20C2")
BeginChrThread(0x101, 3, 1, 37)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x30)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_20E0():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_20E0)
Sleep(600)
#C0049
ChrTalk(
0x13,
"#12P#5A骗你们啦¤\x02",
)
#Auto
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
BeginChrThread(0x14, 3, 1, 40)
BeginChrThread(0x12, 3, 1, 38)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
Sound(441, 0, 100, 0)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
WaitChrThread(0x101, 3)
WaitChrThread(0x12, 3)
Return()
# Function_39_20C2 end
def Function_40_2159(): pass
label("Function_40_2159")
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFAC04, 0x7D0, 0x3E8)
Sound(443, 0, 40, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFA628, 0x3E8, 0x3E8)
Sound(441, 0, 60, 0)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFA240, 0x1F4, 0x3E8)
Sound(441, 0, 40, 0)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFA04C, 0xC8, 0x3E8)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
Return()
# Function_40_2159 end
def Function_41_21DE(): pass
label("Function_41_21DE")
BeginChrThread(0x10, 3, 1, 36)
SetChrChipByIndex(0xFE, 0xFF)
SetChrSubChip(0xFE, 0x0)
OP_98(0xFE, 0x0, 0x0, 0xFFFFF830, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_41_21DE end
def Function_42_2209(): pass
label("Function_42_2209")
Sleep(300)
SetChrChipByIndex(0xFE, 0x9)
SetChrSubChip(0xFE, 0x0)
OP_98(0xFE, 0x0, 0x0, 0xFFFFFC18, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_42_2209 end
def Function_43_2231(): pass
label("Function_43_2231")
BeginChrThread(0x101, 3, 1, 41)
BeginChrThread(0x12, 3, 1, 42)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x30)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_2255():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_2255)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
#C0050
ChrTalk(
0x13,
"#12P#5A什么……！？\x02",
)
#Auto
def lambda_2295():
OP_9D(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFB118, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_2295)
BeginChrThread(0x101, 3, 1, 44)
Sleep(100)
Sound(441, 0, 100, 0)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Sleep(5500)
Return()
# Function_43_2231 end
def Function_44_22DE(): pass
label("Function_44_22DE")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_22F1():
OP_9D(0xFE, 0x6590, 0xFFFFEC78, 0xFFFFB9B0, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_22F1)
BeginChrThread(0x12, 3, 1, 45)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
SetChrChipByIndex(0xFE, 0xFF)
SetChrSubChip(0xFE, 0x0)
OP_98(0xFE, 0x0, 0x0, 0x5DC, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_44_22DE end
def Function_45_233B(): pass
label("Function_45_233B")
SetChrFlags(0xFE, 0x20)
def lambda_2345():
label("loc_2345")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_2345")
QueueWorkItem2(0xFE, 2, lambda_2345)
Sleep(350)
SetChrChipByIndex(0xFE, 0x15)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_2370():
OP_9D(0xFE, 0x6B6C, 0xFFFFF448, 0xFFFFBBA4, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_2370)
BeginChrThread(0x101, 3, 1, 46)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
OP_98(0x10, 0x0, 0x0, 0x5DC, 0xFA0, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
Return()
# Function_45_233B end
def Function_46_23C7(): pass
label("Function_46_23C7")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x21)
SetChrSubChip(0xFE, 0x0)
#C0051
ChrTalk(
0x101,
"#5P#5A#4S噢噢噢噢噢！#3S\x02",
)
#Auto
Sound(809, 0, 100, 0)
def lambda_23FF():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFBD98, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_23FF)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 100, 0)
Sound(547, 0, 40, 0)
OP_82(0x64, 0x0, 0xBB8, 0x96)
PlayEffect(0x0, 0xFF, 0xFE, 0x5, 0, 700, 1000, 0, 0, 0, 1000, 1000, 1000, 0xFF, 0, 0, 0, 0)
BeginChrThread(0x14, 3, 1, 47)
BeginChrThread(0x13, 3, 1, 48)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
WaitChrThread(0x13, 3)
Return()
# Function_46_23C7 end
def Function_47_24AC(): pass
label("Function_47_24AC")
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_96(0xFE, 0x6658, 0xFFFFE890, 0xFFFFCE5A, 0x4E20, 0x0)
Sound(443, 0, 100, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x774C, 0xFFFFE890, 0xFFFFFA9C, 0x1388, 0x3E8)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
Return()
# Function_47_24AC end
def Function_48_24F4(): pass
label("Function_48_24F4")
SetChrChipByIndex(0xFE, 0x31)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
Sound(809, 0, 100, 0)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x7D0)
Sound(441, 0, 80, 0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_48_24F4 end
def Function_49_2538(): pass
label("Function_49_2538")
OP_50(0x69, (scpexpr(EXPR_PUSH_LONG, 0x2), scpexpr(EXPR_ADD_SAVE), scpexpr(EXPR_END)))
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x13, 27500, -6000, -22000, 0)
SetChrPos(0x11, 24500, -6000, -13000, 180)
SetChrPos(0x10, 27500, -6000, -13000, 180)
SetChrPos(0x12, 21300, -6000, -16000, 90)
SetChrPos(0x14, 27500, -5500, -21800, 0)
SetChrFlags(0x14, 0x8)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x13, 0xA)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(17000, 0)
OP_68(26000, -5000, -16000, 15000)
MoveCamera(305, 30, 0, 15000)
FadeToBright(1000, 0)
OP_0D()
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
BeginChrThread(0x13, 3, 1, 50)
label("loc_2630")
Jc((scpexpr(EXPR_GET_RESULT, 0x3), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_2647")
Sleep(1)
Jump("loc_2630")
label("loc_2647")
OP_4B(0x14, 0xFF)
RunExpression(0x0, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
FadeToDark(300, 0, 100)
OP_0D()
Menu(
0,
-1,
-1,
0,
(
"将球强攻向伊莉娅和兰迪之间\x01", # 0
"瞄准后场边界线，击出弧线球\x01", # 1
)
)
MenuEnd(0x0)
OP_60(0x0)
FadeToBright(300, 0)
OP_0D()
OP_4C(0x14, 0xFF)
Jc((scpexpr(EXPR_GET_RESULT, 0x0), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_2B08")
MoveCamera(315, 25, 0, 2000)
SetCameraDistance(15000, 2000)
BeginChrThread(0x101, 3, 1, 62)
WaitChrThread(0x101, 3)
Sound(909, 0, 70, 0)
Sleep(500)
#C0052
ChrTalk(
0x12,
"#13002F#5P#N伊莉娅小姐队得分！\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x13, 0xA)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x11, 0x8)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
OP_93(0x11, 0x5A, 0x1F4)
#C0053
ChrTalk(
0x11,
(
"#12809F#5P完美！！\x01",
"真不愧是伊莉娅小姐！！\x02",
)
)
CloseMessageWindow()
OP_93(0x10, 0x10E, 0x1F4)
#C0054
ChrTalk(
0x10,
"#13400F#12P啊哈哈，普普通通啦。\x02",
)
CloseMessageWindow()
#C0055
ChrTalk(
0x13,
(
"#12906F#12P#N哎呀呀，\x01",
"竟然选择正面强攻，难道你认为自己\x01",
"可以胜过他们二人的身体能力吗？\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
def lambda_27F5():
OP_93(0x11, 0xB4, 0x1F4)
ExitThread()
QueueWorkItem(0x11, 0, lambda_27F5)
Sleep(30)
def lambda_2805():
OP_93(0x10, 0xB4, 0x1F4)
ExitThread()
QueueWorkItem(0x10, 0, lambda_2805)
Sleep(30)
WaitChrThread(0x11, 0)
WaitChrThread(0x10, 0)
OP_93(0x101, 0x87, 0x1F4)
#C0056
ChrTalk(
0x101,
(
"#12506F#5P唉，真丢脸……\x02\x03",
"#12505F……话说回来，瓦吉，\x01",
"你刚才突然说『边界』，\x01",
"到底是什么意思？\x02",
)
)
CloseMessageWindow()
#C0057
ChrTalk(
0x13,
(
"#12900F#12P#N哦，我当时就料到\x01",
"伊莉娅小姐会发起拦截了，\x01",
"所以觉得正面强攻肯定徒劳无功。\x02\x03",
"#12904F『边界』就是边界线……\x01",
"也就是说，让你击出弧线吊球，\x01",
"使球落到后场边界线处。\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
OP_63(0x101, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
Sleep(1000)
#C0058
ChrTalk(
0x101,
(
"#12506F#5P这……你突然那样说，\x01",
"又有谁能听得懂啊！\x02",
)
)
CloseMessageWindow()
#C0059
ChrTalk(
0x13,
(
"#12909F#12P#N啊哈哈，抱歉抱歉。\x02\x03",
"#12900F好啦，尽快调整情绪，\x01",
"想办法逆转比分吧。\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x13, 27500, -6000, -20000, 0)
SetChrPos(0x11, 24500, -6000, -12000, 180)
SetChrPos(0x10, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0060
ChrTalk(
0x12,
(
"#13000F#5P……比赛结束！！\x02\x03",
"#13009F４比１２，\x01",
"伊莉娅小姐队获胜！！\x02",
)
)
CloseMessageWindow()
#C0061
ChrTalk(
0x101,
"#12506F#6P呼，完败啊……\x02",
)
CloseMessageWindow()
Jump("loc_2E8F")
label("loc_2B08")
OP_2C(0xA5, 0x1)
BeginChrThread(0x101, 3, 1, 66)
WaitChrThread(0x101, 3)
Sound(909, 0, 70, 0)
Sleep(500)
#C0062
ChrTalk(
0x12,
"#13002F#5P#N罗伊德警官队得分！\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x13, 0xA)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x11, 0x8)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
#C0063
ChrTalk(
0x101,
"#12500F#6P好……！\x02",
)
CloseMessageWindow()
#C0064
ChrTalk(
0x10,
(
"#13406F#11P哎呀呀～居然是吊球……\x01",
"本以为他们肯定会选择正面强攻呢。\x02",
)
)
CloseMessageWindow()
#C0065
ChrTalk(
0x11,
"#12806F#11P唉～被对手识破了呢。\x02",
)
CloseMessageWindow()
#C0066
ChrTalk(
0x13,
"#12902F#6P#N呵呵，干得不错嘛。\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
OP_63(0x101, 0x0, 2000, 0x26, 0x26, 0xFA, 0x1)
Sleep(1000)
OP_93(0x101, 0x87, 0x1F4)
#C0067
ChrTalk(
0x101,
(
"#12504F#11P……嗯，因为你对我\x01",
"喊了暗号──『边界』。\x02\x03",
"#12502F我察觉到对方的后场有空位，\x01",
"所以立刻改打吊球了。\x02",
)
)
CloseMessageWindow()
#C0068
ChrTalk(
0x13,
(
"#12904F#6P#N呵呵，突然喊出那种暗号，\x01",
"原本还有些不安，担心你无法领会呢。\x02\x03",
"#12909F这大概就是爱的力量吧？\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
#C0069
ChrTalk(
0x101,
(
"#12506F#11P少说蠢话了。\x02\x03",
"#12500F好，继续用这种战术扰乱\x01",
"伊莉娅小姐他们的视线吧！\x02",
)
)
CloseMessageWindow()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x13, 0x2E)
SetChrSubChip(0x13, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x13, 27500, -6000, -20000, 0)
SetChrPos(0x11, 24500, -6000, -12000, 180)
SetChrPos(0x10, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0070
ChrTalk(
0x12,
(
"#13000F#5P……比赛结束！！\x02\x03",
"#13009F１２比１０，\x01",
"罗伊德警官队获胜！！\x02",
)
)
CloseMessageWindow()
#C0071
ChrTalk(
0x101,
"#12509F#6P好！总算赢了！！\x02",
)
CloseMessageWindow()
label("loc_2E8F")
FadeToDark(1000, 0, -1)
OP_0D()
Return()
# Function_49_2538 end
def Function_50_2E9B(): pass
label("Function_50_2E9B")
ClearChrFlags(0x14, 0x8)
Sound(802, 0, 60, 0)
def lambda_2EAB():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_2EAB)
SetChrChipByIndex(0xFE, 0x2D)
SetChrSubChip(0xFE, 0x0)
Sleep(1000)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
#C0072
ChrTalk(
0x13,
"#6P#5A呼……！\x02",
)
#Auto
def lambda_2EF0():
OP_9D(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFCC0C, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_2EF0)
BeginChrThread(0x10, 3, 1, 51)
Sleep(500)
SetChrChipByIndex(0xFE, 0xA)
SetChrSubChip(0xFE, 0x0)
OP_9B(0x0, 0xFE, 0x0, 0xBB8, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_50_2E9B end
def Function_51_2F31(): pass
label("Function_51_2F31")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_2F44():
OP_9D(0xFE, 0x5FB4, 0xFFFFEDA4, 0xFFFFCD38, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_2F44)
BeginChrThread(0x11, 3, 1, 52)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_51_2F31 end
def Function_52_2F6A(): pass
label("Function_52_2F6A")
SetChrFlags(0xFE, 0x20)
def lambda_2F74():
label("loc_2F74")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_2F74")
QueueWorkItem2(0xFE, 2, lambda_2F74)
Sleep(350)
SetChrChipByIndex(0xFE, 0x25)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
Sound(441, 0, 60, 0)
SetChrSubChip(0xFE, 0x1)
def lambda_2F9F():
OP_9D(0xFE, 0x6B6C, 0xFFFFF448, 0xFFFFC75C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_2F9F)
BeginChrThread(0x10, 3, 1, 53)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sleep(500)
SetChrChipByIndex(0xFE, 0x8)
SetChrSubChip(0xFE, 0x0)
OP_93(0xFE, 0xB4, 0x1F4)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_52_2F6A end
def Function_53_2FEC(): pass
label("Function_53_2FEC")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x35)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_3007():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_3007)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
Sound(442, 0, 80, 0)
EndChrThread(0x14, 0x1)
#C0073
ChrTalk(
0x10,
"#11P#5A接球！\x02",
)
#Auto
def lambda_3047():
OP_96(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFB6F4, 0x3A98, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3047)
BeginChrThread(0x101, 3, 1, 54)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_53_2FEC end
def Function_54_307E(): pass
label("Function_54_307E")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_3091():
OP_9D(0xFE, 0x6B6C, 0xFFFFED40, 0xFFFFB5C8, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3091)
BeginChrThread(0x13, 3, 1, 55)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_54_307E end
def Function_55_30B7(): pass
label("Function_55_30B7")
SetChrFlags(0xFE, 0x20)
def lambda_30C1():
label("loc_30C1")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_30C1")
QueueWorkItem2(0xFE, 2, lambda_30C1)
Sleep(350)
SetChrChipByIndex(0xFE, 0x1C)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
Sound(441, 0, 80, 0)
SetChrSubChip(0xFE, 0x1)
def lambda_30EC():
OP_9D(0xFE, 0x5FB4, 0xFFFFF448, 0xFFFFBBA4, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_30EC)
BeginChrThread(0x101, 3, 1, 56)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_55_30B7 end
def Function_56_311F(): pass
label("Function_56_311F")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x21)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_313A():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFBD98, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_313A)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 80, 0)
#C0074
ChrTalk(
0x101,
"#5P#5A回敬你们……！\x02",
)
#Auto
def lambda_3181():
OP_96(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFCC0C, 0x3A98, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3181)
BeginChrThread(0x11, 3, 1, 57)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_56_311F end
def Function_57_31B8(): pass
label("Function_57_31B8")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_31CB():
OP_9D(0xFE, 0x6B6C, 0xFFFFEC78, 0xFFFFC568, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_31CB)
BeginChrThread(0x10, 3, 1, 58)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_57_31B8 end
def Function_58_31F1(): pass
label("Function_58_31F1")
SetChrFlags(0xFE, 0x20)
def lambda_31FB():
label("loc_31FB")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_31FB")
QueueWorkItem2(0xFE, 2, lambda_31FB)
Sleep(350)
SetChrChipByIndex(0xFE, 0x34)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
Sound(441, 0, 80, 0)
SetChrSubChip(0xFE, 0x1)
def lambda_3226():
OP_9D(0xFE, 0x5FB4, 0xFFFFF448, 0xFFFFC75C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3226)
BeginChrThread(0x11, 3, 1, 59)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Sleep(500)
SetChrChipByIndex(0xFE, 0x3)
SetChrSubChip(0xFE, 0x0)
OP_93(0xFE, 0xB4, 0x1F4)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_58_31F1 end
def Function_59_3273(): pass
label("Function_59_3273")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x26)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_328E():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_328E)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
#C0075
ChrTalk(
0x11,
"#11P#5A看招！\x02",
)
#Auto
def lambda_32C8():
OP_96(0xFE, 0x5FB4, 0xFFFFF254, 0xFFFFBF8C, 0x2EE0, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_32C8)
BeginChrThread(0x101, 3, 1, 60)
Sleep(100)
Sound(442, 0, 100, 0)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_59_3273 end
def Function_60_330B(): pass
label("Function_60_330B")
SetChrChipByIndex(0xFE, 0x22)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
Sound(809, 0, 100, 0)
def lambda_3323():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x1388)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_3323)
WaitChrThread(0x14, 1)
Sound(441, 0, 60, 0)
def lambda_334A():
OP_9D(0xFE, 0x6B6C, 0xFFFFED40, 0xFFFFB5C8, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_334A)
BeginChrThread(0x13, 3, 1, 61)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Sleep(500)
#C0076
ChrTalk(
0x13,
"#6P#5A边界！\x02",
)
#Auto
Sleep(500)
SetChrFlags(0x10, 0x20)
OP_93(0x10, 0xB4, 0x1F4)
ClearChrFlags(0x10, 0x20)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
OP_98(0x10, 0xFFFFFA24, 0x0, 0x0, 0xFA0, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
Return()
# Function_60_330B end
def Function_61_33C6(): pass
label("Function_61_33C6")
SetChrFlags(0xFE, 0x20)
def lambda_33D0():
label("loc_33D0")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_33D0")
QueueWorkItem2(0xFE, 2, lambda_33D0)
Sleep(350)
SetChrChipByIndex(0xFE, 0x1C)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_33FB():
OP_9D(0xFE, 0x5FB4, 0xFFFFF448, 0xFFFFBF8C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_33FB)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x2E)
SetChrSubChip(0xFE, 0x0)
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x1), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
Return()
# Function_61_33C6 end
def Function_62_3432(): pass
label("Function_62_3432")
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x21)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_344A():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFBD98, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_344A)
Sleep(600)
#C0077
ChrTalk(
0x101,
"#5P#5A#4S……呼！#3S\x02",
)
#Auto
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 100, 0)
Sound(547, 0, 40, 0)
OP_82(0x64, 0x0, 0xBB8, 0x96)
PlayEffect(0x0, 0xFF, 0xFE, 0x5, 0, 700, 1000, 0, 0, 0, 1000, 1000, 1000, 0xFF, 0, 0, 0, 0)
def lambda_34DF():
OP_96(0xFE, 0x6590, 0xFFFFF060, 0xFFFFC374, 0x2EE0, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_34DF)
BeginChrThread(0x11, 3, 1, 64)
Sleep(30)
BeginChrThread(0x10, 3, 1, 63)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x10, 3)
Return()
# Function_62_3432 end
def Function_63_3529(): pass
label("Function_63_3529")
SetChrChipByIndex(0xFE, 0x36)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
Sound(809, 0, 100, 0)
def lambda_3541():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x1388)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_3541)
WaitChrThread(0x14, 1)
Sound(441, 0, 80, 0)
BeginChrThread(0x14, 3, 1, 65)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
Return()
# Function_63_3529 end
def Function_64_3585(): pass
label("Function_64_3585")
SetChrChipByIndex(0xFE, 0x27)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x1388)
Sound(809, 0, 100, 0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_64_3585 end
def Function_65_35C3(): pass
label("Function_65_35C3")
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_96(0xFE, 0x6FB8, 0xFFFFE890, 0xFFFFBA00, 0x3A98, 0x0)
Sound(443, 0, 100, 0)
Sound(441, 0, 100, 0)
OP_9D(0xFE, 0x7CC4, 0xFFFFE890, 0xFFFFAB50, 0xBB8, 0x3E8)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
Return()
# Function_65_35C3 end
def Function_66_360B(): pass
label("Function_66_360B")
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x21)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_3623():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFBD98, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_3623)
Sleep(600)
#C0078
ChrTalk(
0x101,
"#6P#5A#4S……嘿！#3S\x02",
)
#Auto
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(441, 0, 100, 0)
BeginChrThread(0x14, 3, 1, 68)
BeginChrThread(0x11, 3, 1, 64)
Sleep(30)
BeginChrThread(0x10, 3, 1, 67)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
Return()
# Function_66_360B end
def Function_67_36A0(): pass
label("Function_67_36A0")
SetChrChipByIndex(0xFE, 0x36)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
Sound(809, 0, 100, 0)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x1388)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x18)
Sound(30, 0, 100, 0)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_67_36A0 end
def Function_68_36DE(): pass
label("Function_68_36DE")
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFD508, 0x7D0, 0x3E8)
Sound(443, 0, 50, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFDAE4, 0x3E8, 0x3E8)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFDECC, 0x1F4, 0x3E8)
Sound(441, 0, 60, 0)
OP_9D(0xFE, 0x639C, 0xFFFFE890, 0xFFFFE0C0, 0xC8, 0x3E8)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
Return()
# Function_68_36DE end
def Function_69_3763(): pass
label("Function_69_3763")
OP_50(0x6C, (scpexpr(EXPR_PUSH_LONG, 0x2), scpexpr(EXPR_ADD_SAVE), scpexpr(EXPR_END)))
SetChrPos(0x101, 24500, -6000, -22000, 0)
SetChrPos(0x10, 27500, -6000, -19000, 0)
SetChrPos(0x11, 24500, -6000, -13000, 180)
SetChrPos(0x12, 27500, -6000, -13000, 180)
SetChrPos(0x13, 21300, -6000, -16000, 90)
SetChrPos(0x14, 24500, -5500, -21800, 0)
SetChrFlags(0x14, 0x8)
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(17000, 0)
OP_68(26000, -5000, -16000, 15000)
MoveCamera(305, 30, 0, 15000)
FadeToBright(1000, 0)
OP_0D()
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
BeginChrThread(0x101, 3, 1, 70)
label("loc_385B")
Jc((scpexpr(EXPR_GET_RESULT, 0x3), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_3872")
Sleep(1)
Jump("loc_385B")
label("loc_3872")
OP_4B(0x14, 0xFF)
RunExpression(0x0, (scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
FadeToDark(300, 0, 100)
OP_0D()
Menu(
0,
-1,
-1,
0,
(
"全力将球托高\x01", # 0
"控制力度托球\x01", # 1
)
)
MenuEnd(0x0)
OP_60(0x0)
FadeToBright(300, 0)
OP_0D()
OP_4C(0x14, 0xFF)
Jc((scpexpr(EXPR_GET_RESULT, 0x0), scpexpr(EXPR_PUSH_LONG, 0x0), scpexpr(EXPR_EQU), scpexpr(EXPR_END)), "loc_3C56")
OP_2C(0xA5, 0x1)
MoveCamera(315, 25, 0, 2000)
SetCameraDistance(15000, 2000)
BeginChrThread(0x101, 3, 1, 81)
WaitChrThread(0x101, 3)
Sound(909, 0, 70, 0)
Sleep(500)
#C0079
ChrTalk(
0x13,
"#12902F#5P#N呵呵，打得漂亮。\x02",
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
SetChrChipByIndex(0x11, 0x8)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x12, 0x9)
SetChrSubChip(0x12, 0x0)
OP_63(0x11, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
OP_63(0x12, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
Sleep(1000)
#C0080
ChrTalk(
0x11,
(
"#12806F真、真不愧是伊莉娅小姐……\x01",
"那种身体能力简直就是犯规啊。\x02",
)
)
CloseMessageWindow()
#C0081
ChrTalk(
0x12,
(
"#13006F在那种惊人的高度扣球……\x01",
"我们根本不可能挡得住呢。\x02",
)
)
CloseMessageWindow()
OP_63(0x10, 0x0, 2000, 0x26, 0x27, 0xFA, 0x2)
Sleep(1200)
#C0082
ChrTalk(
0x10,
"#13409F#6P呵呵，随意一击罢了。\x02",
)
CloseMessageWindow()
OP_93(0x10, 0xE1, 0x1F4)
#C0083
ChrTalk(
0x10,
(
"#13400F#12P警察弟弟的判断很出色呢，\x01",
"竟然把球托得那么高。\x02",
)
)
CloseMessageWindow()
#C0084
ChrTalk(
0x101,
(
"#12500F#5P哈哈，因为我觉得凭伊莉娅小姐\x01",
"的身体能力，肯定能接到那一球。\x02",
)
)
CloseMessageWindow()
#C0085
ChrTalk(
0x10,
(
"#13409F#12P呵呵，聪明聪明¤\x02\x03",
"#13400F好，我们就保持这种势头，\x01",
"一鼓作气结束比赛吧！\x02",
)
)
CloseMessageWindow()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x10, 27500, -6000, -20000, 0)
SetChrPos(0x11, 24500, -6000, -12000, 180)
SetChrPos(0x12, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0086
ChrTalk(
0x13,
(
"#12900F#5P#N……比赛结束！！\x02\x03",
"#12904F１２比４，\x01",
"罗伊德队获胜！！\x01",
"呵呵，辛苦啦。\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
#C0087
ChrTalk(
0x101,
"#12509F#6P好！压倒性完胜！！\x02",
)
CloseMessageWindow()
Jump("loc_3F74")
label("loc_3C56")
MoveCamera(315, 25, 0, 2000)
SetCameraDistance(15000, 2000)
BeginChrThread(0x101, 3, 1, 86)
WaitChrThread(0x101, 3)
Sound(909, 0, 70, 0)
Sleep(500)
#C0088
ChrTalk(
0x13,
(
"#12902F#5P#N呵呵，真遗憾，\x01",
"没能把握住机会呢。\x02",
)
)
CloseMessageWindow()
OP_57(0x0)
OP_5A()
SetChrChipByIndex(0x101, 0xFF)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
SetChrChipByIndex(0x11, 0x8)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x12, 0x9)
SetChrSubChip(0x12, 0x0)
#C0089
ChrTalk(
0x11,
"#12806F呼，好危险……！\x02",
)
CloseMessageWindow()
#C0090
ChrTalk(
0x12,
(
"#13011F不过，弹跳力好惊人啊……\x02\x03",
"#13006F如果真能在那种高度击出扣球，\x01",
"我们肯定接不下。\x02",
)
)
CloseMessageWindow()
OP_63(0x101, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
OP_63(0x10, 0x0, 2000, 0x10, 0x13, 0xFA, 0x1)
Sound(23, 0, 100, 0)
Sleep(1000)
OP_93(0x10, 0xE1, 0x1F4)
#C0091
ChrTalk(
0x10,
"#13406F#12P哎呀呀……抱歉哦，警察弟弟。\x02",
)
CloseMessageWindow()
#C0092
ChrTalk(
0x101,
(
"#12512F哪里，是我的失误……\x01",
"没想到你竟然\x01",
"能跳那么高。\x02",
)
)
CloseMessageWindow()
#C0093
ChrTalk(
0x11,
(
"#12800F哈哈，看来女神\x01",
"站在我们这边呢。\x01",
"一鼓作气取得胜利吧！诺艾尔！\x02",
)
)
CloseMessageWindow()
#C0094
ChrTalk(
0x12,
"#13009F是！\x02",
)
CloseMessageWindow()
FadeToDark(1000, 0, -1)
OP_0D()
Sound(909, 0, 70, 0)
Sleep(500)
SetChrChipByIndex(0x101, 0x1F)
SetChrSubChip(0x101, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
SetChrChipByIndex(0x12, 0x29)
SetChrSubChip(0x12, 0x0)
SetChrPos(0x101, 24500, -6000, -19000, 0)
SetChrPos(0x10, 27500, -6000, -20000, 0)
SetChrPos(0x11, 24500, -6000, -12000, 180)
SetChrPos(0x12, 27500, -6000, -13000, 180)
SetChrFlags(0x14, 0x8)
OP_68(26000, -5000, -16000, 0)
MoveCamera(320, 20, 0, 0)
OP_6E(650, 0)
SetCameraDistance(16000, 0)
SetCameraDistance(17000, 1500)
FadeToBright(1000, 0)
OP_6F(0x79)
OP_0D()
#C0095
ChrTalk(
0x13,
(
"#12900F#5P……比赛结束！！\x02\x03",
"#12904F９比１２，\x01",
"兰迪队获胜。\x01",
"呵呵，辛苦啦。\x02",
)
)
CloseMessageWindow()
#C0096
ChrTalk(
0x101,
"#12506F#6P呜，输了呢……\x02",
)
CloseMessageWindow()
label("loc_3F74")
FadeToDark(1000, 0, -1)
OP_0D()
Return()
# Function_69_3763 end
def Function_70_3F80(): pass
label("Function_70_3F80")
ClearChrFlags(0x14, 0x8)
Sound(802, 0, 60, 0)
def lambda_3F90():
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3F90)
SetChrChipByIndex(0xFE, 0x1E)
SetChrSubChip(0xFE, 0x0)
Sleep(1000)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
#C0097
ChrTalk(
0x101,
"#5P#5A……嘿！\x02",
)
#Auto
def lambda_3FD5():
OP_9D(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFCC70, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_3FD5)
BeginChrThread(0x11, 3, 1, 71)
Sleep(500)
SetChrChipByIndex(0xFE, 0xFF)
SetChrSubChip(0xFE, 0x0)
OP_9B(0x0, 0xFE, 0x0, 0xBB8, 0xFA0, 0x0)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_70_3F80 end
def Function_71_4016(): pass
label("Function_71_4016")
WaitChrThread(0x14, 1)
Sound(441, 0, 100, 0)
SetChrSubChip(0xFE, 0x1)
def lambda_4029():
OP_9D(0xFE, 0x6AA4, 0xFFFFEC78, 0xFFFFCD38, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_4029)
BeginChrThread(0x12, 3, 1, 72)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_71_4016 end
def Function_72_404F(): pass
label("Function_72_404F")
SetChrFlags(0xFE, 0x20)
def lambda_4059():
label("loc_4059")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_4059")
QueueWorkItem2(0xFE, 2, lambda_4059)
Sleep(350)
SetChrChipByIndex(0xFE, 0x15)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
Sound(441, 0, 80, 0)
SetChrSubChip(0xFE, 0x1)
def lambda_4084():
OP_9D(0xFE, 0x5FB4, 0xFFFFF448, 0xFFFFC75C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_4084)
BeginChrThread(0x11, 3, 1, 73)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
OP_93(0xFE, 0xB4, 0x1F4)
OP_9B(0x1, 0x10, 0x0, 0xFFFFFA24, 0xFA0, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
Return()
# Function_72_404F end
def Function_73_40DD(): pass
label("Function_73_40DD")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x26)
SetChrSubChip(0xFE, 0x0)
#C0098
ChrTalk(
0x11,
"#11P#5A速攻！\x02",
)
#Auto
Sound(809, 0, 100, 0)
def lambda_410A():
OP_9D(0xFE, 0x5FB4, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_410A)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
def lambda_4132():
OP_96(0xFE, 0x5FB4, 0xFFFFEA84, 0xFFFFB6F4, 0x4E20, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_4132)
BeginChrThread(0x101, 3, 1, 74)
Sleep(100)
Sound(442, 0, 80, 0)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_73_40DD end
def Function_74_4175(): pass
label("Function_74_4175")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
def lambda_4182():
OP_9D(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFB0B4, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_4182)
BeginChrThread(0x10, 3, 1, 75)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_74_4175 end
def Function_75_41A8(): pass
label("Function_75_41A8")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
#C0099
ChrTalk(
0x10,
"#6P#5A嘿！\x02",
)
#Auto
def lambda_41CA():
OP_9D(0xFE, 0x5FB4, 0xFFFFEC78, 0xFFFFB5C8, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_41CA)
BeginChrThread(0x101, 3, 1, 76)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_75_41A8 end
def Function_76_41F0(): pass
label("Function_76_41F0")
SetChrFlags(0xFE, 0x20)
def lambda_41FA():
label("loc_41FA")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_41FA")
QueueWorkItem2(0xFE, 2, lambda_41FA)
Sleep(350)
SetChrChipByIndex(0xFE, 0x20)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 60, 0)
def lambda_4225():
OP_9D(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFCC0C, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_4225)
BeginChrThread(0x12, 3, 1, 77)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_76_41F0 end
def Function_77_4258(): pass
label("Function_77_4258")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 80, 0)
def lambda_426B():
OP_9D(0xFE, 0x5FB4, 0xFFFFEC78, 0xFFFFC568, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_426B)
BeginChrThread(0x11, 3, 1, 78)
Sleep(500)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_77_4258 end
def Function_78_4291(): pass
label("Function_78_4291")
SetChrFlags(0xFE, 0x20)
def lambda_429B():
label("loc_429B")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_429B")
QueueWorkItem2(0xFE, 2, lambda_429B)
Sleep(350)
SetChrChipByIndex(0xFE, 0x25)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
#C0100
ChrTalk(
0x11,
"#11P#5A上了！\x02",
)
#Auto
def lambda_42D8():
OP_9D(0xFE, 0x6B6C, 0xFFFFF448, 0xFFFFC75C, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_42D8)
BeginChrThread(0x12, 3, 1, 79)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
SetChrChipByIndex(0x10, 0x3)
SetChrSubChip(0x10, 0x0)
OP_9B(0x1, 0x10, 0x0, 0x5DC, 0xFA0, 0x0)
SetChrChipByIndex(0x10, 0x18)
SetChrSubChip(0x10, 0x0)
SetChrFlags(0x11, 0x20)
OP_93(0x11, 0xB4, 0x1F4)
ClearChrFlags(0x11, 0x20)
SetChrChipByIndex(0x11, 0x8)
SetChrSubChip(0x11, 0x0)
OP_98(0x11, 0x5DC, 0x0, 0x0, 0xFA0, 0x0)
SetChrChipByIndex(0x11, 0x17)
SetChrSubChip(0x11, 0x0)
Return()
# Function_78_4291 end
def Function_79_435F(): pass
label("Function_79_435F")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x2B)
SetChrSubChip(0xFE, 0x0)
Sound(809, 0, 100, 0)
def lambda_437A():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFC568, 0x7D0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_437A)
Sleep(600)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
#C0101
ChrTalk(
0x12,
"#11P#5A这招如何！？\x02",
)
#Auto
Sound(442, 0, 80, 0)
def lambda_43C0():
OP_96(0xFE, 0x6B6C, 0xFFFFEA84, 0xFFFFB6F4, 0x4E20, 0x0)
ExitThread()
QueueWorkItem(0x14, 1, lambda_43C0)
BeginChrThread(0x10, 3, 1, 80)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
Return()
# Function_79_435F end
def Function_80_43FD(): pass
label("Function_80_43FD")
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_4410():
OP_9D(0xFE, 0x5FB4, 0xFFFFEC78, 0xFFFFB5C8, 0xBB8, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_4410)
SetChrFlags(0x101, 0x20)
OP_93(0x101, 0x5A, 0x1F4)
ClearChrFlags(0x101, 0x20)
Sleep(300)
SetChrSubChip(0xFE, 0x0)
Sleep(200)
EndChrThread(0x101, 0x2)
RunExpression(0x3, (scpexpr(EXPR_PUSH_LONG, 0x1), scpexpr(EXPR_STUB), scpexpr(EXPR_END)))
Return()
# Function_80_43FD end
def Function_81_4452(): pass
label("Function_81_4452")
#C0102
ChrTalk(
0x101,
"#5P#5A伊莉娅小姐！！\x02",
)
#Auto
SetChrFlags(0xFE, 0x20)
def lambda_4475():
label("loc_4475")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_4475")
QueueWorkItem2(0xFE, 2, lambda_4475)
Sleep(350)
SetChrChipByIndex(0xFE, 0x20)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 100, 0)
def lambda_44A0():
OP_9D(0xFE, 0x6B6C, 0xFFFFF448, 0xFFFFBBA4, 0xCE4, 0x3E8)
ExitThread()
QueueWorkItem(0x14, 1, lambda_44A0)
BeginChrThread(0x10, 3, 1, 82)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x10, 3)
Return()
# Function_81_4452 end
def Function_82_44D7(): pass
label("Function_82_44D7")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x35)
SetChrSubChip(0xFE, 0x0)
#C0103
ChrTalk(
0x10,
"#5P#5A#4S噢啊啊啊啊啊！！#3S\x02",
)
#Auto
Sound(809, 0, 100, 0)
def lambda_4513():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFBD98, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_4513)
Sleep(700)
SetChrSubChip(0xFE, 0x1)
EndChrThread(0x14, 0x1)
Sound(442, 0, 100, 0)
Sound(547, 0, 40, 0)
OP_82(0x64, 0x0, 0xBB8, 0x96)
PlayEffect(0x0, 0xFF, 0xFE, 0x5, 0, 700, 1000, 0, 0, 0, 1000, 1000, 1000, 0xFF, 0, 0, 0, 0)
BeginChrThread(0x14, 3, 1, 85)
BeginChrThread(0x11, 3, 1, 83)
BeginChrThread(0x12, 3, 1, 84)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x14, 3)
WaitChrThread(0x11, 3)
WaitChrThread(0x12, 3)
Return()
# Function_82_44D7 end
def Function_83_45CA(): pass
label("Function_83_45CA")
SetChrChipByIndex(0xFE, 0x27)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x7D0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x17)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_83_45CA end
def Function_84_45FC(): pass
label("Function_84_45FC")
SetChrChipByIndex(0xFE, 0x2C)
SetChrSubChip(0xFE, 0x0)
ClearChrFlags(0xFE, 0x1)
OP_9C(0xFE, 0x0, 0x0, 0x0, 0x5DC, 0x7D0)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x29)
SetChrSubChip(0xFE, 0x0)
Return()
# Function_84_45FC end
def Function_85_462E(): pass
label("Function_85_462E")
SetChrChip(0x0, 0xFE, 0x1E, 0x12C)
OP_96(0xFE, 0x64D2, 0xFFFFE890, 0xFFFFD29C, 0x61A8, 0x0)
Sound(443, 0, 100, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x54A6, 0xFFFFE890, 0x46A, 0x7D0, 0x3E8)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x48DA, 0xFFFFE890, 0x26B6, 0x3E8, 0x3E8)
SetChrChip(0x1, 0xFE, 0x0, 0x0)
Return()
# Function_85_462E end
def Function_86_4693(): pass
label("Function_86_4693")
#C0104
ChrTalk(
0x101,
"#5P#5A伊莉娅小姐！！\x02",
)
#Auto
SetChrFlags(0xFE, 0x20)
def lambda_46B6():
label("loc_46B6")
TurnDirection(0xFE, 0x14, 500)
Yield()
Jump("loc_46B6")
QueueWorkItem2(0xFE, 2, lambda_46B6)
Sleep(350)
SetChrChipByIndex(0xFE, 0x20)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 1)
SetChrSubChip(0xFE, 0x1)
Sound(441, 0, 60, 0)
BeginChrThread(0x14, 3, 1, 88)
BeginChrThread(0x10, 3, 1, 87)
Sleep(500)
EndChrThread(0xFE, 0x2)
ClearChrFlags(0xFE, 0x20)
SetChrChipByIndex(0xFE, 0x1F)
SetChrSubChip(0xFE, 0x0)
WaitChrThread(0x14, 3)
WaitChrThread(0x10, 3)
Return()
# Function_86_4693 end
def Function_87_4705(): pass
label("Function_87_4705")
Sleep(500)
ClearChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x35)
SetChrSubChip(0xFE, 0x0)
#C0105
ChrTalk(
0x10,
"#5P#20A#4S噢啊啊……#3S哎？哎呀！\x02",
)
#Auto
Sound(809, 0, 100, 0)
def lambda_4745():
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFBD98, 0xAF0, 0x3E8)
ExitThread()
QueueWorkItem(0xFE, 1, lambda_4745)
Sleep(700)
SetChrSubChip(0xFE, 0x1)
Sound(590, 0, 100, 0)
BeginChrThread(0x11, 3, 1, 83)
BeginChrThread(0x12, 3, 1, 84)
Sleep(100)
SetChrSubChip(0xFE, 0x2)
Sleep(100)
WaitChrThread(0xFE, 1)
SetChrFlags(0xFE, 0x1)
SetChrChipByIndex(0xFE, 0x18)
SetChrSubChip(0xFE, 0x0)
Sound(30, 0, 100, 0)
WaitChrThread(0x11, 3)
WaitChrThread(0x12, 3)
Return()
# Function_87_4705 end
def Function_88_47A0(): pass
label("Function_88_47A0")
Sound(443, 0, 40, 0)
Sound(441, 0, 80, 0)
OP_9D(0xFE, 0x6B6C, 0xFFFFE890, 0xFFFFBD98, 0x898, 0x3E8)
Sound(441, 0, 60, 0)
OP_9D(0xFE, 0x6F54, 0xFFFFE890, 0xFFFFC091, 0x384, 0x3E8)
Sound(441, 0, 60, 0)
OP_9D(0xFE, 0x717A, 0xFFFFE890, 0xFFFFC1E4, 0x12C, 0x3E8)
Return()
# Function_88_47A0 end
SaveToFile()
Try(main)
|
import nltk
from urllib.request import urlopen
from nltk import word_tokenize
Single_PMID = "24964572"
PMIDs = ["28483577", "24964572", "27283605"]
Pubtator_Info_URL = "https://www.ncbi.nlm.nih.gov/research/pubtator-api/publications/export/pubtator?pmids=24964572"
Pubtator_Info = urlopen(Pubtator_Info_URL, None, timeout=100000)
Title = []
Abstract = []
Bioconcept_Gene = []
Bioconcept_Disease = []
Bioconcept_Chemical = []
Bioconcept_Mutation = []
Bioconcept_Species = []
Bioconcept_Cellline = []
while True:
Info_line = Pubtator_Info.readline()
if not Info_line: break
#Abstract tokenization
if str(Info_line).__contains__("|a|"):
print(Info_line)
Abstract = str(Info_line).replace('\\n','').\
replace(str(Single_PMID),"").\
replace("|a|","").lower().\
replace('b"','').\
replace('"','').\
split(".")
print(Abstract)
#Abstract를 tokenization 진행
#tokens = word_tokenize(str(Abstract))
#print(tokens)
#text = nltk.Text(tokens)
#text.concordance("Garlic", 100, 100)
print("\n")
print("\n")
# 두 키워드를 포함하는 sentence 추출
for info in Abstract:
if str(info).__contains__(str("garlic").lower()) and str(info).__contains__(str("cancer").lower()):
#print("Extraction")
#print(str(info).strip())
Data = str(info).strip()
print(Data)
data_tokens = word_tokenize(str(Data))
print(data_tokens)
inter_data_token = data_tokens[int(data_tokens.index('garlic'))+1:int(data_tokens.index('cancer'))-1]
#Tokenization 진행 후 관련된 단어를 포함하는지에 대한 여부로 두 keyword 사이의 연관성을 비교 분석
key = "treatment"
for inter_data in inter_data_token:
print(inter_data)
if str(inter_data) == str(key):
correlation = True
elif str(inter_data) == str(key):
correlation = False
print(correlation)
"""
#Bioconcept filtering (Gene, Disease, Chemical, Mutation, Species, Celline)
#if str(Info_line).__contains__("Species"):
# print(str(Info_line))
""" |
if 'c' in 'Python':
print 'YES'
else:
print 'NO'
#http://www.hacksparrow.com/python-check-if-a-character-or-substring-is-in-a-string.html |
# -*- coding: utf-8 -*-
# cython: language_level=3, always_allow_keywords=True
## Copyright 2007-2018 by LivingLogic AG, Bayreuth/Germany
## Copyright 2007-2018 by Walter Dörwald
##
## All Rights Reserved
##
## See ll/xist/__init__.py for the license
"""
This namespace module implements Atom 1.0 as specified by :rfc:`4287`.
"""
from ll.xist import xsc, sims
from ll.xist.ns import html
__docformat__ = "reStructuredText"
xmlns = "http://www.w3.org/2005/Atom"
class feed(xsc.Element):
"""
The :class:`feed` element is the document (i.e., top-level) element of an
Atom Feed Document, acting as a container for metadata and data associated
with the feed.
"""
xmlns = xmlns
class entry(xsc.Element):
"""
The :class:`entry` element represents an individual entry, acting as a
container for metadata and data associated with the entry.
"""
xmlns = xmlns
class content(xsc.Element):
"""
The :class:`content` element either contains or links to the content of
the :class:`entry`.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class type(xsc.TextAttr): pass
class src(xsc.URLAttr): pass
class author(xsc.Element):
"""
The :class:`author` element indicates the author of the
:class:`entry` or :class:`feed`.
"""
xmlns = xmlns
class category(xsc.Element):
"""
The :class:`category` element conveys information about a category
associated with an :class:`entry` or :class:`feed`.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class term(xsc.TextAttr): required = True
class scheme(xsc.URLAttr): pass
class label(xsc.TextAttr): pass
class contributor(xsc.Element):
"""
The :class:`contributor` element indicates a person or other entity
who contributed :class:`entry` or :class:`feed`.
"""
xmlns = xmlns
class generator(xsc.Element):
"""
The :class:`generator` element's content identifies the agent used to
generate a feed, for debugging and other purposes.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class uri(xsc.URLAttr): pass
class version(xsc.TextAttr): pass
class icon(xsc.Element):
"""
The :class:`icon` element's content is an IRI reference that identifies
an image that provides iconic visual identification for a feed.
"""
xmlns = xmlns
class id(xsc.Element):
"""
The :class:`id` element conveys a permanent, universally unique identifier
for an :class:`entry` or :class:`feed`.
"""
xmlns = xmlns
class link(xsc.Element):
"""
The :class:`link` element defines a reference from an
:class:`entry` or :class:`feed` to a Web resource.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class href(xsc.URLAttr): required = True
class rel(xsc.TextAttr): pass
class type(xsc.TextAttr): pass
class hreflang(xsc.TextAttr): pass
class title(xsc.TextAttr): pass
class length(xsc.TextAttr): pass
class logo(xsc.Element):
"""
The :class:`logo` element's content is an IRI reference that identifies
an image that provides visual identification for a :class:`feed`.
"""
xmlns = xmlns
class published(xsc.Element):
"""
The :class:`published` element indicatesg an instant in time associated
with an event early in the life cycle of the :class:`entry`.
"""
xmlns = xmlns
class rights(xsc.Element):
"""
The :class:`rights` element contains text that conveys information about
rights held in and over an :class:`entry` or :class:`feed`.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class type(xsc.TextAttr): pass
class source(xsc.Element):
"""
If an :class:`entry` is copied from one :class:`feed` into another
:class:`feed`, then the source :class:`feed`'s metadata (all child elements
of :class:`feed` other than the :class:`entry` elements) may be preserved
within the copied entry by adding a :class:`source` child element, if it is
not already present in the :class:`entry`, and including some or all of the
source :class:`feed`'s Metadata elements as the :class:`source` element's
children.
"""
xmlns = xmlns
class subtitle(xsc.Element):
"""
The :class:`subtitle` element contains text that conveys a human-readable
description or subtitle for a :class:`feed`.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class type(xsc.TextAttr): pass
class summary(xsc.Element):
"""
The :class:`summary` element contains text that conveys a short summary,
abstract, or excerpt of an entry.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class type(xsc.TextAttr): pass
class title(xsc.Element):
"""
The :class:`title` element contains text that conveys a human-readable
title for an :class:`entry` or :class:`feed`.
"""
xmlns = xmlns
class Attrs(xsc.Element.Attrs):
class type(xsc.TextAttr): pass
class updated(xsc.Element):
"""
The :class:`updated` element contains a date indicating the most recent
instant in time when an :class:`entry` or :class:`feed` was modified in a
way the publisher considers significant.
"""
xmlns = xmlns
class email(xsc.Element):
"""
The :class:`email` element's content conveys an e-mail address associated
with the person.
"""
xmlns = xmlns
class uri(xsc.Element):
"""
The :class:`uri` element's content conveys an IRI associated with the person.
"""
xmlns = xmlns
class name(xsc.Element):
"""
The :class:`name` element's content conveys a human-readable name for the
person.
"""
xmlns = xmlns
link.model = \
category.model = sims.Empty()
content.model = sims.ElementsOrText(html.div)
source.model = sims.ElementsOrText(author, category, contributor, generator, icon, id, link, logo, rights, subtitle, title, updated)
feed.model = sims.Elements(author, category, contributor, generator, icon, logo, id, link, rights, subtitle, title, updated, entry)
entry.model = sims.Elements(author, category, content, contributor, id, link, published, rights, source, summary, title, updated)
contributor.model = \
author.model = sims.Elements(name, uri, email)
title.model = \
summary.model = \
subtitle.model = \
rights.model = sims.ElementsOrText(html.div)
updated.model = \
published.model = \
logo.model = \
id.model = \
icon.model = \
generator.model = \
email.model = \
uri.model = \
name.model = sims.NoElements()
|
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