Datasets:

ytzi

/

the-stack-dedup-python-scored-filtered

like 0

ed4a2840446404d2f282a8452d7b98f961fd5554

py

Python

hi-ml-histopathology/src/histopathology/preprocessing/tiling.py

kumar-pratik/hi-ml

a108cf4ea244a76127adedc0ca60f0a5afdfb3e8

2020-09-22T16:38:16.000Z

2022-03-30T09:56:03.000Z

hi-ml-histopathology/src/histopathology/preprocessing/tiling.py

kumar-pratik/hi-ml

a108cf4ea244a76127adedc0ca60f0a5afdfb3e8

2020-09-23T09:32:33.000Z

2022-03-30T18:15:01.000Z

hi-ml-histopathology/src/histopathology/preprocessing/tiling.py

kumar-pratik/hi-ml

a108cf4ea244a76127adedc0ca60f0a5afdfb3e8

2020-09-23T00:12:58.000Z

2022-03-31T07:39:55.000Z

# ------------------------------------------------------------------------------------------ # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License (MIT). See LICENSE in the repo root for license information. # ------------------------------------------------------------------------------------------ # These tiling implementations are adapted from PANDA Kaggle solutions, for example: # https://github.com/kentaroy47/Kaggle-PANDA-1st-place-solution/blob/master/src/data_process/a00_save_tiles.py from typing import Any, Optional, Tuple import numpy as np def get_1d_padding(length: int, tile_size: int) -> Tuple[int, int]: """Computes symmetric padding for `length` to be divisible by `tile_size`.""" pad = (tile_size - length % tile_size) % tile_size return (pad // 2, pad - pad // 2) def pad_for_tiling_2d(array: np.ndarray, tile_size: int, channels_first: Optional[bool] = True, **pad_kwargs: Any) -> Tuple[np.ndarray, np.ndarray]: """Symmetrically pads a 2D `array` such that both dimensions are divisible by `tile_size`. :param array: 2D image array. :param tile_size: Width/height of each tile in pixels. :param channels_first: Whether `array` is in CHW (`True`, default) or HWC (`False`) layout. :param pad_kwargs: Keyword arguments to be passed to `np.pad()` (e.g. `constant_values=0`). :return: A tuple containing: - `padded_array`: Resulting array, in the same CHW/HWC layout as the input. - `offset`: XY offset introduced by the padding. Add this to coordinates relative to the original array to obtain indices for the padded array. """ height, width = array.shape[1:] if channels_first else array.shape[:-1] padding_h = get_1d_padding(height, tile_size) padding_w = get_1d_padding(width, tile_size) padding = [padding_h, padding_w] channels_axis = 0 if channels_first else 2 padding.insert(channels_axis, (0, 0)) # zero padding on channels axis padded_array = np.pad(array, padding, **pad_kwargs) offset = (padding_w[0], padding_h[0]) return padded_array, np.array(offset) def tile_array_2d(array: np.ndarray, tile_size: int, channels_first: Optional[bool] = True, **pad_kwargs: Any) -> Tuple[np.ndarray, np.ndarray]: """Split an image array into square non-overlapping tiles. The array will be padded symmetrically if its dimensions are not exact multiples of `tile_size`. :param array: Image array. :param tile_size: Width/height of each tile in pixels. :param pad_kwargs: Keyword arguments to be passed to `np.pad()` (e.g. `constant_values=0`). :param channels_first: Whether `array` is in CHW (`True`, default) or HWC (`False`) layout. :return: A tuple containing: - `tiles`: A batch of tiles in NCHW layout. - `coords`: XY coordinates of each tile, in the same order. """ padded_array, (offset_w, offset_h) = pad_for_tiling_2d(array, tile_size, channels_first, **pad_kwargs) if channels_first: channels, height, width = padded_array.shape else: height, width, channels = padded_array.shape n_tiles_h = height // tile_size n_tiles_w = width // tile_size if channels_first: intermediate_shape = (channels, n_tiles_h, tile_size, n_tiles_w, tile_size) axis_order = (1, 3, 0, 2, 4) # (n_tiles_h, n_tiles_w, channels, tile_size, tile_size) output_shape = (n_tiles_h * n_tiles_w, channels, tile_size, tile_size) else: intermediate_shape = (n_tiles_h, tile_size, n_tiles_w, tile_size, channels) axis_order = (0, 2, 1, 3, 4) # (n_tiles_h, n_tiles_w, tile_size, tile_size, channels) output_shape = (n_tiles_h * n_tiles_w, tile_size, tile_size, channels) tiles = padded_array.reshape(intermediate_shape) # Split width and height axes tiles = tiles.transpose(axis_order) tiles = tiles.reshape(output_shape) # Flatten tile batch dimension # Compute top-left coordinates of every tile, relative to the original array's origin coords_h = tile_size * np.arange(n_tiles_h) - offset_h coords_w = tile_size * np.arange(n_tiles_w) - offset_w # Shape: (n_tiles_h * n_tiles_w, 2) coords = np.stack(np.meshgrid(coords_w, coords_h), axis=-1).reshape(-1, 2) return tiles, coords def assemble_tiles_2d(tiles: np.ndarray, coords: np.ndarray, fill_value: Optional[float] = np.nan, channels_first: Optional[bool] = True) -> Tuple[np.ndarray, np.ndarray]: """Assembles a 2D array from sequences of tiles and coordinates. :param tiles: Stack of tiles with batch dimension first. :param coords: XY tile coordinates, assumed to be spaced by multiples of `tile_size` (shape: [N, 2]). :param tile_size: Size of each tile; must be >0. :param fill_value: Value to assign to empty elements (default: `NaN`). :param channels_first: Whether each tile is in CHW (`True`, default) or HWC (`False`) layout. :return: A tuple containing: - `array`: The reassembled 2D array with the smallest dimensions to contain all given tiles. - `offset`: The lowest XY coordinates. - `offset`: XY offset introduced by the assembly. Add this to tile coordinates to obtain indices for the assembled array. """ if coords.shape[0] != tiles.shape[0]: raise ValueError(f"Tile coordinates and values must have the same length, " f"got {coords.shape[0]} and {tiles.shape[0]}") if channels_first: n_tiles, channels, tile_size, _ = tiles.shape else: n_tiles, tile_size, _, channels = tiles.shape tile_xs, tile_ys = coords.T x_min, x_max = min(tile_xs), max(tile_xs + tile_size) y_min, y_max = min(tile_ys), max(tile_ys + tile_size) width = x_max - x_min height = y_max - y_min output_shape = (channels, height, width) if channels_first else (height, width, channels) array = np.full(output_shape, fill_value) offset = np.array([-x_min, -y_min]) for idx in range(n_tiles): row = coords[idx, 1] + offset[1] col = coords[idx, 0] + offset[0] if channels_first: array[:, row:row + tile_size, col:col + tile_size] = tiles[idx] else: array[row:row + tile_size, col:col + tile_size, :] = tiles[idx] return array, offset

ed4d3cea76d6d1815b54c52a975d47ddfb5f8c99

py

Python

server/djangoapp/restapis.py

christiansencq/ibm_capstone

d445fd40c0267be0948a5d85e9d43828b908641c

server/djangoapp/restapis.py

christiansencq/ibm_capstone

d445fd40c0267be0948a5d85e9d43828b908641c

server/djangoapp/restapis.py

christiansencq/ibm_capstone

d445fd40c0267be0948a5d85e9d43828b908641c

import requests import json # import related models here from .models import CarDealer, DealerReview from requests.auth import HTTPBasicAuth import logging logger = logging.getLogger(__name__) # Create a `get_request` to make HTTP GET requests # e.g., response = requests.get(url, params=params, headers={'Content-Type': 'application/json'}, # auth=HTTPBasicAuth('apikey', api_key)) def get_request(url, api_key, **kwargs): print("GET from {}".format(url)) print(kwargs) try: if api_key is not None: response = requests.get(url, headers={'Content-Type': 'application/json'}, params=kwargs, auth=HTTPBasicAuth('apikey', api_key)) else: response = requests.get(url, headers={'Content-Type': 'application/json'}, params=kwargs) except: print("Network Error") status_code = response.status_code print("With status code {}".format(status_code)) json_data = json.loads(response.text) return json_data, status_code # Create a `post_request` to make HTTP POST requests # e.g., response = requests.post(url, params=kwargs, json=payload) def post_request(url, json_payload, **kwargs): print("Post to url: {} ".format(url)) print(kwargs) print(json_payload) response = requests.post(url, headers={'Content-Type': 'application/json'}, params=kwargs, json=json_payload) status_code = response.status_code print("With status code {}".format(status_code)) json_data = json.loads(response.text) return json_data, status_code # Create a get_dealers_from_cf method to get dealers from a cloud function def get_dealers_from_cf(url, **kwargs): info = [] result = "ok" # - Call get_request() with specified arguments logger.info("Get Dealers from CF Called!") json_result, status_code = get_request(url, None) if status_code == 200 and json_result: dealers = json_result['rows'] logger.info(len(dealers)) for dealer in dealers: dlr_data = dealer['doc'] #print('ADDRESS', dlr_data["address"]) if dlr_data.get('address'): # Create a CarDealer object with values in `doc` object dealer_obj = CarDealer(address=dlr_data.get("address"), city=dlr_data.get("city"), full_name=dlr_data.get("full_name"), id=dlr_data.get("id"), lat=dlr_data.get("lat"), long=dlr_data.get("long"), short_name=dlr_data.get("short_name"), state=dlr_data.get("state"), st=dlr_data.get("st"), zip=dlr_data.get("zip")) # dealer_obj = CarDealer(address=dealer["doc"]["address"], city=dealer["doc"]["city"], full_name=dealer["doc"]["full_name"], # id=dealer["doc"]["id"], lat=dealer["doc"]["lat"], long=dealer["doc"]["long"], # short_name=dealer["doc"]["short_name"], # st=dealer["doc"]["st"], state=dealer["doc"]["state"], zip=dealer["doc"]["zip"]) info.append(dealer_obj) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result def get_dealer_by_id(url, dealerId): # Call get_request with a URL parameter info = None result = "ok" json_result, status_code = get_request(url, None, dealerId=dealerId) # json_result, status_code = get_request(url, None, dealerId=dealerId) if status_code == 200 and json_result: # Get the row list in JSON as dealers dealers = json_result["rows"] for dealer in dealers: # Create a CarDealer object with values in `doc` object info = CarDealer(address=dealer.get("address"), city=dealer.get("city"), full_name=dealer.get("full_name"), id=dealer.get("id"), lat=dealer.get("lat"), long=dealer.get("long"), short_name=dealer.get("short_name"), st=dealer.get("st"), state=dealer.get("state"), zip=dealer.get("zip")) # info = CarDealer(address=dealer["address"], city=dealer["city"], full_name=dealer["full_name"], # id=dealer["id"], lat=dealer["lat"], long=dealer["long"], # short_name=dealer["short_name"], state=dealer["state"], # st=dealer["st"], zip=dealer["zip"]) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result def get_dealers_by_state (url, state): info = [] result = "ok" # Call get_request with a URL parameter json_result, status_code = get_request(url, None, state=state) if status_code == 200 and json_result: # Get the row list in JSON as dealers dealers = json_result["rows"] # For each dealer object for dealer in dealers: # dlr_data = dealer["doc"] # Create a CarDealer object with values in `doc` object dealer_obj = CarDealer(address=dealer.get("address"), city=dealer.get("city"), full_name=dealer.get("full_name"), id=dealer.get("id"), lat=dealer.get("lat"), long=dealer.get("long"), short_name=dealer.get("short_name"), state=dealer.get("state"), st=dealer.get("st"), zip=dealer.get("zip")) # dealer_obj = CarDealer(address=dlr_data.get("address"), city=dlr_data.get("city"), full_name=dlr_data.get("full_name"), # id=dlr_data.get("id"), lat=dlr_data.get("lat"), long=dlr_data.get("long"), # short_name=dlr_data.get("short_name"), state=dlr_data.get("state"), # st=dlr_data.get("st"), zip=dlr_data.get("zip")) info.append(dealer_obj) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result def get_dealer_reviews_from_cf (url, dealerId): info = [] result = "ok" # Call get_request with a URL parameter json_result, status_code = get_request(url, None, dealerId=dealerId) if status_code == 200 and json_result: # Get the row list in JSON as reviews reviews = json_result["body"]["data"] # For each review object for review in reviews: if (dealerId == review.get("dealership")): # Create a DealerReview object with values in object #sentiment = analyze_review_sentiments(review["review"]) review_obj = DealerReview( id=review.get("id"), name=review.get("name"), review=review.get("review"), purchase=review.get("purchase"), car_make=review.get("car_make", None), car_model=review.get("car_model", None), car_year=review.get("car_year", None), purchase_date=review.get("purchase_date", None)) info.append(review_obj) elif json_result: result = json_result["message"] else: result = "Unknown error" return info, result # Create an `analyze_review_sentiments` method to call Watson NLU and analyze text # def analyze_review_sentiments(text): # - Call get_request() with specified arguments # - Get the returned sentiment label such as Positive or Negative

ed4d8f444cbb7eba10514b86dbcd28fb80cd5824

py

Python

examples/python/upload.py

oslokommune/okdata-data-uploader

fc006ae90440b267613260bba90235799bf0cf6e

examples/python/upload.py

oslokommune/okdata-data-uploader

fc006ae90440b267613260bba90235799bf0cf6e

examples/python/upload.py

oslokommune/okdata-data-uploader

fc006ae90440b267613260bba90235799bf0cf6e

import logging from configparser import ConfigParser from sdk.data_uploader import DataUploader logging.basicConfig(level=logging.INFO) log = logging.getLogger() config = ConfigParser() config.read("config.ini") ##### # Datasets to be added to metadata API datasetData = { "title": "Test", "description": "Test data", "keywords": ["test"], "accessRights": "non-public", "objective": "Formålsbeskrivelse", "contactPoint": { "name": "Tim", "email": "tim@example.org", "phone": "12345678", }, "publisher": "Tim", } datasetVersionData = {"version": "6", "schema": {}, "transformation": {}} datasetVersionEditionData = { "edition": "2019-05-28T15:37:00+02:00", "description": "Data for one hour", "startTime": "2018-12-21T08:00:00+01:00", "endTime": "2018-12-21T09:00:00+01:00", } ###### # The dataset* variables are optional, if these are set in config.ini this script will # not run the relevant DataUploader function datasetId = config.get("dataUploader", "datasetId", fallback=None) datasetVersion = config.get("dataUploader", "datasetVersion", fallback=None) datasetVersionEdition = config.get( "dataUploader", "datasetVersionEdition", fallback=None ) upload = DataUploader(config) try: log.info("Uploading a file to S3") upload.login() if datasetId is None: upload.createDataset(datasetData) if datasetVersion is None: upload.createVersion(datasetVersionData) if datasetVersionEdition is None: upload.createEdition(datasetVersionEditionData) log.info(f"Dataset: {upload.datasetId}") log.info(f"Version: {upload.datasetVersion}") log.info(f"Edition: {upload.datasetVersionEdition}") if upload.upload("README.md"): log.info("Done... go brew some coffee") else: log.error("Could not upload file....") except Exception as e: log.exception(f">> Something went horrible wrong:\n{e}") # To upload with curl: cmd = upload.curl("tmp3.zip") # Max upload size for now is 5GB

ed4da4c3e62ea1a20080eade8fbb9743d55cdd88

py

Python

doc/examples.py

Enerccio/mahjong

903505a7886c31845dfa6b3f54c936a4feb29e6e

2017-09-20T15:02:20.000Z

2022-03-28T11:33:28.000Z

doc/examples.py

Enerccio/mahjong

903505a7886c31845dfa6b3f54c936a4feb29e6e

2017-09-23T14:28:36.000Z

2022-01-06T08:41:57.000Z

doc/examples.py

Enerccio/mahjong

903505a7886c31845dfa6b3f54c936a4feb29e6e

2017-10-19T09:06:53.000Z

2022-03-15T05:08:22.000Z

from mahjong.hand_calculating.hand import HandCalculator from mahjong.meld import Meld from mahjong.hand_calculating.hand_config import HandConfig, OptionalRules from mahjong.shanten import Shanten from mahjong.tile import TilesConverter calculator = HandCalculator() # useful helper def print_hand_result(hand_result): print(hand_result.han, hand_result.fu) print(hand_result.cost['main']) print(hand_result.yaku) for fu_item in hand_result.fu_details: print(fu_item) print('') #################################################################### # Tanyao hand by ron # #################################################################### # we had to use all 14 tiles in that array tiles = TilesConverter.string_to_136_array(man='22444', pin='333567', sou='444') win_tile = TilesConverter.string_to_136_array(sou='4')[0] result = calculator.estimate_hand_value(tiles, win_tile) print_hand_result(result) #################################################################### # Tanyao hand by tsumo # #################################################################### result = calculator.estimate_hand_value(tiles, win_tile, config=HandConfig(is_tsumo=True)) print_hand_result(result) #################################################################### # Add open set to hand # #################################################################### melds = [Meld(meld_type=Meld.PON, tiles=TilesConverter.string_to_136_array(man='444'))] result = calculator.estimate_hand_value(tiles, win_tile, melds=melds, config=HandConfig(options=OptionalRules(has_open_tanyao=True))) print_hand_result(result) #################################################################### # Shanten calculation # #################################################################### shanten = Shanten() tiles = TilesConverter.string_to_34_array(man='13569', pin='123459', sou='443') result = shanten.calculate_shanten(tiles) print(result) #################################################################### # Kazoe as a sanbaiman # #################################################################### tiles = TilesConverter.string_to_136_array(man='22244466677788') win_tile = TilesConverter.string_to_136_array(man='7')[0] melds = [ Meld(Meld.KAN, TilesConverter.string_to_136_array(man='2222'), False) ] dora_indicators = [ TilesConverter.string_to_136_array(man='1')[0], TilesConverter.string_to_136_array(man='1')[0], TilesConverter.string_to_136_array(man='1')[0], TilesConverter.string_to_136_array(man='1')[0], ] config = HandConfig(is_riichi=True, options=OptionalRules(kazoe=HandConfig.KAZOE_SANBAIMAN)) result = calculator.estimate_hand_value(tiles, win_tile, melds, dora_indicators, config) print_hand_result(result) #################################################################### # Change the cost of yaku # #################################################################### config = HandConfig(is_renhou=True) # renhou as an yakuman - old style config.yaku.renhou.han_closed = 13 tiles = TilesConverter.string_to_136_array(man='22444', pin='333567', sou='444') win_tile = TilesConverter.string_to_136_array(sou='4')[0] result = calculator.estimate_hand_value(tiles, win_tile, config=config) print_hand_result(result)

ed57f1712b86394159992dc11fd79688181d493e

bzl

Python

tensorflow_probability/python/build_defs.bzl

jbergmanster/probability

e15b307066e7485b8fe9faf3d289c739ab8d3806

tensorflow_probability/python/build_defs.bzl

jbergmanster/probability

e15b307066e7485b8fe9faf3d289c739ab8d3806

tensorflow_probability/python/build_defs.bzl

jbergmanster/probability

e15b307066e7485b8fe9faf3d289c739ab8d3806

# Copyright 2019 The TensorFlow Probability Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ """Build defs for TF/NumPy/JAX-variadic libraries & tests.""" # [internal] load python3.bzl NO_REWRITE_NEEDED = [ "internal:all_util", "internal:docstring_util", "internal:reparameterization", "layers", "platform_google", ] REWRITER_TARGET = "//tensorflow_probability/substrates/meta:rewrite" RUNFILES_ROOT = "tensorflow_probability/" def _substrate_src(src, substrate): """Rewrite a single src filename for the given substrate.""" return "_{}/_generated_{}".format(substrate, src) def _substrate_srcs(srcs, substrate): """Rewrite src filenames for the given substrate.""" return [_substrate_src(src, substrate) for src in srcs] def _substrate_dep(dep, substrate): """Convert a single dep to one appropriate for the given substrate.""" dep_to_check = dep if dep.startswith(":"): dep_to_check = "{}{}".format(native.package_name(), dep) for no_rewrite in NO_REWRITE_NEEDED: if no_rewrite in dep_to_check: return dep if "tensorflow_probability/" in dep or dep.startswith(":"): if "internal/backend" in dep: return dep if ":" in dep: return "{}.{}".format(dep, substrate) return "{}:{}.{}".format(dep, dep.split("/")[-1], substrate) return dep def _substrate_deps(deps, substrate): """Convert deps to those appropriate for the given substrate.""" new_deps = [_substrate_dep(dep, substrate) for dep in deps] backend_dep = "//tensorflow_probability/python/internal/backend/{}".format(substrate) if backend_dep not in new_deps: new_deps.append(backend_dep) return new_deps # This is needed for the transitional period during which we have the internal # py2and3_test and py_test comingling in BUILD files. Otherwise the OSS export # rewrite process becomes irreversible. def py3_test(*args, **kwargs): """Internal/external reversibility, denotes py3-only vs py2+3 tests. Args: *args: Passed to underlying py_test. **kwargs: Passed to underlying py_test. srcs_version and python_version are added (with value `"PY3"`) if not specified. """ kwargs = dict(kwargs) if "srcs_version" not in kwargs: kwargs["srcs_version"] = "PY3" if "python_version" not in kwargs: kwargs["python_version"] = "PY3" native.py_test(*args, **kwargs) def _resolve_omit_dep(dep): """Resolves a `substrates_omit_deps` item to full target.""" if ":" not in dep: dep = "{}:{}".format(dep, dep.split("/")[-1]) if dep.startswith(":"): dep = "{}{}".format(native.package_name(), dep) return dep def _substrate_runfiles_symlinks_impl(ctx): """A custom BUILD rule to generate python runfiles symlinks. A custom build rule which adds runfiles symlinks for files matching a substrate genrule file pattern, i.e. `'_jax/_generated_normal.py'`. This rule will aggregate and pass along deps while adding the given symlinks to the runfiles structure. Build rule attributes: - substrate: One of 'jax' or 'numpy'; which substrate this applies to. - deps: A list of py_library labels. These are passed along. Args: ctx: Rule analysis context. Returns: Info objects to propagate deps and add runfiles symlinks. """ # Aggregate the depset inputs to resolve transitive dependencies. transitive_sources = [] uses_shared_libraries = [] imports = [] has_py2_only_sources = [] has_py3_only_sources = [] cc_infos = [] for dep in ctx.attr.deps: if PyInfo in dep: transitive_sources.append(dep[PyInfo].transitive_sources) uses_shared_libraries.append(dep[PyInfo].uses_shared_libraries) imports.append(dep[PyInfo].imports) has_py2_only_sources.append(dep[PyInfo].has_py2_only_sources) has_py3_only_sources.append(dep[PyInfo].has_py3_only_sources) # if PyCcLinkParamsProvider in dep: # DisableOnExport # cc_infos.append(dep[PyCcLinkParamsProvider].cc_info) # DisableOnExport if CcInfo in dep: cc_infos.append(dep[CcInfo]) # Determine the set of symlinks to generate. transitive_sources = depset(transitive = transitive_sources) runfiles_dict = {} substrate = ctx.attr.substrate file_substr = "_{}/_generated_".format(substrate) for f in transitive_sources.to_list(): if "tensorflow_probability" in f.dirname and file_substr in f.short_path: pre, post = f.short_path.split("/python/") out_path = "{}/substrates/{}/{}".format( pre, substrate, post.replace(file_substr, ""), ) runfiles_dict[RUNFILES_ROOT + out_path] = f # Construct the output structures to pass along Python srcs/deps/etc. py_info = PyInfo( transitive_sources = transitive_sources, uses_shared_libraries = any(uses_shared_libraries), imports = depset(transitive = imports), has_py2_only_sources = any(has_py2_only_sources), has_py3_only_sources = any(has_py3_only_sources), ) py_cc_link_info = cc_common.merge_cc_infos(cc_infos = cc_infos) py_runfiles = depset( transitive = [depset(transitive = [ dep[DefaultInfo].data_runfiles.files, dep[DefaultInfo].default_runfiles.files, ]) for dep in ctx.attr.deps], ) runfiles = DefaultInfo(runfiles = ctx.runfiles( transitive_files = py_runfiles, root_symlinks = runfiles_dict, )) return py_info, py_cc_link_info, runfiles # See documentation at: # https://docs.bazel.build/versions/3.4.0/skylark/rules.html substrate_runfiles_symlinks = rule( implementation = _substrate_runfiles_symlinks_impl, attrs = { "substrate": attr.string(), "deps": attr.label_list(), }, ) def multi_substrate_py_library( name, srcs = [], deps = [], substrates_omit_deps = [], jax_omit_deps = [], numpy_omit_deps = [], testonly = 0, srcs_version = "PY2AND3"): """A TFP `py_library` for each of TF, NumPy, and JAX. Args: name: The TF `py_library` name. NumPy and JAX libraries have '.numpy' and '.jax' appended. srcs: As with `py_library`. A `genrule` is used to rewrite srcs for NumPy and JAX substrates. deps: As with `py_library`. The list is rewritten to depend on substrate-specific libraries for substrate variants. substrates_omit_deps: List of deps to omit if those libraries are not rewritten for the substrates. jax_omit_deps: List of deps to omit for the JAX substrate. numpy_omit_deps: List of deps to omit for the NumPy substrate. testonly: As with `py_library`. srcs_version: As with `py_library`. """ native.py_library( name = name, srcs = srcs, deps = deps, srcs_version = srcs_version, testonly = testonly, ) remove_deps = [ "//third_party/py/tensorflow", "//third_party/py/tensorflow:tensorflow", ] trimmed_deps = [dep for dep in deps if (dep not in substrates_omit_deps and dep not in remove_deps)] resolved_omit_deps_numpy = [ _resolve_omit_dep(dep) for dep in substrates_omit_deps + numpy_omit_deps ] for src in srcs: native.genrule( name = "rewrite_{}_numpy".format(src.replace(".", "_")), srcs = [src], outs = [_substrate_src(src, "numpy")], cmd = "$(location {}) $(SRCS) --omit_deps={} > $@".format( REWRITER_TARGET, ",".join(resolved_omit_deps_numpy), ), tools = [REWRITER_TARGET], ) native.py_library( name = "{}.numpy.raw".format(name), srcs = _substrate_srcs(srcs, "numpy"), deps = _substrate_deps(trimmed_deps, "numpy"), srcs_version = srcs_version, testonly = testonly, ) # Add symlinks under tfp/substrates/numpy. substrate_runfiles_symlinks( name = "{}.numpy".format(name), substrate = "numpy", deps = [":{}.numpy.raw".format(name)], testonly = testonly, ) resolved_omit_deps_jax = [ _resolve_omit_dep(dep) for dep in substrates_omit_deps + jax_omit_deps ] jax_srcs = _substrate_srcs(srcs, "jax") for src in srcs: native.genrule( name = "rewrite_{}_jax".format(src.replace(".", "_")), srcs = [src], outs = [_substrate_src(src, "jax")], cmd = "$(location {}) $(SRCS) --omit_deps={} --numpy_to_jax > $@".format( REWRITER_TARGET, ",".join(resolved_omit_deps_jax), ), tools = [REWRITER_TARGET], ) native.py_library( name = "{}.jax.raw".format(name), srcs = jax_srcs, deps = _substrate_deps(trimmed_deps, "jax"), srcs_version = srcs_version, testonly = testonly, ) # Add symlinks under tfp/substrates/jax. substrate_runfiles_symlinks( name = "{}.jax".format(name), substrate = "jax", deps = [":{}.jax.raw".format(name)], testonly = testonly, ) def multi_substrate_py_test( name, size = "small", jax_size = None, numpy_size = None, srcs = [], deps = [], tags = [], numpy_tags = [], jax_tags = [], disabled_substrates = [], srcs_version = "PY2AND3", timeout = None, shard_count = None): """A TFP `py2and3_test` for each of TF, NumPy, and JAX. Args: name: Name of the `test_suite` which covers TF, NumPy and JAX variants of the test. Each substrate will have a dedicated `py2and3_test` suffixed with '.tf', '.numpy', or '.jax' as appropriate. size: As with `py_test`. jax_size: A size override for the JAX target. numpy_size: A size override for the numpy target. srcs: As with `py_test`. These will have a `genrule` emitted to rewrite NumPy and JAX variants, writing the test file into a subdirectory. deps: As with `py_test`. The list is rewritten to depend on substrate-specific libraries for substrate variants. tags: Tags global to this test target. NumPy also gets a `'tfp_numpy'` tag, and JAX gets a `'tfp_jax'` tag. A `f'_{name}'` tag is used to produce the `test_suite`. numpy_tags: Tags specific to the NumPy test. (e.g. `"notap"`). jax_tags: Tags specific to the JAX test. (e.g. `"notap"`). disabled_substrates: Iterable of substrates to disable, items from ["numpy", "jax"]. srcs_version: As with `py_test`. timeout: As with `py_test`. shard_count: As with `py_test`. """ name_tag = "_{}".format(name) tags = [t for t in tags] tags.append(name_tag) tags.append("multi_substrate") native.py_test( name = "{}.tf".format(name), size = size, srcs = srcs, main = "{}.py".format(name), deps = deps, tags = tags, srcs_version = srcs_version, timeout = timeout, shard_count = shard_count, ) if "numpy" not in disabled_substrates: numpy_srcs = _substrate_srcs(srcs, "numpy") native.genrule( name = "rewrite_{}_numpy".format(name), srcs = srcs, outs = numpy_srcs, cmd = "$(location {}) $(SRCS) > $@".format(REWRITER_TARGET), tools = [REWRITER_TARGET], ) py3_test( name = "{}.numpy".format(name), size = numpy_size or size, srcs = numpy_srcs, main = _substrate_src("{}.py".format(name), "numpy"), deps = _substrate_deps(deps, "numpy"), tags = tags + ["tfp_numpy"] + numpy_tags, srcs_version = srcs_version, python_version = "PY3", timeout = timeout, shard_count = shard_count, ) if "jax" not in disabled_substrates: jax_srcs = _substrate_srcs(srcs, "jax") native.genrule( name = "rewrite_{}_jax".format(name), srcs = srcs, outs = jax_srcs, cmd = "$(location {}) $(SRCS) --numpy_to_jax > $@".format(REWRITER_TARGET), tools = [REWRITER_TARGET], ) jax_deps = _substrate_deps(deps, "jax") # [internal] Add JAX build dep py3_test( name = "{}.jax".format(name), size = jax_size or size, srcs = jax_srcs, main = _substrate_src("{}.py".format(name), "jax"), deps = jax_deps, tags = tags + ["tfp_jax"] + jax_tags, srcs_version = srcs_version, python_version = "PY3", timeout = timeout, shard_count = shard_count, ) native.test_suite( name = name, tags = [name_tag], )

ed587bf56577619d8ec39ef62825f11e9ce7e776

py

Python

projects/MAE/utils/weight_convert.py

Oneflow-Inc/libai

e473bd3962f07b1e37232d2be39c8257df0ec0f3

2021-12-10T08:47:06.000Z

2022-03-28T09:02:15.000Z

projects/MAE/utils/weight_convert.py

Oneflow-Inc/libai

e473bd3962f07b1e37232d2be39c8257df0ec0f3

2021-11-03T05:16:45.000Z

2022-03-31T06:16:23.000Z

projects/MAE/utils/weight_convert.py

Oneflow-Inc/libai

e473bd3962f07b1e37232d2be39c8257df0ec0f3

2021-12-29T08:12:08.000Z

2022-03-28T06:59:45.000Z

# coding=utf-8 # Copyright 2021 The OneFlow Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging import oneflow as flow import torch logger = logging.getLogger(__name__) def convert_qkv_weight(cfg, value): """ Convert qkv.weight to be compatible with LiBai transformer layer Args: cfg: config file value: qkv.weight in the loaded checkpoint """ num_heads = cfg.model.num_heads hidden_size = cfg.model.embed_dim head_size = int(hidden_size / num_heads) qkv_weight = ( value.view([3, num_heads, head_size, hidden_size]) .permute(1, 0, 2, 3) .contiguous() .view(hidden_size * 3, hidden_size) ) return qkv_weight def convert_qkv_bias(cfg, value): """ Convert qkv.bias to be compatible with LiBai transformer layer Args: cfg: config file value: qkv.bias in the loaded checkpoint """ num_heads = cfg.model.num_heads hidden_size = cfg.model.embed_dim head_size = int(hidden_size / num_heads) qkv_bias = ( value.view(3, num_heads, head_size).permute(1, 0, 2).contiguous().view(hidden_size * 3) ) return qkv_bias def filter_keys(key, value, cfg): """ Filtering the state_dict keys and values to match LiBai's MAE model """ if "norm1" in key: key = key.replace("norm1", "input_layernorm") elif "attn.qkv" in key: key = key.replace("attn.qkv", "self_attention.query_key_value") if "weight" in key: value = convert_qkv_weight(cfg, value) if "bias" in key: value = convert_qkv_bias(cfg, value) elif "attn.proj" in key: key = key.replace("attn.proj", "self_attention.dense") elif "norm2" in key: key = key.replace("norm2", "post_attention_layernorm") elif "mlp.fc1" in key: key = key.replace("mlp.fc1", "mlp.dense_h_to_4h") elif "mlp.fc2" in key: key = key.replace("mlp.fc2", "mlp.dense_4h_to_h") elif "fc_norm" in key: key = key.replace("fc_norm", "norm") return key, value def load_torch_checkpoint(model, cfg, path="./mae_finetuned_vit_base.pth", strict=False): """ Load checkpoint from the given torch weights. Torch weight can be downloaded from the original repo: https://github.com/facebookresearch/mae """ torch_dict = torch.load(path, map_location="cpu")["model"] parameters = torch_dict new_parameters = dict() for key, value in parameters.items(): if "num_batches_tracked" not in key: # to global tensor key, val = filter_keys(key, value, cfg) val = val.detach().cpu().numpy() val = flow.tensor(val).to_global( sbp=flow.sbp.broadcast, placement=flow.placement("cuda", ranks=[0]) ) new_parameters[key] = val model.load_state_dict(new_parameters, strict=strict) print("Successfully load torch mae checkpoint.") return model

ed6236b34ab65a1e059ca45441d455cec6bd4e90

py

Python

validator/delphi_validator/run.py

benjaminysmith/covidcast-indicators

b1474cd68a1497166fefe4beffd4d5ff867b9a61

validator/delphi_validator/run.py

benjaminysmith/covidcast-indicators

b1474cd68a1497166fefe4beffd4d5ff867b9a61

validator/delphi_validator/run.py

benjaminysmith/covidcast-indicators

b1474cd68a1497166fefe4beffd4d5ff867b9a61

# -*- coding: utf-8 -*- """Functions to call when running the tool. This module should contain a function called `run_module`, that is executed when the module is run with `python -m delphi_validator`. """ from delphi_utils import read_params from .validate import Validator def run_module(): """Run the validator as a module.""" parent_params = read_params() params = parent_params['validation'] validator = Validator(params) validator.validate(parent_params["export_dir"]).print_and_exit()

ed6aff1082796c2046965ddce3d39f2087944e89

py

Python

setup.py

marcus-luck/zohoreader

e832f076a8a87bf27607980fb85a1d2bc8339743

2020-11-11T02:19:50.000Z

2020-11-11T02:19:50.000Z

setup.py

marcus-luck/zohoreader

e832f076a8a87bf27607980fb85a1d2bc8339743

setup.py

marcus-luck/zohoreader

e832f076a8a87bf27607980fb85a1d2bc8339743

from setuptools import setup def readme(): with open('README.rst') as f: return f.read() setup(name='zohoreader', version='0.1', description='A simple reader for zoho projects API to get all projects, users and timereports', long_description=readme(), classifiers=[ 'Development Status :: 3 - Alpha', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python :: 3.5', ], keywords='zoho, API, zoho project', url='https://github.com/marcus-luck/zohoreader', author='Marcus Luck', author_email='marcus.luck@outlook.com', license='MIT', packages=['zohoreader'], zip_safe=False, install_requires=[ 'requests>=2.12.4', 'python-dateutil>=2.7.2' ], test_suite='nose.collector', tests_require=['nose', 'nose-cover3'], include_package_data=True )

ed6bae7a17f418cda8c2e6d4ee817869bb64ec62

bzl

Python

stratum/portage/build_defs.bzl

cholve/stratum

09ddb5acb604f7e694a6b7d2fe93fea79f801794

2019-09-11T15:01:37.000Z

2022-03-28T11:14:29.000Z

stratum/portage/build_defs.bzl

cholve/stratum

09ddb5acb604f7e694a6b7d2fe93fea79f801794

2019-09-18T03:37:08.000Z

2022-03-30T00:59:53.000Z

stratum/portage/build_defs.bzl

cholve/stratum

09ddb5acb604f7e694a6b7d2fe93fea79f801794

2019-09-16T07:30:53.000Z

2022-03-18T09:53:03.000Z

# Copyright 2018 Google LLC # Copyright 2018-present Open Networking Foundation # SPDX-License-Identifier: Apache-2.0 """A portable build system for Stratum P4 switch stack. To use this, load() this file in a BUILD file, specifying the symbols needed. The public symbols are the macros: decorate(path) sc_cc_lib Declare a portable Library. sc_proto_lib Declare a portable .proto Library. sc_cc_bin Declare a portable Binary. sc_package Declare a portable tarball package. and the variables/lists: ALL_ARCHES All known arches. EMBEDDED_ARCHES All embedded arches. EMBEDDED_PPC Name of PowerPC arch - "ppc". EMBEDDED_X86 Name of "x86" arch. HOST_ARCH Name of default "host" arch. HOST_ARCHES All host arches. STRATUM_INTERNAL For declaring Stratum internal visibility. The macros are like cc_library(), proto_library(), and cc_binary(), but with different options and some restrictions. The key difference: you can supply lists of architectures for which they should be compiled - defaults to all if left unstated. Internally, libraries and binaries are generated for every listed architecture. The names are decorated to keep them different and allow all to be generated and addressed independently. This aspect of the system is suboptimal - something along the lines of augmenting context with a user defined configuration fragment would be a much cleaner solution. Currently supported architectures: ppc x86 """ load("//tools/build_defs/label:def.bzl", "parse_label") load( "//devtools/build_cleaner/skylark:build_defs.bzl", "register_extension_info", ) load("@rules_proto//proto:defs.bzl", "proto_library") load("@rules_cc//cc:defs.bzl", "cc_binary", "cc_library", "cc_test") # Generic path & label helpers. ============================================ def _normpath(path): """Normalize a path. Normalizes a path by removing unnecessary path-up segments and its corresponding directories. Providing own implementation because import os is not allowed in build defs. For example ../../dir/to/deeply/nested/path/../../../other/path will become ../../dir/to/other/path Args: path: A valid absolute or relative path to normalize. Returns: A path equivalent to the input path with minimal use of path-up segments. Invalid input paths will stay invalid. """ sep = "/" level = 0 result = [] for d in path.split(sep): if d in ("", "."): if result: continue elif d == "..": if level > 0: result.pop() level += -1 continue else: level += 1 result.append(d) return sep.join(result) # Adds a suffix to a label, expanding implicit targets if needed. def decorate(label, suffix): if label.endswith(":"): # .../bar: -> .../bar label = label[:-1] if ":" in label: # .../bar:bat -> .../bar:bat_suffix return "%s_%s" % (label, suffix) elif label.startswith("//"): # //foo/bar -> //foo/bar:bar_suffix return "%s:%s_%s" % (label, label.split("/")[-1], suffix) else: # bar -> bar_suffix return "%s_%s" % (label, suffix) # Creates a relative filename from a label, replacing "//" and ":". def _make_filename(label): if label.startswith("//"): # //foo/bar:bat/baz -> google3_foo/bar/bat/baz return label.replace("//", "google3/").replace(":", "/") elif label.startswith(":"): # :bat/baz -> bat/baz return label[1:] else: # bat/baz -> bat/baz return label # Adds dquotes around a string. def dquote(s): return '"' + s + '"' # Adds squotes around a string. def squote(s): return "'" + s + "'" # Emulate Python 2.5+ str(startswith([prefix ...]) def starts_with(s, prefix_list): for prefix in prefix_list: if s.startswith(prefix): return prefix return None def sc_platform_select(host = None, ppc = None, x86 = None, default = None): """Public macro to alter blaze rules based on the platform architecture. Generates a blaze select(...) statement that can be used in most contexts to alter a blaze rule based on the target platform architecture. If no selection is provided for a given platform, {default} is used instead. A specific value or default must be provided for every target platform. Args: host: The value to use for host builds. ppc: The value to use for ppc builds. x86: The value to use for x86 builds. default: The value to use for any of {host,ppc,x86} that isn't specified. Returns: The requested selector. """ if default == None and (host == None or ppc == None or x86 == None): fail("Missing a select value for at least one platform in " + "sc_platform_select. Please add.") config_label_prefix = "//stratum:stratum_" return select({ "//conditions:default": (host or default), config_label_prefix + "ppc": (ppc or default), config_label_prefix + "x86": (x86 or default), }) # Generates an sc_platform_select based on a textual list of arches. def sc_platform_filter(value, default, arches): return sc_platform_select( host = value if "host" in arches else default, ppc = value if "ppc" in arches else default, x86 = value if "x86" in arches else default, ) def sc_platform_alias( name, host = None, ppc = None, x86 = None, default = None, visibility = None): """Public macro to create an alias that changes based on target arch. Generates a blaze alias that will select the appropriate target. If no selection is provided for a given platform and no default is set, a dummy default target is used instead. Args: name: The name of the alias target. host: The result of the alias for host builds. ppc: The result of the alias for ppc builds. x86: The result of the alias for x86 builds. default: The result of the alias for any of {host,ppc,x86} that isn't specified. visibility: The visibility of the alias target. """ native.alias( name = name, actual = sc_platform_select( default = default or "//stratum/portage:dummy", host = host, ppc = ppc, x86 = x86, ), visibility = visibility, ) # Embedded build definitions. ============================================== EMBEDDED_PPC = "ppc" EMBEDDED_X86 = "x86" EMBEDDED_ARCHES = [ EMBEDDED_PPC, EMBEDDED_X86, ] HOST_ARCH = "host" HOST_ARCHES = [HOST_ARCH] ALL_ARCHES = EMBEDDED_ARCHES + HOST_ARCHES # Identify Stratum platform arch for .pb.h shims and other portability hacks. _ARCH_DEFINES = sc_platform_select( default = ["STRATUM_ARCH_HOST"], ppc = ["STRATUM_ARCH_PPC"], x86 = ["STRATUM_ARCH_X86"], ) STRATUM_INTERNAL = [ "//stratum:__subpackages__", ] # # Build options for all embedded architectures # # Set _TRACE_SRCS to show sources in embedded sc_cc_lib compile steps. # This is more general than it may seem: genrule doesn't have hdrs or deps # attributes, so all embedded dependencies appear as a `src'. # TODO(unknown): if useful again then inject from cmdline else kill feature. _TRACE_SRCS = False # Used for all gcc invocations. _EMBEDDED_FLAGS = [ "-O0", # Don't use this for program-sizing build #-- "-Os", # Use this for program-sizing build "-g", # Don't use this for program-sizing build "-Wall", "-Werror", # Warn lots, and force fixing warnings. "-no-canonical-prefixes", # Don't mangle paths and confuse blaze. "-fno-builtin-malloc", # We'll use tcmalloc "-fno-builtin-calloc", "-fno-builtin-realloc", "-fno-builtin-free", "-D__STDC_FORMAT_MACROS=1", # TODO(unknown): Figure out how we can use $(CC_FLAGS) instead of this. "-D__GOOGLE_STL_LEGACY_COMPATIBILITY", ] # Used for C and C++ compiler invocations. _EMBEDDED_CFLAGS = [ "-I$(GENDIR)", ] # Used for C++ compiler invocations. _EMBEDDED_CXXFLAGS = [ "-std=gnu++11", # Allow C++11 features _and_ GNU extensions. ] # Used for linking binaries. _EMBEDDED_LDFLAGS = [ # "-static", # Use this for program-sizing build # "-Wl,--gc-sections,--no-wchar-size-warning", # Use this for program-sizing build ] # PPC ====================================================================== _PPC_GRTE = "//unsupported_toolchains/crosstoolng_powerpc32_8540/sysroot" # X86 ====================================================================== _X86_GRTE = "//grte/v4_x86/release/usr/grte/v4" # Portability definitions =================================================== def sc_cc_test( name, size = None, srcs = None, deps = None, data = None, defines = None, copts = None, linkopts = None, visibility = None): """Creates a cc_test rule that interacts safely with Stratum builds. Generates a cc_test rule that doesn't break the build when an embedded arch is selected. During embedded builds this target will generate a dummy binary and will not attempt to build any dependencies. Args: name: Analogous to cc_test name argument. size: Analogous to cc_test size argument. srcs: Analogous to cc_test srcs argument. deps: Analogous to cc_test deps argument. data: Analogous to cc_test data argument. defines: Analogous to cc_test defines argument. copts: Analogous to cc_test copts argument. linkopts: Analogous to cc_test linkopts argument. visibility: Analogous to cc_test visibility argument. """ cc_test( name = name, size = size or "small", srcs = sc_platform_select(host = srcs or [], default = []), deps = sc_platform_select( host = deps or [], default = ["//stratum/portage:dummy_with_main"], ), data = data or [], defines = defines, copts = copts, linkopts = linkopts, visibility = visibility, ) register_extension_info( extension_name = "sc_cc_test", label_regex_for_dep = "{extension_name}", ) def sc_cc_lib( name, deps = None, srcs = None, hdrs = None, arches = None, copts = None, defines = None, includes = None, include_prefix = None, strip_include_prefix = None, data = None, testonly = None, textual_hdrs = None, visibility = None, xdeps = None): """Creates rules for the given portable library and arches. Args: name: Analogous to cc_library name argument. deps: Analogous to cc_library deps argument. srcs: Analogous to cc_library srcs argument. hdrs: Analogous to cc_library hdrs argument. arches: List of architectures to generate this way. copts: Analogous to cc_library copts argument. defines: Symbols added as "-D" compilation options. includes: Paths to add as "-I" compilation options. include_prefix: Analogous to cc_library include_prefix argument. strip_include_prefix: Analogous to cc_library strip_include_prefix argument. data: Files to provide as data at runtime (host builds only). testonly: Standard blaze testonly parameter. textual_hdrs: Analogous to cc_library. visibility: Standard blaze visibility parameter. xdeps: External (file) dependencies of this library - no decorations assumed, used and exported as header, not for flags, libs, etc. """ alwayslink = 0 deps = depset(deps or []) srcs = depset(srcs or []) hdrs = depset(hdrs or []) xdeps = depset(xdeps or []) copts = depset(copts or []) includes = depset(includes or []) data = depset(data or []) textual_hdrs = depset(textual_hdrs or []) if srcs: if [s for s in srcs.to_list() if not s.endswith(".h")]: alwayslink = 1 if not arches: arches = ALL_ARCHES defs_plus = (defines or []) + _ARCH_DEFINES textual_plus = textual_hdrs | depset(deps.to_list()) cc_library( name = name, deps = sc_platform_filter(deps, [], arches), srcs = sc_platform_filter(srcs, [], arches), hdrs = sc_platform_filter(hdrs, [], arches), alwayslink = alwayslink, copts = sc_platform_filter(copts, [], arches), defines = defs_plus, includes = sc_platform_filter(includes, [], arches), include_prefix = include_prefix, strip_include_prefix = strip_include_prefix, testonly = testonly, textual_hdrs = sc_platform_filter( textual_plus | xdeps, [], arches, ), data = sc_platform_filter(data, [], arches), visibility = visibility, ) register_extension_info( extension_name = "sc_cc_lib", label_regex_for_dep = "{extension_name}", ) def sc_cc_bin( name, deps = None, srcs = None, arches = None, copts = None, defines = None, includes = None, testonly = None, visibility = None): """Creates rules for the given portable binary and arches. Args: name: Analogous to cc_binary name argument. deps: Analogous to cc_binary deps argument. srcs: Analogous to cc_binary srcs argument. arches: List of architectures to generate this way. copts: Analogous to cc_binary copts argument. defines: Symbols added as "-D" compilation options. includes: Paths to add as "-I" compilation options. testonly: Standard blaze testonly parameter. visibility: Standard blaze visibility parameter. """ deps = depset(deps or []) srcs = depset(srcs or []) if not arches: arches = ALL_ARCHES defs_plus = (defines or []) + _ARCH_DEFINES cc_binary( name = name, deps = sc_platform_filter( deps, ["//stratum/portage:dummy_with_main"], arches, ), srcs = sc_platform_filter(srcs, [], arches), copts = copts, defines = defs_plus, includes = includes, linkopts = ["-ldl", "-lutil"], testonly = testonly, visibility = visibility, ) register_extension_info( extension_name = "sc_cc_bin", label_regex_for_dep = "{extension_name}", ) # Protobuf ================================================================= _SC_GRPC_DEPS = [ "//sandblaze/prebuilt/grpc", "//sandblaze/prebuilt/grpc:grpc++_codegen_base", "//sandblaze/prebuilt/grpc:grpc++_codegen_proto_lib", ] _PROTOC = "@com_google_protobuf//:protobuf:protoc" _PROTOBUF = "@com_google_protobuf//:protobuf" _SC_GRPC_PLUGIN = "//sandblaze/prebuilt/protobuf:grpc_cpp_plugin" _GRPC_PLUGIN = "//grpc:grpc_cpp_plugin" def _loc(target): """Return target location for constructing commands. Args: target: Blaze target name available to this build. Returns: $(location target) """ return "$(location %s)" % target def _gen_proto_lib( name, srcs, hdrs, deps, arch, visibility, testonly, proto_include, grpc_shim_rule): """Creates rules and filegroups for embedded protobuf library. For every given ${src}.proto, generate: :${src}_${arch}.pb rule to run protoc ${src}.proto => ${src}.${arch}.pb.{h,cc} :${src}_${arch}.grpc.pb rule to run protoc w/ erpc plugin: ${src}.proto => ${src}.${arch}.grpc.pb.{h,cc} :${src}_${arch}_proto_rollup collects include options for protoc: ${src}_${arch}_proto_rollup.flags Feed each set into sc_cc_lib to wrap them them up into a usable library; note that ${src}_${arch}_erpc_proto depends on ${src}_${arch}_proto. Args: name: Base name for this library. srcs: List of proto files hdrs: More files to build into this library, but also exported for dependent rules to utilize. deps: List of deps for this library arch: Which architecture to build this library for. visibility: Standard blaze visibility parameter, passed through to subsequent rules. testonly: Standard blaze testonly parameter. proto_include: Include path for generated sc_cc_libs. grpc_shim_rule: If needed, the name of the grpc shim for this proto lib. """ bash_vars = ["g3=$${PWD}"] # TODO(unknown): Switch protobuf to using the proto_include mechanism protoc_label = _PROTOC protobuf_label = _PROTOBUF protobuf_hdrs = "%s:well_known_types_srcs" % protobuf_label protobuf_srcs = [protobuf_hdrs] protobuf_include = "$${g3}/protobuf/src" if arch in EMBEDDED_ARCHES: grpc_plugin = _SC_GRPC_PLUGIN else: grpc_plugin = _GRPC_PLUGIN protoc_deps = [] for dep in deps: if dep.endswith("_proto"): protoc_deps.append("%s_%s_headers" % (dep, arch)) name_arch = decorate(name, arch) # We use this filegroup to accumulate the set of .proto files needed to # compile this proto. native.filegroup( name = decorate(name_arch, "headers"), srcs = hdrs + protoc_deps, visibility = visibility, ) my_proto_rollup = decorate(name_arch, "proto_rollup.flags") protoc_srcs_set = (srcs + hdrs + protoc_deps + protobuf_srcs + [my_proto_rollup]) gen_srcs = [] gen_hdrs = [] grpc_gen_hdrs = [] grpc_gen_srcs = [] tools = [protoc_label] grpc_tools = [protoc_label, grpc_plugin] protoc = "$${g3}/%s" % _loc(protoc_label) grpc_plugin = "$${g3}/%s" % _loc(grpc_plugin) cpp_out = "$${g3}/$(GENDIR)/%s/%s" % (native.package_name(), arch) accum_flags = [] full_proto_include = None if proto_include == ".": full_proto_include = native.package_name() elif proto_include: full_proto_include = "%s/%s" % (native.package_name(), proto_include) if full_proto_include: temp_prefix = "%s/%s" % (cpp_out, native.package_name()[len(full_proto_include):]) # We do a bit of extra work with these include flags to avoid generating # warnings. accum_flags.append( "$$(if [[ -e $(GENDIR)/%s ]]; then echo -IG3LOC/$(GENDIR)/%s; fi)" % (full_proto_include, full_proto_include), ) accum_flags.append( "$$(if [[ -e %s ]]; then echo -IG3LOC/%s; fi)" % (full_proto_include, full_proto_include), ) else: temp_prefix = "%s/%s" % (cpp_out, native.package_name()) proto_rollups = [ decorate(decorate(dep, arch), "proto_rollup.flags") for dep in deps if dep.endswith("_proto") ] proto_rollup_cmds = ["printf '%%s\n' %s" % flag for flag in accum_flags] proto_rollup_cmds.append("cat $(SRCS)") proto_rollup_cmd = "{ %s; } | sort -u -o $(@)" % "; ".join(proto_rollup_cmds) native.genrule( name = decorate(name_arch, "proto_rollup"), srcs = proto_rollups, outs = [my_proto_rollup], cmd = proto_rollup_cmd, visibility = visibility, testonly = testonly, ) for src in srcs + hdrs: if src.endswith(".proto"): src_stem = src[0:-6] src_arch = "%s_%s" % (src_stem, arch) temp_stem = "%s/%s" % (temp_prefix, src_stem) gen_stem = "%s.%s" % (src_stem, arch) # We can't use $${PWD} until this step, because our rollup command # might be generated on another forge server. proto_path_cmds = ["rollup=$$(sed \"s,G3LOC,$${PWD},g\" %s)" % _loc(my_proto_rollup)] proto_rollup_flags = ["$${rollup}"] if proto_include: # We'll be cd-ing to another directory before protoc, so # adjust our .proto path accordingly. proto_src_loc = "%s/%s" % (native.package_name(), src) if proto_src_loc.startswith(full_proto_include + "/"): proto_src_loc = proto_src_loc[len(full_proto_include) + 1:] else: print("Invalid proto include '%s' doesn't match src %s" % (full_proto_include, proto_src_loc)) # By cd-ing to another directory, we force protoc to produce # different symbols. Careful, our proto might be in GENDIR! proto_path_cmds.append("; ".join([ "if [[ -e %s ]]" % ("%s/%s" % (full_proto_include, proto_src_loc)), "then cd %s" % full_proto_include, "else cd $(GENDIR)/%s" % full_proto_include, "fi", ])) gendir_include = ["-I$${g3}/$(GENDIR)", "-I$${g3}", "-I."] else: proto_src_loc = "%s/%s" % (native.package_name(), src) proto_path_cmds.append("[[ -e %s ]] || cd $(GENDIR)" % proto_src_loc) gendir_include = ["-I$(GENDIR)", "-I."] # Generate messages gen_pb_h = gen_stem + ".pb.h" gen_pb_cc = gen_stem + ".pb.cc" gen_hdrs.append(gen_pb_h) gen_srcs.append(gen_pb_cc) cmds = bash_vars + [ "mkdir -p %s" % temp_prefix, ] + proto_path_cmds + [ " ".join([protoc] + gendir_include + proto_rollup_flags + [ "-I%s" % protobuf_include, "--cpp_out=%s" % cpp_out, proto_src_loc, ]), "cd $${g3}", "cp %s.pb.h %s" % (temp_stem, _loc(gen_pb_h)), "cp %s.pb.cc %s" % (temp_stem, _loc(gen_pb_cc)), ] pb_outs = [gen_pb_h, gen_pb_cc] native.genrule( name = src_arch + ".pb", srcs = protoc_srcs_set, outs = pb_outs, tools = tools, cmd = " && ".join(cmds), heuristic_label_expansion = 0, visibility = visibility, ) # Generate GRPC if grpc_shim_rule: gen_grpc_pb_h = gen_stem + ".grpc.pb.h" gen_grpc_pb_cc = gen_stem + ".grpc.pb.cc" grpc_gen_hdrs.append(gen_grpc_pb_h) grpc_gen_srcs.append(gen_grpc_pb_cc) cmds = bash_vars + [ "mkdir -p %s" % temp_prefix, ] + proto_path_cmds + [ " ".join([ protoc, "--plugin=protoc-gen-grpc-cpp=%s" % grpc_plugin, ] + gendir_include + proto_rollup_flags + [ "-I%s" % protobuf_include, "--grpc-cpp_out=%s" % cpp_out, proto_src_loc, ]), "cd $${g3}", "cp %s.grpc.pb.h %s" % (temp_stem, _loc(gen_grpc_pb_h)), "cp %s.grpc.pb.cc %s" % (temp_stem, _loc(gen_grpc_pb_cc)), ] grpc_pb_outs = [gen_grpc_pb_h, gen_grpc_pb_cc] native.genrule( name = src_arch + ".grpc.pb", srcs = protoc_srcs_set, outs = grpc_pb_outs, tools = grpc_tools, cmd = " && ".join(cmds), heuristic_label_expansion = 0, visibility = visibility, ) dep_set = depset(deps) | [protobuf_label] includes = [] if proto_include: includes = [proto_include] # Note: Public sc_proto_lib invokes this once per (listed) arch; # which then calls sc_cc_lib with same name for each arch; # multiple such calls are OK as long as the arches are disjoint. sc_cc_lib( name = decorate(name, arch), deps = dep_set, srcs = gen_srcs, hdrs = hdrs + gen_hdrs, arches = [arch], copts = [], includes = includes, testonly = testonly, textual_hdrs = gen_hdrs, visibility = visibility, ) if grpc_shim_rule: grpc_name = name[:-6] + "_grpc_proto" grpc_dep_set = dep_set | [name] | _SC_GRPC_DEPS grpc_gen_hdrs_plus = grpc_gen_hdrs + gen_hdrs sc_cc_lib( name = decorate(grpc_name, arch), deps = grpc_dep_set, srcs = grpc_gen_srcs, hdrs = hdrs + grpc_gen_hdrs_plus + [grpc_shim_rule], arches = [arch], copts = [], includes = includes, testonly = testonly, textual_hdrs = grpc_gen_hdrs_plus, visibility = visibility, ) def _gen_proto_shims(name, pb_modifier, srcs, arches, visibility): """Macro to build .pb.h multi-arch master switch for sc_proto_lib. For each src path.proto, generates path.pb.h consisting of: #ifdef logic to select path.${arch}.pb.h Also generates an alias that will select the appropriate proto target based on the currently selected platform architecture. Args: name: Base name for this library. pb_modifier: protoc plugin-dependent file extension (e.g.: .pb) srcs: List of proto files. arches: List of arches this shim should support. visibility: The blaze visibility of the generated alias. Returns: Name of shim rule for use in follow-on hdrs and/or src lists. """ outs = [] cmds = [] hdr_ext = pb_modifier + ".h" for src in srcs: pkg, filename = parse_label(src) if not filename.endswith(".proto"): continue hdr_stem = filename[0:-6] new_hdr_name = hdr_stem + hdr_ext outs.append(new_hdr_name) # Generate lines for shim switch file. # Lines expand inside squotes, so quote accordingly. include_fmt = "#include " + dquote(pkg + "/" + hdr_stem + ".%s" + hdr_ext) lines = [ "#if defined(STRATUM_ARCH_%s)" % "PPC", include_fmt % "ppc", "#elif defined(STRATUM_ARCH_%s)" % "X86", include_fmt % "x86", "#elif defined(STRATUM_ARCH_%s)" % "HOST", include_fmt % "host", "#else", "#error Unknown STRATUM_ARCH", "#endif", ] gen_cmds = [("printf '%%s\\n' '%s'" % line) for line in lines] new_hdr_loc = "$(location %s)" % new_hdr_name cmds.append("{ %s; } > %s" % (" && ".join(gen_cmds), new_hdr_loc)) shim_rule = decorate(name, "shims") native.genrule( name = shim_rule, srcs = srcs, outs = outs, cmd = " && ".join(cmds) or "true", ) sc_platform_alias( name = name, host = decorate(name, "host") if "host" in arches else None, ppc = decorate(name, "ppc") if "ppc" in arches else None, x86 = decorate(name, "x86") if "x86" in arches else None, visibility = visibility, ) return shim_rule def _gen_py_proto_lib(name, srcs, deps, visibility, testonly): """Creates a py_proto_library from the given srcs. There's no clean way to make python protos work with sc_proto_lib's proto_include field, so we keep this simple. For library "name", generates: * ${name}_default_pb, a regular proto library. * ${name}_py, a py_proto_library based on ${name}_default_pb. Args: name: Standard blaze name argument. srcs: Standard blaze srcs argument. deps: Standard blaze deps argument. visibility: Standard blaze visibility argument. testonly: Standard blaze testonly argument. """ regular_proto_name = decorate(name, "default_pb") py_name = decorate(name, "py") proto_library( name = regular_proto_name, srcs = srcs, deps = [decorate(dep, "default_pb") for dep in deps], visibility = visibility, testonly = testonly, ) native.py_proto_library( name = py_name, api_version = 2, deps = [regular_proto_name], visibility = visibility, testonly = testonly, ) # TODO(unknown): Add support for depending on normal proto_library rules. def sc_proto_lib( name = None, srcs = [], hdrs = [], deps = [], arches = [], visibility = None, testonly = None, proto_include = None, python_support = False, services = []): """Public macro to build multi-arch library from Message protobuf(s). For library "name", generates: * ${name}_shim aka .pb.h master switch - see _gen_proto_shims, above. * ${name}_${arch}_pb protobuf compile rules - one for each arch. * sc_cc_lib(name) with those as input. * ${name}_py a py_proto_library version of this library. Only generated if python_support == True. Args: name: Base name for this library. srcs: List of .proto files - private to this library. hdrs: As above, but also exported for dependent rules to utilize. deps: List of deps for this library arches: Which architectures to build this library for, None => ALL. visibility: Standard blaze visibility parameter, passed through to subsequent rules. testonly: Standard blaze testonly parameter. proto_include: Path to add to include path. This will affect the symbols generated by protoc, as well as the include paths used for both sc_cc_lib and sc_proto_lib rules that depend on this rule. Typically "." python_support: Defaults to False. If True, generate a python proto library from this rule. Any sc_proto_lib with python support may only depend on sc_proto_libs that also have python support, and may not use the proto_include field in this rule. services: List of services to enable {"grpc", "rpc"}; Only "grpc" is supported. So "rpc" and "grpc" are equivalent. """ if not arches: if testonly: arches = HOST_ARCHES else: arches = ALL_ARCHES service_enable = { "grpc": 0, } for service in services or []: if service == "grpc": service_enable["grpc"] = 1 elif service == "rpc": service_enable["grpc"] = 1 else: fail("service='%s' not in (grpc, rpc)" % service) deps = depset(deps or []) shim_rule = _gen_proto_shims( name = name, pb_modifier = ".pb", srcs = srcs + hdrs, arches = arches, visibility = visibility, ) grpc_shim_rule = None if (service_enable["grpc"]): grpc_shim_rule = _gen_proto_shims( name = decorate(name[:-6], "grpc_proto"), pb_modifier = ".grpc.pb", srcs = srcs + hdrs, arches = arches, visibility = visibility, ) for arch in arches: _gen_proto_lib( name = name, srcs = srcs, hdrs = [shim_rule] + hdrs, deps = deps, arch = arch, visibility = visibility, testonly = testonly, proto_include = proto_include, grpc_shim_rule = grpc_shim_rule, ) if python_support: if proto_include: fail("Cannot use proto_include on an sc_proto_lib with python support.") _gen_py_proto_lib( name = name, srcs = depset(srcs + hdrs), deps = deps, visibility = visibility, testonly = testonly, ) register_extension_info( extension_name = "sc_proto_lib", label_regex_for_dep = "{extension_name}", ) def sc_package( name = None, bins = None, data = None, deps = None, arches = None, visibility = None): """Public macro to package binaries and data for deployment. For package "name", generates: * ${name}_${arch}_bin and ${name}_${arch}_data filesets containing respectively all of the binaries and all of the data needed for this package and all dependency packages. * ${name}_${arch} fileset containing the corresponding bin and data filesets, mapped to bin/ and share/ respectively. * ${name}_${arch}_tarball rule builds that .tar.gz package. Args: name: Base name for this package. bins: List of sc_cc_bin rules to be packaged. data: List of files (and file producing rules) to be packaged. deps: List of other sc_packages to add to this package. arches: Which architectures to build this library for, None => EMBEDDED_ARCHES (HOST_ARCHES not generally supported). visibility: Standard blaze visibility parameter, passed through to all filesets. """ bins = depset(bins or []) data = depset(data or []) deps = depset(deps or []) if not arches: arches = EMBEDDED_ARCHES fileset_name = decorate(name, "fs") for extension, inputs in [ ("bin", ["%s.stripped" % b for b in bins.to_list()]), ("data", data), ]: native.Fileset( name = decorate(fileset_name, extension), out = decorate(name, extension), entries = [ native.FilesetEntry( files = inputs, ), ] + [ native.FilesetEntry(srcdir = decorate(dep, extension)) for dep in deps.to_list() ], visibility = visibility, ) # Add any platform specific files to the final tarball. platform_entries = sc_platform_select( # We use a different ppc toolchain for Stratum. # This means that we must provide portable shared libs for our ppc # executables. ppc = [native.FilesetEntry( srcdir = "%s:BUILD" % _PPC_GRTE, files = [":libs"], destdir = "lib/stratum", symlinks = "dereference", )], default = [], ) native.Fileset( name = fileset_name, out = name, entries = [ native.FilesetEntry( srcdir = decorate(name, "bin"), destdir = "bin", ), native.FilesetEntry( srcdir = decorate(name, "data"), destdir = "share", ), ] + platform_entries, visibility = visibility, ) outs = ["%s.tar.gz" % name] # Copy our files into a temporary directory and make any necessary changes # before tarballing. cmds = [ "TEMP_DIR=$(@D)/stratum_packaging_temp", "mkdir $${TEMP_DIR}", "cp -r %s $${TEMP_DIR}/tarball" % _loc(fileset_name), "if [[ -e $${TEMP_DIR}/tarball/bin ]]", "then for f in $${TEMP_DIR}/tarball/bin/*.stripped", " do mv $${f} $${f%.stripped}", # rename not available. "done", "fi", "tar czf %s -h -C $${TEMP_DIR}/tarball ." % _loc(name + ".tar.gz"), "rm -rf $${TEMP_DIR}", ] native.genrule( name = decorate(name, "tarball"), srcs = [":%s" % fileset_name], outs = outs, cmd = "; ".join(cmds), visibility = visibility, )

ed6e652c3847138189ca7b951889b9b3a32aa8ce

py

Python

jassen/django/project/project/urls.py

cabilangan112/intern-drf-blog

b2d6c7a4af1316b2c7ce38547bd9df99b4f3e8b9

jassen/django/project/project/urls.py

cabilangan112/intern-drf-blog

b2d6c7a4af1316b2c7ce38547bd9df99b4f3e8b9

jassen/django/project/project/urls.py

cabilangan112/intern-drf-blog

b2d6c7a4af1316b2c7ce38547bd9df99b4f3e8b9

"""project URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.0/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.conf.urls import url, include from rest_framework import routers from blog import views from blog.views import PostViewSet,CommentViewSet,CategoryViewSet,TagViewSet,DraftViewSet,HideViewSet from django.conf import settings from django.conf.urls.static import static router = routers.DefaultRouter() router.register(r'hide',HideViewSet, base_name='hiddinn') router.register(r'draft',DraftViewSet, base_name='draft') router.register(r'post', PostViewSet, base_name='post') router.register(r'comment', CommentViewSet, base_name='comment') router.register(r'tags', TagViewSet, base_name='tags') router.register(r'category', CategoryViewSet, base_name='category') from django.contrib import admin from django.urls import path urlpatterns = [ path('admin/', admin.site.urls), url(r'^', include(router.urls)), url(r'^api-auth/', include('rest_framework.urls', namespace='rest_framework')) ] urlpatterns.extend( static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT) )

ed6e6b0df61cc3926c2f1e1ffc6195fcb5a7b2f1

py

Python

deep-learning-app/src/models/__init__.py

everbrez/Deep-Learning-based-Chemical-Graphics-Analysis-Platform

5ecaedadd74e96891c28d9f73384e07c1526916b

2021-04-30T10:44:32.000Z

2021-04-30T10:44:32.000Z

deep-learning-app/src/models/__init__.py

everbrez/Deep-Learning-based-Chemical-Graphics-Analysis-Platform

5ecaedadd74e96891c28d9f73384e07c1526916b

deep-learning-app/src/models/__init__.py

everbrez/Deep-Learning-based-Chemical-Graphics-Analysis-Platform

5ecaedadd74e96891c28d9f73384e07c1526916b

print('init')

71ea1c59255a1948249d1ed69284c07777e83df9

py

Python

estafeta/core/__init__.py

Solunest/pyestafeta

cd24cea4973f5184f4cc7e72a653de8b22e32f69

estafeta/core/__init__.py

Solunest/pyestafeta

cd24cea4973f5184f4cc7e72a653de8b22e32f69

estafeta/core/__init__.py

Solunest/pyestafeta

cd24cea4973f5184f4cc7e72a653de8b22e32f69

from estafeta.core.client import EstafetaClient user = None password = None id = None account_number = None production = None from estafeta.core.error import EstafetaWrongData, EstafetaEmptyField __url_label__ = [ 'https://labelqa.estafeta.com/EstafetaLabel20/services/EstafetaLabelWS?wsdl', 'https://label.estafeta.com/EstafetaLabel20/services/EstafetaLabelWS?wsdl', ] __url_tracking__ = [ 'https://trackingqa.estafeta.com/Service.asmx?wsdl', 'https://tracking.estafeta.com/Service.asmx?wsdl', ] __url_quote__ = [ 'http://frecuenciacotizador.estafeta.com/Service.asmx?wsdl', 'http://frecuenciacotizador.estafeta.com/Service.asmx?wsdl', ]

71f5039371a3b37776d4da5587717221d15a60a1

py

Python

VAE/reduced_model/nesm_generator.py

youngmg1995/NES-Music-Maker

aeda10a541cfd439cfa46c45e63411e0d98e41c1

2020-06-26T22:02:35.000Z

2021-11-20T19:24:33.000Z

VAE/reduced_model/nesm_generator.py

youngmg1995/NES-Music-Maker

aeda10a541cfd439cfa46c45e63411e0d98e41c1

VAE/reduced_model/nesm_generator.py

youngmg1995/NES-Music-Maker

aeda10a541cfd439cfa46c45e63411e0d98e41c1

# -*- coding: utf-8 -*- """ Created on Wed Apr 1 17:14:19 2020 @author: Mitchell nesm_generator.py ~~~~~~~~~~~~~~~~~ This file serves as a script for using our pre-trained VAE model to generate brand new NES music soundtracks. NOTE - using the reduced model we only generate the first melodic voice for each track rather than each of the four voices present in an NESM track. To do so we first reconstruct our model using the file VAE class defined in `VAE.py` and the same parameters used in `model_training`. Then we use functions from the file `generation_utils` to have our trained model create entirely new and original NES music. """ # Imports #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # NOTE - nesmdb folder manually added to environment libraries from dataset_utils import load_training from VAE import VAE from generation_utils import generate_seprsco, latent_SVD, get_latent_vecs,\ plot_track, filter_tracks import nesmdb from nesmdb.vgm.vgm_to_wav import save_vgmwav import tensorflow as tf import numpy as np import os, json ### Load Mappings #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Parameters for shape of dataset (note these are also used for model def.) measures = 8 measure_len = 96 # load data training_foldername = '../../nesmdb24_seprsco/train/' train_save_filename = 'transformed_dataset.json' dataset , labels2int_map , int2labels_map = \ load_training(training_foldername, train_save_filename, measures = measures, measure_len = measure_len) ### Reinitiate Model #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ### Model Parameters latent_dim = 124 input_dim = len(int2labels_map) - 1 dropout = .1 maxnorm = None vae_b1 , vae_b2 = .02 , .1 print('Reinitiating VAE Model') # Build Model model = VAE(latent_dim, input_dim, measures, measure_len, dropout, maxnorm, vae_b1 , vae_b2) # Reload Saved Weights checkpoint_dir = './training_checkpoints' checkpoint_prefix = os.path.join(checkpoint_dir, "model_ckpt") model.load_weights(checkpoint_prefix) model.build(tf.TensorShape([None, measures, measure_len, ])) # Print Summary of Model model.summary() ### Sample Latent Variable Distributions #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Here we use SVD to more effectively sample from the orthogonal components # of our latent space # Parameters for sampling num_songs = 10 print('Generating Latent Samples to Generate {} New Tracks'.format(num_songs)) # Grab distributions of dataset over latent space # Have to run in batches due to size of the dataset batch_size = 300 latent_vecs = get_latent_vecs(model, dataset, batch_size) # Sample from normal distribution rand_vecs = np.random.normal(0.0, 1.0, (num_songs, latent_dim)) # perform SVD plot_eigenvalues = True sample_vecs = latent_SVD(latent_vecs, rand_vecs, plot_eigenvalues) ### Generate New Tracks #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Create new seprsco tracks using our model and the random samples # Seprsco files can later be converted to valid NES music format # Parameters for track generation (specifically filtering) p_min = .5 print('Generating New Tracks from Latent Samples') # Decode samples using VAE decoded_tracks = model.decoder(sample_vecs) # Plot first decoded track print("Example Model Generated Track") plot_track(decoded_tracks[0]) # Filter Track decoded_tracks = filter_tracks(decoded_tracks, p_min) # Plot first filtered track print("Example Filtered Track") plot_track(decoded_tracks[0]) # Convert tracks to seprsco format print('Converting Model Output to Seprsco') seprsco_tracks = generate_seprsco(decoded_tracks, int2labels_map) ### Convert to WAV #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Convert seprsco tracks to WAV files so we can listen!!! print('Converting Seprsco to WAV Audio') wav_tracks = [] for track in seprsco_tracks: wav = nesmdb.convert.seprsco_to_wav(track) wav_tracks.append(wav) ### Save WAV Files #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ # Save our wav tracks to appropriate files (be sure not to overwrite existing) # Also save latent variables so we can reproduce songs we like # Save WAV tracks save_wav = False if save_wav: print('Saving Generated WAV Audio Tracks') wav_folder = 'model_gen_files/' for i in range(len(wav_tracks)): wav_file = wav_folder+'VAE_NESM_{}.wav'.format(i) save_vgmwav(wav_file, wav_tracks[i]) # Save Latent Variables save_latent_var = False if save_latent_var: print('Saving Latent Variables for Generated Tracks') latent_filename = os.path.join(wav_folder, "latent_variables.json") with open(latent_filename, 'w') as f: json.dump({ 'VAE_NESM_{}.wav'.format(i): sample_vecs[i].tolist() for i in range(sample_vecs.shape[0]) }, f) #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #----------------------------------END FILE------------------------------------ #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

71f8c70583f9e40977155faf528bc04d31d42d94

py

Python

EX025.py

gjaosdij/PythonProject

ae27990efa93462b632f165d13c08c7fd93beb38

EX025.py

gjaosdij/PythonProject

ae27990efa93462b632f165d13c08c7fd93beb38

EX025.py

gjaosdij/PythonProject

ae27990efa93462b632f165d13c08c7fd93beb38

print('Digite seu nome completo: ') nome = input().strip().upper() print('Seu nome tem "Silva"?') print('SILVA' in nome)

71fdcd33231ded5dc2f9d6d67f26d46eb50eca3d

py

Python

geolucidate/functions.py

kurtraschke/geolucidate

827195a90d972fa5efce5a03bdbe53d8395d94ba

2015-09-17T01:01:53.000Z

2019-09-10T14:30:43.000Z

geolucidate/functions.py

kurtraschke/geolucidate

827195a90d972fa5efce5a03bdbe53d8395d94ba

geolucidate/functions.py

kurtraschke/geolucidate

827195a90d972fa5efce5a03bdbe53d8395d94ba

2018-09-11T21:54:36.000Z

2020-06-25T19:05:45.000Z

# -*- coding: utf-8 -*- from decimal import Decimal, setcontext, ExtendedContext from geolucidate.links.google import google_maps_link from geolucidate.links.tools import MapLink from geolucidate.parser import parser_re setcontext(ExtendedContext) def _cleanup(parts): """ Normalize up the parts matched by :obj:`parser.parser_re` to degrees, minutes, and seconds. >>> _cleanup({'latdir': 'south', 'longdir': 'west', ... 'latdeg':'60','latmin':'30', ... 'longdeg':'50','longmin':'40'}) ['S', '60', '30', '00', 'W', '50', '40', '00'] >>> _cleanup({'latdir': 'south', 'longdir': 'west', ... 'latdeg':'60','latmin':'30', 'latdecsec':'.50', ... 'longdeg':'50','longmin':'40','longdecsec':'.90'}) ['S', '60', '30.50', '00', 'W', '50', '40.90', '00'] """ latdir = (parts['latdir'] or parts['latdir2']).upper()[0] longdir = (parts['longdir'] or parts['longdir2']).upper()[0] latdeg = parts.get('latdeg') longdeg = parts.get('longdeg') latmin = parts.get('latmin', '00') or '00' longmin = parts.get('longmin', '00') or '00' latdecsec = parts.get('latdecsec', '') longdecsec = parts.get('longdecsec', '') if (latdecsec and longdecsec): latmin += latdecsec longmin += longdecsec latsec = '00' longsec = '00' else: latsec = parts.get('latsec', '') or '00' longsec = parts.get('longsec', '') or '00' return [latdir, latdeg, latmin, latsec, longdir, longdeg, longmin, longsec] def _convert(latdir, latdeg, latmin, latsec, longdir, longdeg, longmin, longsec): """ Convert normalized degrees, minutes, and seconds to decimal degrees. Quantize the converted value based on the input precision and return a 2-tuple of strings. >>> _convert('S','50','30','30','W','50','30','30') ('-50.508333', '-50.508333') >>> _convert('N','50','27','55','W','127','27','65') ('50.459167', '-127.460833') """ if (latsec != '00' or longsec != '00'): precision = Decimal('0.000001') elif (latmin != '00' or longmin != '00'): precision = Decimal('0.001') else: precision = Decimal('1') latitude = Decimal(latdeg) latmin = Decimal(latmin) latsec = Decimal(latsec) longitude = Decimal(longdeg) longmin = Decimal(longmin) longsec = Decimal(longsec) if latsec > 59 or longsec > 59: # Assume that 'seconds' greater than 59 are actually a decimal # fraction of minutes latitude += (latmin + (latsec / Decimal('100'))) / Decimal('60') longitude += (longmin + (longsec / Decimal('100'))) / Decimal('60') else: latitude += (latmin + (latsec / Decimal('60'))) / Decimal('60') longitude += (longmin + (longsec / Decimal('60'))) / Decimal('60') if latdir == 'S': latitude *= Decimal('-1') if longdir == 'W': longitude *= Decimal('-1') lat_str = str(latitude.quantize(precision)) long_str = str(longitude.quantize(precision)) return (lat_str, long_str) def replace(string, sub_function=google_maps_link()): """ Replace detected coordinates with a map link, using the given substitution function. The substitution function will be passed a :class:`~.MapLink` instance, and should return a string which will be substituted by :func:`re.sub` in place of the detected coordinates. >>> replace("58147N/07720W") '<a href="http://maps.google.com/maps?q=58.235278%2C-77.333333+%2858147N%2F07720W%29&ll=58.235278%2C-77.333333&t=h" title="58147N/07720W (58.235278, -77.333333)">58147N/07720W</a>' >>> replace("5814N/07720W", google_maps_link('satellite')) '<a href="http://maps.google.com/maps?q=58.233%2C-77.333+%285814N%2F07720W%29&ll=58.233%2C-77.333&t=k" title="5814N/07720W (58.233, -77.333)">5814N/07720W</a>' >>> from geolucidate.links.bing import bing_maps_link >>> replace("58N/077W", bing_maps_link('map')) '<a href="http://bing.com/maps/default.aspx?style=r&cp=58~-77&sp=Point.58_-77_58N%2F077W&v=2" title="58N/077W (58, -77)">58N/077W</a>' """ def do_replace(match): original_string = match.group() (latitude, longitude) = _convert(*_cleanup(match.groupdict())) return sub_function(MapLink(original_string, latitude, longitude)) return parser_re.sub(do_replace, string) def get_replacements(string, sub_function=google_maps_link()): """ Return a dict whose keys are instances of :class:`re.Match` and whose values are the corresponding replacements. Use :func:`get_replacements` when the replacement cannot be performed through ordinary string substitution by :func:`re.sub`, as in :func:`replace`. >>> get_replacements("4630 NORTH 5705 WEST 58147N/07720W") ... #doctest: +ELLIPSIS {<re.Match object...>: '<a href="..." title="...">4630 NORTH 5705 WEST</a>', <re.Match object...>: '<a href="..." title="...">58147N/07720W</a>'} >>> test_string = "4630 NORTH 5705 WEST 58147N/07720W" >>> replacements = get_replacements(test_string) >>> offset = 0 >>> out = bytearray(test_string, encoding="ascii", errors="replace") >>> for (match, link) in replacements.items(): ... start = match.start() + offset ... end = match.end() + offset ... out[start:end] = bytearray(link, encoding="ascii", errors="replace") ... offset += (len(link) - len(match.group())) >>> out.decode(encoding="ascii") == replace(test_string) True """ substitutions = {} matches = parser_re.finditer(string) for match in matches: (latitude, longitude) = _convert(*_cleanup(match.groupdict())) substitutions[match] = sub_function(MapLink(match.group(), latitude, longitude)) return substitutions

71fe29113947026b758491d3c116f1982f10cf36

py

Python

setup.py

rluzuriaga/pokedex

e5c18c410994d5fb589bc3dceaba71f85268edfb

2020-08-15T01:16:17.000Z

2022-03-12T17:51:17.000Z

setup.py

rluzuriaga/pokedex

e5c18c410994d5fb589bc3dceaba71f85268edfb

2020-08-12T17:20:55.000Z

2022-03-28T18:19:28.000Z

setup.py

rluzuriaga/pokedex

e5c18c410994d5fb589bc3dceaba71f85268edfb

2020-08-18T00:09:15.000Z

2022-03-01T07:47:41.000Z

from setuptools import setup, find_packages setup( name='Pokedex', version='0.1', zip_safe=False, packages=find_packages(), package_data={ 'pokedex': ['data/csv/*.csv'] }, install_requires=[ 'SQLAlchemy>=1.0,<2.0', 'whoosh>=2.5,<2.7', 'markdown==2.4.1', 'construct==2.5.3', 'six>=1.9.0', ], entry_points={ 'console_scripts': [ 'pokedex = pokedex.main:setuptools_entry', ], }, classifiers=[ "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.7", ] )

71feffbb5e24e7f37afedbf05e8ccd4bc8d2a4ea

py

Python

pos_neg_graph/graph_ratio.py

Yudabin/Review_Project

b924199d6845defeb4cd243a99426070c014d8d8

pos_neg_graph/graph_ratio.py

Yudabin/Review_Project

b924199d6845defeb4cd243a99426070c014d8d8

pos_neg_graph/graph_ratio.py

Yudabin/Review_Project

b924199d6845defeb4cd243a99426070c014d8d8

2020-11-10T00:54:45.000Z

2020-11-10T00:54:45.000Z

import matplotlib.font_manager as fm import matplotlib.pyplot as plt import numpy as np font_location = './wordcloud_file/malgun.ttf' # For Windows font_name = fm.FontProperties(fname=font_location).get_name() plt.rc('font', family=font_name) def percent_graph2(movie_review) : b = movie_review labelss = sorted(b['score'].unique())## 라벨설정함. 한글이 적용이 안됨!!! c = b['score'].value_counts().sort_index() ## 빈도 print(c) print(labelss) fig = plt.figure(figsize=(8,8)) ## 캔버스 생성 fig.set_facecolor('white') ## 캔버스 배경색을 하얀색으로 설정 ax = fig.add_subplot() ## 프레임 생성 pie = ax.pie(c, ## 파이차트 출력 startangle=90, ## 시작점을 90도(degree)로 지정 counterclock=False, ## 시계 방향으로 그린다. # autopct=lambda p : '{:.2f}%'.format(p), ## 퍼센티지 출력 wedgeprops=dict(width=0.5), colors = ['yellowgreen', 'orange'], labels = labelss, textprops={'fontsize': 22} ) total = np.sum(c) ## 빈도수 총합 sum_pct = 0 ## 백분율 초기값 for i, l in enumerate(labelss): ang1, ang2 = pie[0][i].theta1, pie[0][i].theta2 ## 각1, 각2 r = pie[0][i].r ## 원의 반지름 x = ((r + 0.5) / 2) * np.cos(np.pi / 180 * ((ang1 + ang2) / 2)) ## 정중앙 x좌표 y = ((r + 0.5) / 2) * np.sin(np.pi / 180 * ((ang1 + ang2) / 2)) ## 정중앙 y좌표 if i < len(labelss) - 1: sum_pct += float(f'{c[i] / total * 100:.2f}') ## 백분율을 누적한다. ax.text(x, y, f'{c[i] / total * 100:.2f}%', ha='center', va='center', size=22, color='white', weight='bold') ## 백분율 텍스트 표시 else: ## 총합을 100으로 맞추기위해 마지막 백분율은 100에서 백분율 누적값을 빼준다. ax.text(x, y, f'{100 - sum_pct:.2f}%', ha='center', va='center',size=22,color='white', weight='bold') # pie.rc('font', family=font_name) # plt.legend(pie[0], labelss) ## 범례 표시 plt.savefig('./static/images/pos_neg_ratio.png') # 경로

9c0520151db9426f768e41a165d1e59bc2354107

py

Python

src/eavatar.ava/pod/mods/tasks/__init__.py

eavatar/ava

4f09c5417b7187dd919b7edabb8c516d8efc0696

src/eavatar.ava/pod/mods/tasks/__init__.py

eavatar/ava

4f09c5417b7187dd919b7edabb8c516d8efc0696

src/eavatar.ava/pod/mods/tasks/__init__.py

eavatar/ava

4f09c5417b7187dd919b7edabb8c516d8efc0696

# -*- coding: utf-8 -*- """ Modules for exposing functions that can be run as tasks. """ from __future__ import (absolute_import, division, print_function, unicode_literals)

9c18aa829131bc05a668cd4d7a72da450336ed4f

py

Python

example_scripts/profile_validation/plot_validation_gridded_data.py

British-Oceanographic-Data-Centre/NEMO-ENTRUST

41ed278e56428404ab8ec41d74a9a3a761e308ae

example_scripts/profile_validation/plot_validation_gridded_data.py

British-Oceanographic-Data-Centre/NEMO-ENTRUST

41ed278e56428404ab8ec41d74a9a3a761e308ae

example_scripts/profile_validation/plot_validation_gridded_data.py

British-Oceanographic-Data-Centre/NEMO-ENTRUST

41ed278e56428404ab8ec41d74a9a3a761e308ae

""" Plot up surface or bottom (or any fixed level) errors from a profile object with no z_dim (vertical dimension). Provide an array of netcdf files and mess with the options to get a figure you like. You can define how many rows and columns the plot will have. This script will plot the provided list of netcdf datasets from left to right and top to bottom. A colorbar will be placed right of the figure. """ import xarray as xr import matplotlib.pyplot as plt import numpy as np import sys sys.path.append("/Users/dbyrne/code/COAsT") import coast import pandas as pd #%% File settings run_name = "test" # List of analysis output files. Profiles from each will be plotted # on each axis of the plot fn_list = [ "~/transfer/test_grid.nc", "~/transfer/test_grid.nc", ] # Filename for the output fn_out = "/Users/dbyrne/transfer/surface_gridded_errors_{0}.png".format(run_name) #%% General Plot Settings var_name = "abs_diff_temperature" # Variable name in analysis file to plot # If you used var modified to make gridded data # then this is where to select season etc. save_plot = False # Masking out grid cells that don't contain many points min_points_in_average = 5 name_of_count_variable = "grid_N" # Subplot axes settings n_r = 2 # Number of subplot rows n_c = 2 # Number of subplot columns figsize = (10, 5) # Figure size lonbounds = [-15, 9.5] # Longitude bounds latbounds = [45, 64] # Latitude bounds subplot_padding = 0.5 # Amount of vertical and horizontal padding between plots fig_pad = (0.075, 0.075, 0.1, 0.1) # Figure padding (left, top, right, bottom) # Leave some space on right for colorbar # Scatter opts marker_size = 3 # Marker size cmap = "bwr" # Colormap for normal points clim = (-1, 1) # Color limits for normal points discrete_cmap = True # Discretize colormap cmap_levels = 14 # Labels and Titles fig_title = "SST Errors" # Whole figure title title_fontsize = 13 # Fontsize of title title_fontweight = "bold" # Fontweight to use for title dataset_names = ["CO9p0", "CO9p0", "CO9p0"] # Names to use for labelling plots subtitle_fontsize = 11 # Fontsize for dataset subtitles subtitle_fontweight = "normal" # Fontweight for dataset subtitles # PLOT SEASONS. Make sure n_r = 2 and n_c = 2 # If this option is true, only the first dataset will be plotted, with seasonal # variables on each subplot. The season_suffixes will be added to var_name # for each subplot panel. plot_seasons = True season_suffixes = ["DJF", "MAM", "JJA", "SON"] #%% Read and plotdata # Read all datasets into list ds_list = [xr.open_dataset(dd) for dd in fn_list] n_ds = len(ds_list) n_ax = n_r * n_c # Create plot and flatten axis array f, a = coast.plot_util.create_geo_subplots(lonbounds, latbounds, n_r, n_c, figsize=figsize) a_flat = a.flatten() # Dicretize colormap maybe if discrete_cmap: cmap = plt.cm.get_cmap(cmap, cmap_levels) # Determine if we will extend the colormap or not extend_cbar = [] # Loop over dataset for ii in range(n_ax): ur_index = np.unravel_index(ii, (n_r, n_c)) # Select season if required if plot_seasons: ds = ds_list[0] var_ii = var_name + "_{0}".format(season_suffixes[ii]) N_var = "{0}_{1}".format(name_of_count_variable, season_suffixes[ii]) a_flat[ii].text(0.05, 1.02, season_suffixes[ii], transform=a_flat[ii].transAxes, fontweight="bold") else: ds = ds_list[ii] var_ii = var_name a_flat[ii].set_title(dataset_names[ii], fontsize=subtitle_fontsize, fontweight=subtitle_fontweight) N_var = name_of_count_variable data = ds[var_ii].values count_var = ds[N_var] data[count_var < min_points_in_average] = np.nan # Scatter and set title pc = a_flat[ii].pcolormesh( ds.longitude, ds.latitude, data, cmap=cmap, vmin=clim[0], vmax=clim[1], ) # Will we extend the colorbar for this dataset? extend_cbar.append(coast.plot_util.determine_colorbar_extension(data, clim[0], clim[1])) # Set Figure title f.suptitle(fig_title, fontsize=title_fontsize, fontweight=title_fontweight) # Set tight figure layout f.tight_layout(w_pad=subplot_padding, h_pad=subplot_padding) f.subplots_adjust(left=(fig_pad[0]), bottom=(fig_pad[1]), right=(1 - fig_pad[2]), top=(1 - fig_pad[3])) # Handle colorbar -- will we extend it? if "both" in extend_cbar: extend = "both" elif "max" in extend_cbar and "min" in extend_cbar: extend = "both" elif "max" in extend_cbar: extend = "max" elif "min" in extend_cbar: extend = "min" else: extend = "neither" cbar_ax = f.add_axes([(1 - fig_pad[2] + fig_pad[2] * 0.15), 0.15, 0.025, 0.7]) f.colorbar(pc, cax=cbar_ax, extend=extend) # Save plot maybe if save_plot: f.savefig(fn_out)

9c191035667faa5283a1d949656c67ee58df9705

py

Python

feature-engineering/samples/statistical_features.py

jeury301/text-classifier

d86f658ef3368e4a3f6fd74328fa862e2881ac3b

feature-engineering/samples/statistical_features.py

jeury301/text-classifier

d86f658ef3368e4a3f6fd74328fa862e2881ac3b

feature-engineering/samples/statistical_features.py

jeury301/text-classifier

d86f658ef3368e4a3f6fd74328fa862e2881ac3b

from sklearn.feature_extraction.text import TfidfVectorizer def compute_tf_idf(corpus): """Computing term frequency (tf) - inverse document frequency (idf). :param corpus: List of documents. :returns: tf-idf of corpus. """ return TfidfVectorizer().fit_transform(corpus) if __name__ == '__main__': sample_corpus = [ 'This is sample document.', 'another random document.', 'third sample document text' ] print(compute_tf_idf(sample_corpus))

9c2757bc39980fb41a4822e37ad9596b865f8c2a

py

Python

nima/models/productos/constants.py

erichav/NIMA

6ca845047e2d1764f07af76bfbbed9f1a82bc10f

nima/models/productos/constants.py

erichav/NIMA

6ca845047e2d1764f07af76bfbbed9f1a82bc10f

nima/models/productos/constants.py

erichav/NIMA

6ca845047e2d1764f07af76bfbbed9f1a82bc10f

2018-11-18T03:58:53.000Z

2018-11-18T03:58:53.000Z

COLLECTION = 'productos'

9c28065db1d863fb5b79db27e4909a5e2d4c5505

py

Python

deepchem/metrics/score_function.py

hsjang001205/deepchem

02fce35729826b1ef12a1cfa6519b491510217be

2020-08-19T17:25:27.000Z

2020-08-19T17:25:27.000Z

deepchem/metrics/score_function.py

swpper/deepchem

510b9bf1805bc5a472c1a519700e6b128e06c651

2020-09-22T18:42:21.000Z

2020-09-22T18:42:21.000Z

deepchem/metrics/score_function.py

swpper/deepchem

510b9bf1805bc5a472c1a519700e6b128e06c651

2020-10-06T13:31:21.000Z

2020-10-06T13:31:21.000Z

"""Evaluation metrics.""" import numpy as np from sklearn.metrics import matthews_corrcoef # noqa from sklearn.metrics import recall_score # noqa from sklearn.metrics import cohen_kappa_score from sklearn.metrics import r2_score # noqa from sklearn.metrics import mean_squared_error from sklearn.metrics import mean_absolute_error from sklearn.metrics import precision_score # noqa from sklearn.metrics import precision_recall_curve from sklearn.metrics import auc from sklearn.metrics import jaccard_score from sklearn.metrics import f1_score from sklearn.metrics import roc_auc_score # noqa from sklearn.metrics import accuracy_score # noqa from sklearn.metrics import balanced_accuracy_score # noqa from scipy.stats import pearsonr # kappa_score is an alias for `sklearn.metrics.cohen_kappa_score` kappa_score = cohen_kappa_score def pearson_r2_score(y: np.ndarray, y_pred: np.ndarray) -> float: """Computes Pearson R^2 (square of Pearson correlation). Parameters ---------- y: np.ndarray ground truth array y_pred: np.ndarray predicted array Returns ------- float The Pearson-R^2 score. """ return pearsonr(y, y_pred)[0]**2 def jaccard_index(y: np.ndarray, y_pred: np.ndarray) -> float: """Computes Jaccard Index which is the Intersection Over Union metric which is commonly used in image segmentation tasks. DEPRECATED: WILL BE REMOVED IN A FUTURE VERSION OF DEEEPCHEM. USE `jaccard_score` instead. Parameters ---------- y: np.ndarray ground truth array y_pred: np.ndarray predicted array Returns ------- score: float The jaccard index. A number between 0 and 1. """ return jaccard_score(y, y_pred) def pixel_error(y: np.ndarray, y_pred: np.ndarray) -> float: """An error metric in case y, y_pred are images. Defined as 1 - the maximal F-score of pixel similarity, or squared Euclidean distance between the original and the result labels. Parameters ---------- y: np.ndarray ground truth array y_pred: np.ndarray predicted array Returns ------- score: float The pixel-error. A number between 0 and 1. """ return 1 - f1_score(y, y_pred) def prc_auc_score(y: np.ndarray, y_pred: np.ndarray) -> float: """Compute area under precision-recall curve Parameters ---------- y: np.ndarray A numpy array of shape `(N, n_classes)` or `(N,)` with true labels y_pred: np.ndarray Of shape `(N, n_classes)` with class probabilities. Returns ------- float The area under the precision-recall curve. A number between 0 and 1. """ precision, recall, _ = precision_recall_curve(y[:, 1], y_pred[:, 1]) return auc(recall, precision) def rms_score(y_true: np.ndarray, y_pred: np.ndarray) -> float: """Computes RMS error.""" return np.sqrt(mean_squared_error(y_true, y_pred)) def mae_score(y_true: np.ndarray, y_pred: np.ndarray) -> float: """Computes MAE.""" return mean_absolute_error(y_true, y_pred) def bedroc_score(y_true: np.ndarray, y_pred: np.ndarray, alpha: float = 20.0): """Compute BEDROC metric. BEDROC metric implemented according to Truchon and Bayley that modifies the ROC score by allowing for a factor of early recognition. Please confirm details from [1]_. Parameters ---------- y_true: np.ndarray Binary class labels. 1 for positive class, 0 otherwise y_pred: np.ndarray Predicted labels alpha: float, default 20.0 Early recognition parameter Returns ------- float Value in [0, 1] that indicates the degree of early recognition Notes ----- This function requires RDKit to be installed. References ---------- .. [1] Truchon et al. "Evaluating virtual screening methods: good and bad metrics for the “early recognition” problem." Journal of chemical information and modeling 47.2 (2007): 488-508. """ try: from rdkit.ML.Scoring.Scoring import CalcBEDROC except ModuleNotFoundError: raise ValueError("This function requires RDKit to be installed.") # validation assert len(y_true) == len(y_pred), 'Number of examples do not match' assert np.array_equal( np.unique(y_true).astype(int), [0, 1]), ('Class labels must be binary: %s' % np.unique(y_true)) yt = np.asarray(y_true) yp = np.asarray(y_pred) yt = yt.flatten() yp = yp[:, 1].flatten() # Index 1 because one_hot predictions scores = list(zip(yt, yp)) scores = sorted(scores, key=lambda pair: pair[1], reverse=True) return CalcBEDROC(scores, 0, alpha)

9c2d9e0a79b8d15e42eda3577f2435526ea67e86

py

Python

searching/jump_search.py

magnusrodseth/data-structures-and-algorithms

45dfdc0859683d5c76b82b87f415e2c0cdbc15e8

searching/jump_search.py

magnusrodseth/data-structures-and-algorithms

45dfdc0859683d5c76b82b87f415e2c0cdbc15e8

searching/jump_search.py

magnusrodseth/data-structures-and-algorithms

45dfdc0859683d5c76b82b87f415e2c0cdbc15e8

import math from typing import List def jump_search(array: List[int], value: int) -> int: """ Performs a jump search on a list of integers. :param array: is the array to search. :param value: is the value to search. :return: the index of the value, or -1 if it doesn't exist.' """ if len(array) == 0: return -1 block_size = get_block_size(array) # Pointers for traversing the array start_pointer = 0 next_pointer = block_size while (start_pointer < len(array)) and (array[next_pointer - 1] < value): start_pointer = next_pointer next_pointer += block_size # Prevent next from going out of bounds if next_pointer > len(array): next_pointer = len(array) # Linear search through the relevant block for i in range(start_pointer, next_pointer): if array[i] == value: return i return -1 def get_block_size(array: List[int]) -> int: """ Gets the block size of an array for jump search. The block size is the square root of the length of the array. We then calculate the absolute value of this block size, because we're using the value as index pointer, and negative values do not make sense here. This value is then floored to act as index pointer in the array. :param array: is the array to search. :return: the block size to be used in jump search. """ return math.floor(abs(math.sqrt(len(array)))) if __name__ == '__main__': # Array must be sorted in order for binary search to work array = [3, 5, 6, 9, 11, 18, 20, 21, 24, 30] print(array) index = jump_search(array, 31) print(index)

9c36070009525ecb4d0b9ecb8aa020fd7b1f9bca

py

Python

src/cms/views/error_handler/error_handler.py

digitalfabrik/coldaid-backend

b769510570d5921e30876565263813c0362994e2

2019-12-05T16:45:17.000Z

2020-05-09T07:26:34.000Z

src/cms/views/error_handler/error_handler.py

digitalfabrik/coldaid-backend

b769510570d5921e30876565263813c0362994e2

2019-12-05T12:31:37.000Z

2021-01-07T15:47:45.000Z

src/cms/views/error_handler/error_handler.py

digitalfabrik/coldaid-backend

b769510570d5921e30876565263813c0362994e2

2019-12-11T09:52:26.000Z

2020-05-09T07:26:38.000Z

from django.shortcuts import render from django.utils.translation import ugettext as _ # pylint: disable=unused-argument def handler400(request, exception): ctx = {'code': 400, 'title': _('Bad request'), 'message': _('There was an error in your request.')} response = render(request, 'error_handler/http_error.html', ctx) response.status_code = 400 return response # pylint: disable=unused-argument def handler403(request, exception): ctx = {'code': 403, 'title': _('Forbidden'), 'message': _("You don't have the permission to access this page.")} response = render(request, 'error_handler/http_error.html', ctx) response.status_code = 403 return response # pylint: disable=unused-argument def handler404(request, exception): ctx = {'code': 404, 'title': _('Page not found'), 'message': _('The page you requested could not be found.')} response = render(request, 'error_handler/http_error.html', ctx) response.status_code = 404 return response # pylint: disable=unused-argument def handler500(request): ctx = {'code': 500, 'title': _('Internal Server Error'), 'message': _('An unexpected error has occurred.')} response = render(request, 'error_handler/http_error.html', ctx) response.status_code = 500 return response # pylint: disable=unused-argument def csrf_failure(request, reason): return render(request, 'error_handler/csrf_failure.html')

9c429be32392440a110878d04d24fb43356f3b77

py

Python

paperhub/input.py

GiuseppeBaldini/PaperHub

5efdee1a0374c995a6717a4baee2106df808af12

paperhub/input.py

GiuseppeBaldini/PaperHub

5efdee1a0374c995a6717a4baee2106df808af12

2020-03-27T12:05:14.000Z

2020-03-28T01:10:20.000Z

paperhub/input.py

GiuseppeBaldini/PaperHub

5efdee1a0374c995a6717a4baee2106df808af12

# Input DOI / URL import re import sys # Pyperclip is not built-in, check and download if needed try: import pyperclip except (ImportError, ModuleNotFoundError): print('Pyperclip module not found. Please download it.') sys.exit(0) # Regex for links link_regex = re.compile(r'''( http[s]?:// (?:[a-zA-Z]| [0-9]| [$-_@.&+]| [!*\(\),]| (?:%[0-9a-fA-F][0-9a-fA-F]))+ )''', re.IGNORECASE | re.VERBOSE) # Get DOI / URL using different methods # Method 1: argument try: input_link = sys.argv[1] # Method 2: clipboard except IndexError: input_link = pyperclip.paste() # Method 3: manual input def regex_check(regex, link): """ Check using regex. If DOI/URL are not in the right format, require manual input until correct or Enter to quit. """ while True: match = re.match(regex, link) if match == None: link = str(input('''Enter valid DOI / URL or press Enter to quit: > ''')) if link == '': exit() else: continue else: return link url = regex_check(link_regex, input_link)

9c42d1030d5bf12bec44656b0c6d8328e6f4647e

py

Python

cgbind/esp.py

duartegroup/cgbind

8c2369d4c49e8b008fc3951719d99e0c4f6b6b16

2020-06-08T16:18:56.000Z

2021-01-28T09:59:16.000Z

cgbind/esp.py

duartegroup/cgbind

8c2369d4c49e8b008fc3951719d99e0c4f6b6b16

cgbind/esp.py

duartegroup/cgbind

8c2369d4c49e8b008fc3951719d99e0c4f6b6b16

2020-11-16T04:52:43.000Z

2021-06-04T05:07:29.000Z

import numpy as np from time import time from cgbind.atoms import get_atomic_number from cgbind.log import logger from cgbind.constants import Constants from cgbind.exceptions import CgbindCritical def get_esp_cube_lines(charges, atoms): """ From a list of charges and a set of xyzs create the electrostatic potential map grid-ed uniformly between the most negative x, y, z values -5 Å and the largest x, y, z +5 Å :param charges: (list(float)) :param atoms: (list(autode.atoms.Atom)) :return: (list(str)), (min ESP value, max ESP value) """ logger.info('Calculating the ESP and generating a .cube file') start_time = time() try: from esp_gen import get_cube_lines except ModuleNotFoundError: raise CgbindCritical('esp_gen not available. cgbind must be ' 'installed with the --esp_gen flag') if charges is None: logger.error('Could not generate an .cube file, charges were None') return [], (None, None) coords = np.array([atom.coord for atom in atoms]) charges = np.array(charges) # Get the max and min points from the coordinates max_cart_values = np.max(coords, axis=0) min_cat_values = np.min(coords, axis=0) # The grid needs to be slightly larger than the smallest/largest Cartesian # coordinate # NOTE: All distances from here are in Bohr (a0) i.e. atomic units min_carts = Constants.ang2a0 * (min_cat_values - 5 * np.ones(3)) max_carts = Constants.ang2a0 * (max_cart_values + 5 * np.ones(3)) coords = np.array([Constants.ang2a0 * np.array(coord) for coord in coords]) # Number of voxels will be nx * ny * nz nx, ny, nz = 50, 50, 50 vox_size = max_carts - min_carts rx, ry, rz = vox_size[0] / nx, vox_size[1] / ny, vox_size[2] / nz # Write the .cube file lines cube_file_lines = ['Generated by cgbind\n', 'ESP\n'] n_atoms = len(coords) min_x, min_y, min_z = min_carts cube_file_lines.append(f'{n_atoms:>5d}{min_x:>12f}{min_y:>12f}{min_z:>12f}\n') # n_atoms origin(x y z) cube_file_lines.append(f'{nx:>5d}{rx:>12f}{0.0:>12f}{0.0:>12f}\n') # Number of voxels and their size cube_file_lines.append(f'{ny:>5d}{0.0:>12f}{ry:>12f}{0.0:>12f}\n') cube_file_lines.append(f'{nz:>5d}{0.0:>12f}{0.0:>12f}{rz:>12f}\n') for atom in atoms: x, y, z = atom.coord cube_file_lines.append(f'{get_atomic_number(atom):>5d}{0.0:>12f}' f'{Constants.ang2a0*x:>12f}{Constants.ang2a0*y:>12f}{Constants.ang2a0*z:>12f}\n') # Looping over x, y, z is slow in python so use Cython extension cube_val_lines, min_val, max_val = get_cube_lines(nx, ny, nz, coords, min_carts, charges, vox_size) cube_file_lines += cube_val_lines logger.info(f'ESP generated in {time()-start_time:.3f} s') return cube_file_lines, (min_val, max_val)

9c49c6272ae1b539badcabd74a81163ceda4090b

py

Python

Mundo 3/teste.py

RafaelSdm/Curso-de-Python

ae933ba80ee00ad5160bd5d05cf4b21007943fd4

2021-03-10T21:53:38.000Z

2021-03-10T21:53:38.000Z

Mundo 3/teste.py

RafaelSdm/Curso-de-Python

ae933ba80ee00ad5160bd5d05cf4b21007943fd4

Mundo 3/teste.py

RafaelSdm/Curso-de-Python

ae933ba80ee00ad5160bd5d05cf4b21007943fd4

pessoas = {'nomes': "Rafael","sexo":"macho alfa","idade":19} print(f"o {pessoas['nomes']} que se considera um {pessoas['sexo']} possui {pessoas['idade']}") print(pessoas.keys()) print(pessoas.values()) print(pessoas.items()) for c in pessoas.keys(): print(c) for c in pessoas.values(): print(c) for c, j in pessoas.items(): print(f"o {c} pertence ao {j}") del pessoas['sexo'] print(pessoas) pessoas["sexo"] = "macho alfa" print(pessoas) print("outro codida daqui pra frente \n\n\n\n\n\n") estado1 = {'estado': 'minas gerais', 'cidade':'capela nova' } estado2 = {'estado':'rio de janeiro', 'cidade':"rossinha"} brasil = [] brasil.append(estado1) brasil.append(estado2) print(brasil) print(f"o brasil possui um estado chamado {brasil[0]['estado']} e a prorpia possui uma cidade chamada {brasil[0]['cidade']}") print("-"*45) es = {} br = [] for c in range(0,3): es['estado'] = str(input("informe o seu estado:")) es['cidade'] = str(input("informe a sua cidade:")) br.append(es.copy()) for c in br: for i,j in c.items(): print(f"o campo {i} tem valor {j}")

9c49fd2b9580ad32f0138ff3ca8bca4fa9148e22

py

Python

rsa-cipher/makeRsaKeys.py

mumbo-pro/cyrptography-algorithm

8e08c027c361f94c547f8b4ede723401399c93ed

2021-02-23T09:53:19.000Z

2021-02-23T09:53:19.000Z

rsa-cipher/makeRsaKeys.py

mumbo-pro/cyrptography-algorithm

8e08c027c361f94c547f8b4ede723401399c93ed

2019-09-18T08:24:05.000Z

2019-09-18T08:24:05.000Z

rsa-cipher/makeRsaKeys.py

mumbo-pro/cyrptography-algorithm

8e08c027c361f94c547f8b4ede723401399c93ed

# RSA Key Generator 2. # http://inventwithpython.com/hacking (BSD Licensed) 3. 4. import random, sys, os, rabinMiller, cryptomath The program imports the rabinMiller and cryptomath modules that we created in the last chapter, along with a few others. Chapter 24 – Public Key Cryptography and the RSA Cipher 387 makeRsaKeys.py 7. def main(): 8. # create a public/private keypair with 1024 bit keys 9. print('Making key files...') 10. makeKeyFiles('al_sweigart', 1024) 11. print('Key files made.')

9c4a756656ca930b517891bc50444eed71522301

py

Python

atlas-outreach-data-tools-framework-1.1/Configurations/PlotConf_TTbarAnalysis.py

Harvard-Neutrino/phys145

c3dc5788128fa2a7db0af0c796cf3afd957bf0ed

atlas-outreach-data-tools-framework-1.1/Configurations/PlotConf_TTbarAnalysis.py

Harvard-Neutrino/phys145

c3dc5788128fa2a7db0af0c796cf3afd957bf0ed

atlas-outreach-data-tools-framework-1.1/Configurations/PlotConf_TTbarAnalysis.py

Harvard-Neutrino/phys145

c3dc5788128fa2a7db0af0c796cf3afd957bf0ed

2021-11-30T02:08:12.000Z

2021-11-30T02:08:12.000Z

config = { "Luminosity": 1000, "InputDirectory": "results", "Histograms" : { "WtMass" : {}, "etmiss" : {}, "lep_n" : {}, "lep_pt" : {}, "lep_eta" : {}, "lep_E" : {}, "lep_phi" : {"y_margin" : 0.6}, "lep_charge" : {"y_margin" : 0.6}, "lep_type" : {"y_margin" : 0.5}, "lep_ptconerel30" : {}, "lep_etconerel20" : {}, "lep_d0" : {}, "lep_z0" : {}, "n_jets" : {}, "jet_pt" : {}, "jet_m" : {}, "jet_jvf" : {"y_margin" : 0.4}, "jet_eta" : {}, "jet_MV1" : {"y_margin" : 0.3}, "vxp_z" : {}, "pvxp_n" : {}, }, "Paintables": { "Stack": { "Order" : ["Diboson", "DrellYan", "W", "Z", "stop", "ttbar"], "Processes" : { "Diboson" : { "Color" : "#fa7921", "Contributions" : ["WW", "WZ", "ZZ"]}, "DrellYan": { "Color" : "#5bc0eb", "Contributions" : ["DYeeM08to15", "DYeeM15to40", "DYmumuM08to15", "DYmumuM15to40", "DYtautauM08to15", "DYtautauM15to40"]}, "W": { "Color" : "#e55934", "Contributions" : ["WenuJetsBVeto", "WenuWithB", "WenuNoJetsBVeto", "WmunuJetsBVeto", "WmunuWithB", "WmunuNoJetsBVeto", "WtaunuJetsBVeto", "WtaunuWithB", "WtaunuNoJetsBVeto"]}, "Z": { "Color" : "#086788", "Contributions" : ["Zee", "Zmumu", "Ztautau"]}, "stop": { "Color" : "#fde74c", "Contributions" : ["stop_tchan_top", "stop_tchan_antitop", "stop_schan", "stop_wtchan"]}, "ttbar": { "Color" : "#9bc53d", "Contributions" : ["ttbar_lep", "ttbar_had"]} } }, "data" : { "Contributions": ["data_Egamma", "data_Muons"]} }, "Depictions": { "Order": ["Main", "Data/MC"], "Definitions" : { "Data/MC": { "type" : "Agreement", "Paintables" : ["data", "Stack"] }, "Main": { "type" : "Main", "Paintables": ["Stack", "data"] }, } }, }

9c4cf09ffcfa4dd9bf0d914e9750a3f14e039df3

py

Python

examples/basic/findQSpark.py

myriadrf/pyLMS7002M

b866deea1f05dba44c9ed1a1a4666352b811b66b

2016-11-29T05:10:36.000Z

2021-10-31T19:27:46.000Z

examples/basic/findQSpark.py

myriadrf/pyLMS7002M

b866deea1f05dba44c9ed1a1a4666352b811b66b

2017-04-15T21:36:01.000Z

2017-06-08T09:44:26.000Z

examples/basic/findQSpark.py

myriadrf/pyLMS7002M

b866deea1f05dba44c9ed1a1a4666352b811b66b

2016-11-28T20:47:55.000Z

2021-04-07T01:48:20.000Z

from pyLMS7002M import * print("Searching for QSpark...") try: QSpark = QSpark() except: print("QSpark not found") exit(1) print("\QSpark info:") QSpark.printInfo() # print the QSpark board info # QSpark.LMS7002_Reset() # reset the LMS7002M lms7002 = QSpark.getLMS7002() # get the LMS7002M object ver, rev, mask = lms7002.chipInfo # get the chip info print("\nLMS7002M info:") print("VER : "+str(ver)) print("REV : "+str(rev)) print("MASK : "+str(mask))

9c5de31d5758cb655e6faea3c4a14331feb71111

py

Python

examples/multi_physics/piezo_elasticity.py

BubuLK/sfepy

3e8e2082c26d574dc334fe3a0e0eeb723f7a6657

examples/multi_physics/piezo_elasticity.py

BubuLK/sfepy

3e8e2082c26d574dc334fe3a0e0eeb723f7a6657

examples/multi_physics/piezo_elasticity.py

BubuLK/sfepy

3e8e2082c26d574dc334fe3a0e0eeb723f7a6657

r""" Piezo-elasticity problem - linear elastic material with piezoelectric effects. Find :math:`\ul{u}`, :math:`\phi` such that: .. math:: - \omega^2 \int_{Y} \rho\ \ul{v} \cdot \ul{u} + \int_{Y} D_{ijkl}\ e_{ij}(\ul{v}) e_{kl}(\ul{u}) - \int_{Y_2} g_{kij}\ e_{ij}(\ul{v}) \nabla_k \phi = 0 \;, \quad \forall \ul{v} \;, \int_{Y_2} g_{kij}\ e_{ij}(\ul{u}) \nabla_k \psi + \int_{Y} K_{ij} \nabla_i \psi \nabla_j \phi = 0 \;, \quad \forall \psi \;, where .. math:: D_{ijkl} = \mu (\delta_{ik} \delta_{jl}+\delta_{il} \delta_{jk}) + \lambda \ \delta_{ij} \delta_{kl} \;. """ from __future__ import absolute_import import os import numpy as nm from sfepy import data_dir from sfepy.discrete.fem import MeshIO from sfepy.mechanics.matcoefs import stiffness_from_lame import six def post_process(out, pb, state, extend=False): """ Calculate and output the strain and stresses for the given state. """ from sfepy.base.base import Struct from sfepy.discrete.fem import extend_cell_data ev = pb.evaluate strain = ev('ev_cauchy_strain.i.Y(u)', mode='el_avg') stress = ev('ev_cauchy_stress.i.Y(inclusion.D, u)', mode='el_avg') piezo = -ev('ev_piezo_stress.i.Y2(inclusion.coupling, phi)', mode='el_avg') piezo = extend_cell_data(piezo, pb.domain, 'Y2', val=0.0) piezo_strain = ev('ev_piezo_strain.i.Y(inclusion.coupling, u)', mode='el_avg') out['cauchy_strain'] = Struct(name='output_data', mode='cell', data=strain, dofs=None) out['elastic_stress'] = Struct(name='output_data', mode='cell', data=stress, dofs=None) out['piezo_stress'] = Struct(name='output_data', mode='cell', data=piezo, dofs=None) out['piezo_strain'] = Struct(name='output_data', mode='cell', data=piezo_strain, dofs=None) out['total_stress'] = Struct(name='output_data', mode='cell', data=stress + piezo, dofs=None) return out filename_mesh = data_dir + '/meshes/2d/special/circle_in_square.mesh' ## filename_mesh = data_dir + '/meshes/2d/special/circle_in_square_small.mesh' ## filename_mesh = data_dir + '/meshes/3d/special/cube_sphere.mesh' ## filename_mesh = data_dir + '/meshes/2d/special/cube_cylinder.mesh' omega = 1 omega_squared = omega**2 conf_dir = os.path.dirname(__file__) io = MeshIO.any_from_filename(filename_mesh, prefix_dir=conf_dir) bbox, dim = io.read_bounding_box(ret_dim=True) geom = {3 : '3_4', 2 : '2_3'}[dim] x_left, x_right = bbox[:,0] options = { 'post_process_hook' : 'post_process', } regions = { 'Y' : 'all', 'Y1' : 'cells of group 1', 'Y2' : 'cells of group 2', 'Y2_Surface': ('r.Y1 *v r.Y2', 'facet'), 'Left' : ('vertices in (x < %f)' % (x_left + 1e-3), 'facet'), 'Right' : ('vertices in (x > %f)' % (x_right - 1e-3), 'facet'), } fields = { 'displacement' : ('real', dim, 'Y', 1), 'potential' : ('real', 1, 'Y', 1), } variables = { 'u' : ('unknown field', 'displacement', 0), 'v' : ('test field', 'displacement', 'u'), 'phi' : ('unknown field', 'potential', 1), 'psi' : ('test field', 'potential', 'phi'), } ebcs = { 'u1' : ('Left', {'u.all' : 0.0}), 'u2' : ('Right', {'u.0' : 0.1}), 'phi' : ('Y2_Surface', {'phi.all' : 0.0}), } def get_inclusion_pars(ts, coor, mode=None, **kwargs): """TODO: implement proper 3D -> 2D transformation of constitutive matrices.""" if mode == 'qp': _, dim = coor.shape sym = (dim + 1) * dim // 2 dielectric = nm.eye(dim, dtype=nm.float64) # !!! coupling = nm.ones((dim, sym), dtype=nm.float64) # coupling[0,1] = 0.2 out = { # Lame coefficients in 1e+10 Pa. 'D' : stiffness_from_lame(dim=2, lam=0.1798, mu=0.148), # dielectric tensor 'dielectric' : dielectric, # piezoelectric coupling 'coupling' : coupling, 'density' : nm.array([[0.1142]]), # in 1e4 kg/m3 } for key, val in six.iteritems(out): out[key] = val[None, ...] return out materials = { 'inclusion' : (None, 'get_inclusion_pars') } functions = { 'get_inclusion_pars' : (get_inclusion_pars,), } integrals = { 'i' : 2, } equations = { '1' : """- %f * dw_volume_dot.i.Y(inclusion.density, v, u) + dw_lin_elastic.i.Y(inclusion.D, v, u) - dw_piezo_coupling.i.Y2(inclusion.coupling, v, phi) = 0""" % omega_squared, '2' : """dw_piezo_coupling.i.Y2(inclusion.coupling, u, psi) + dw_diffusion.i.Y(inclusion.dielectric, psi, phi) = 0""", } solvers = { 'ls' : ('ls.scipy_direct', {}), 'newton' : ('nls.newton', {'i_max' : 1, 'eps_a' : 1e-10, }), }

9c5f1cf8cb3617f22a594d7ff47f26bbe868fb45

py

Python

01-logica-de-programacao-e-algoritmos/Aula 06/01 Tuplas/1.2 Desempacotamento de parametros em funcoes/ex01.py

rafaelbarretomg/Uninter

1f84b0103263177122663e991db3a8aeb106a959

01-logica-de-programacao-e-algoritmos/Aula 06/01 Tuplas/1.2 Desempacotamento de parametros em funcoes/ex01.py

rafaelbarretomg/Uninter

1f84b0103263177122663e991db3a8aeb106a959

01-logica-de-programacao-e-algoritmos/Aula 06/01 Tuplas/1.2 Desempacotamento de parametros em funcoes/ex01.py

rafaelbarretomg/Uninter

1f84b0103263177122663e991db3a8aeb106a959

# Desempacotamento de parametros em funcoes # somando valores de uma tupla def soma(*num): soma = 0 print('Tupla: {}' .format(num)) for i in num: soma += i return soma # Programa principal print('Resultado: {}\n' .format(soma(1, 2))) print('Resultado: {}\n' .format(soma(1, 2, 3, 4, 5, 6, 7, 8, 9)))

9c68e55390ec5a85f2cfdfcd46e61487ba6ce000

py

Python

tests/unit/ppr/test_search_query.py

doug-lovett/test-schemas-dl

a05e87b983f2c3559c081dd65aff05e2c67e6186

tests/unit/ppr/test_search_query.py

doug-lovett/test-schemas-dl

a05e87b983f2c3559c081dd65aff05e2c67e6186

tests/unit/ppr/test_search_query.py

doug-lovett/test-schemas-dl

a05e87b983f2c3559c081dd65aff05e2c67e6186

# Copyright © 2020 Province of British Columbia # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Test Suite to ensure the PPR Search Query schema is valid. """ import copy from registry_schemas import validate from registry_schemas.example_data.ppr import SEARCH_QUERY def test_valid_search_query_ind_debtor(): """Assert that the schema is performing as expected for a search by individual debtor.""" query = copy.deepcopy(SEARCH_QUERY) query['type'] = 'INDIVIDUAL_DEBTOR' del query['criteria']['debtorName']['business'] del query['criteria']['value'] del query['clientReferenceId'] del query['startDateTime'] del query['endDateTime'] is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert is_valid def test_valid_search_query_bus_debtor(): """Assert that the schema is performing as expected for a search by business debtor.""" query = copy.deepcopy(SEARCH_QUERY) query['type'] = 'BUSINESS_DEBTOR' del query['criteria']['debtorName']['first'] del query['criteria']['debtorName']['second'] del query['criteria']['debtorName']['last'] del query['criteria']['value'] is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert is_valid def test_valid_search_query_airdot(): """Assert that the schema is performing as expected for a search by aircraft DOT.""" query = copy.deepcopy(SEARCH_QUERY) query['type'] = 'AIRCRAFT_DOT' del query['criteria']['debtorName'] query['criteria']['value'] = 'CFYXW' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert is_valid def test_valid_search_query_regnum(): """Assert that the schema is performing as expected for a search by registration number.""" query = copy.deepcopy(SEARCH_QUERY) query['type'] = 'REGISTRATION_NUMBER' del query['criteria']['debtorName'] query['criteria']['value'] = '023001B' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert is_valid def test_valid_search_query_mhrnum(): """Assert that the schema is performing as expected for a search by MHR number.""" query = copy.deepcopy(SEARCH_QUERY) query['type'] = 'MHR_NUMBER' del query['criteria']['debtorName'] query['criteria']['value'] = '21324' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert is_valid def test_valid_search_query_serialnum(): """Assert that the schema is performing as expected for a search by serial number.""" query = copy.deepcopy(SEARCH_QUERY) query['type'] = 'SERIAL_NUMBER' del query['criteria']['debtorName'] query['criteria']['value'] = 'KM8J3CA46JU622994' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert is_valid def test_invalid_search_query_missing_type(): """Assert that an invalid search query fails - type is missing.""" query = copy.deepcopy(SEARCH_QUERY) del query['type'] del query['criteria']['debtorName']['business'] del query['criteria']['value'] is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_missing_criteria(): """Assert that an invalid search query fails - criteria is missing.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria'] is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_type(): """Assert that an invalid search query fails - type is invalid.""" query = copy.deepcopy(SEARCH_QUERY) query['type'] = 'XXXXXXXX' del query['criteria']['debtorName']['business'] del query['criteria']['value'] is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_criteria(): """Assert that an invalid search query fails - criteria is invalid.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['debtorName']['business'] is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_busname(): """Assert that an invalid search query fails - business name is too short.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['debtorName']['first'] del query['criteria']['debtorName']['second'] del query['criteria']['debtorName']['last'] del query['criteria']['value'] query['criteria']['debtorName']['business'] = 'XXXX' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_value(): """Assert that an invalid search query fails - value is too long.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['debtorName'] query['criteria']['value'] = 'XxxxxxxxxxxxxxxxxxxxXxxxxxxxxxxxxxxxxxxxXxxxxxxxxxx' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_debtor(): """Assert that an invalid search query fails - debtor name is invalid.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['value'] is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_firstname(): """Assert that an invalid search query fails - debtor first name is too long.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['value'] del query['criteria']['debtorName']['business'] query['criteria']['debtorName']['first'] = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_secondname(): """Assert that an invalid search query fails - debtor second name is too long.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['value'] del query['criteria']['debtorName']['business'] query['criteria']['debtorName']['second'] = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_lastname(): """Assert that an invalid search query fails - debtor last name is too long.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['value'] del query['criteria']['debtorName']['business'] query['criteria']['debtorName']['last'] = 'XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_clientref(): """Assert that an invalid search query fails - client reference id is too long.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['value'] del query['criteria']['debtorName']['business'] query['clientReferenceId'] = 'XxxxxxxxxxXxxxxxxxxxX' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_startts(): """Assert that an invalid search query fails - start date time format is invalid.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['value'] del query['criteria']['debtorName']['business'] query['startDateTime'] = 'Xxxxxxxxxx' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid def test_invalid_search_query_endts(): """Assert that an invalid search query fails - end date time format is invalid.""" query = copy.deepcopy(SEARCH_QUERY) del query['criteria']['value'] del query['criteria']['debtorName']['business'] query['endDateTime'] = 'Xxxxxxxxxx' is_valid, errors = validate(query, 'searchQuery', 'ppr') if errors: for err in errors: print(err.message) print(errors) assert not is_valid

9c6c043e7e279ee40586854016feb8a49ecc6e3c

py

Python

tamilmorse/morse_encode.py

CRE2525/open-tamil

ffc02509f7b8a6a17644c85799a475a8ba623954

2021-08-03T19:35:18.000Z

2021-08-03T19:35:18.000Z

tamilmorse/morse_encode.py

CRE2525/open-tamil

ffc02509f7b8a6a17644c85799a475a8ba623954

tamilmorse/morse_encode.py

CRE2525/open-tamil

ffc02509f7b8a6a17644c85799a475a8ba623954

## -*- coding: utf-8 -*- #(C) 2018 Muthiah Annamalai # This file is part of Open-Tamil project # You may use or distribute this file under terms of MIT license import codecs import json import tamil import sys import os #e.g. python morse_encode.py கலைஞர் CURRDIR = os.path.dirname(os.path.realpath(__file__)) def encode(text): with codecs.open(os.path.join(CURRDIR,"data","madurai_tamilmorse.json"),"r","utf-8") as fp: codebook = json.loads(fp.read()) output = [codebook.get(l,l) for l in tamil.utf8.get_letters(text)] return u" ".join(output) if __name__ == u"__main__": encode(u" ".join([i.decode("utf-8") for i in sys.argv[1:]]))

9c6f86bf35dea92442e86d8e34f3dfcb1923875e

py

Python

BasicScripts/basics.py

TomasBelskis/PythonAutomation

dd2e30abb214e37d84a8952deb834074abdc84a2

BasicScripts/basics.py

TomasBelskis/PythonAutomation

dd2e30abb214e37d84a8952deb834074abdc84a2

BasicScripts/basics.py

TomasBelskis/PythonAutomation

dd2e30abb214e37d84a8952deb834074abdc84a2

# Python Basics # String concatenaton added_strings = str(32) + "_342" # Getting input input_from_user = input() # Basic print function print(input_from_user) # Mixing boolean and comparison operations if (4 < 5) and (5 < 6): print("True") # Basic if & if else flow if name == 'Alice': print('Hi, Alice.') elif age < 12: print("You are not Alice, kiddo.") elif age > 2000: print('Unlike you, Alice is not an undead, immortal vampire.') elif age > 100: print('You are not Alice, grannie.') # Loops in Python 3 spam = 0 while spam < 5: print('Spam, spam!') spam = spam + 1 # Access loop while True: print('Who are you?') name = input() if name != 'Joe': continue print('Hello, Joe. What is the password? (It is a fish.)') password = input() if password = 'swordfish': break print('Access granted.') # For loops using range function print("My name is") for i in range(5): print('Jimmy Five Times (' + str(i) + ')') # Using starting range for i in range(12, 16): print(i) # Importing modules import random for i in range(5): print(random.randint(1, 10)) # Exiting a python program import sys while True: print('Type exit to exit.') response = input() if response == 'exit': sys.exit() print('You typed ' + response + '.')

9c6fcb64c497c5bc80d5ed65052770cfc9db0316

py

Python

env.example.py

wilcoln/klazor

8f3c40a03a7e61c07eceb6cdbe4d1bb05693727e

2020-01-18T09:33:51.000Z

2020-01-19T10:47:51.000Z

env.example.py

wilcoln/klazor

8f3c40a03a7e61c07eceb6cdbe4d1bb05693727e

2019-08-09T03:54:44.000Z

2022-02-12T16:55:51.000Z

env.example.py

wilcoln/klazor

8f3c40a03a7e61c07eceb6cdbe4d1bb05693727e

DATABASE_OPTIONS = { 'database': 'klazor', 'user': 'root', 'password': '', 'charset': 'utf8mb4', } HOSTS = ['127.0.0.1', '67.209.115.211']

9c73c8f40881c066eecdb84a89d42263b576a7ce

py

Python

note5/package_test5.py

icexmoon/python-learning-notes

838c91d896404290b89992b6517be1b6a79df41f

note5/package_test5.py

icexmoon/python-learning-notes

838c91d896404290b89992b6517be1b6a79df41f

note5/package_test5.py

icexmoon/python-learning-notes

838c91d896404290b89992b6517be1b6a79df41f

#test.py from time_tools import * # print(compareTimestamp(111,222)) time.showNowTime() # now time is XX:XX:XX

9c836060b9b7e80140ebb8a9cc363bc2e1d5ff72

py

Python

basis_set_exchange/cli/bse_cli.py

atomse/basis_set_exchange

7ffd64082c14d2f61eb43f1c2d44792e8b0e394e

basis_set_exchange/cli/bse_cli.py

atomse/basis_set_exchange

7ffd64082c14d2f61eb43f1c2d44792e8b0e394e

basis_set_exchange/cli/bse_cli.py

atomse/basis_set_exchange

7ffd64082c14d2f61eb43f1c2d44792e8b0e394e

''' Command line interface for the basis set exchange ''' import argparse import argcomplete from .. import version from .bse_handlers import bse_cli_handle_subcmd from .check import cli_check_normalize_args from .complete import (cli_case_insensitive_validator, cli_family_completer, cli_role_completer, cli_bsname_completer, cli_write_fmt_completer, cli_read_fmt_completer, cli_reffmt_completer) def run_bse_cli(): ################################################################################################ # NOTE: I am deliberately not using the 'choices' argument in add_argument. I could use it # for formats, etc, however I wouldn't want to use it for basis set names. Therefore, I handle # all of that manually so that error output is consistent and clean ################################################################################################ ######################################## # Main global options ######################################## parser = argparse.ArgumentParser(description='Description of your program') parser.add_argument('-V', action='version', version='basis_set_exchange ' + version()) parser.add_argument('-d', '--data-dir', metavar='PATH', help='Override which data directory to use') parser.add_argument('-o', '--output', metavar='PATH', help='Output to given file rather than stdout') subparsers = parser.add_subparsers(metavar='subcommand', dest='subcmd') subparsers.required = True # https://bugs.python.org/issue9253#msg186387 ######################################## # Listing of data-independent info ######################################## # list-formats subcommand subp = subparsers.add_parser('list-formats', help='Output a list of basis set formats that can be used with obtaining a basis set') subp.add_argument('-n', '--no-description', action='store_true', help='Print only the format names') # list-writer-formats subcommand subp = subparsers.add_parser('list-writer-formats', help='Output a list available basis set formats that can be written') subp.add_argument('-n', '--no-description', action='store_true', help='Print only the format names') # list-reader-formats subp = subparsers.add_parser('list-reader-formats', help='Output a list of basis set formats that can be read') subp.add_argument('-n', '--no-description', action='store_true', help='Print only the format names') # list-ref-formats subcommand subp = subparsers.add_parser('list-ref-formats', help='Output a list all available reference formats and descriptions') subp.add_argument('-n', '--no-description', action='store_true', help='Print only the reference format names') # list-roles subcommand subp = subparsers.add_parser('list-roles', help='Output a list all available roles and descriptions') subp.add_argument('-n', '--no-description', action='store_true', help='Print only the role names') ######################################## # Listing of general info and metadata ######################################## # get-data-dir subparsers.add_parser('get-data-dir', help='Output the default data directory of this package') # list-basis-sets subcommand subp = subparsers.add_parser('list-basis-sets', help='Output a list all available basis sets and descriptions') subp.add_argument('-n', '--no-description', action='store_true', help='Print only the basis set names') subp.add_argument('-f', '--family', help='Limit the basis set list to only the specified family').completer = cli_family_completer subp.add_argument('-r', '--role', help='Limit the basis set list to only the specified role').completer = cli_role_completer subp.add_argument('-s', '--substr', help='Limit the basis set list to only basis sets whose name contains the specified substring') subp.add_argument('-e', '--elements', help='Limit the basis set list to only basis sets that contain all the given elements') # list-families subcommand subparsers.add_parser('list-families', help='Output a list all available basis set families') # lookup-by-role subp = subparsers.add_parser('lookup-by-role', help='Lookup a companion/auxiliary basis by primary basis and role') subp.add_argument('basis', help='Name of the primary basis we want the auxiliary basis for').completer = cli_bsname_completer subp.add_argument('role', help='Role of the auxiliary basis to look for').completer = cli_role_completer ################################# # Output of info ################################# # get-basis subcommand subp = subparsers.add_parser('get-basis', help='Output a formatted basis set') subp.add_argument('basis', help='Name of the basis set to output').completer = cli_bsname_completer subp.add_argument('fmt', help='Which format to output the basis set as').completer = cli_write_fmt_completer subp.add_argument('--elements', help='Which elements of the basis set to output. Default is all defined in the given basis') subp.add_argument('--version', help='Which version of the basis set to output. Default is the latest version') subp.add_argument('--noheader', action='store_true', help='Do not output the header at the top') subp.add_argument('--unc-gen', action='store_true', help='Remove general contractions') subp.add_argument('--unc-spdf', action='store_true', help='Remove combined sp, spd, ... contractions') subp.add_argument('--unc-seg', action='store_true', help='Remove general contractions') subp.add_argument('--opt-gen', action='store_true', help='Optimize general contractions') subp.add_argument('--make-gen', action='store_true', help='Make the basis set as generally-contracted as possible') # get-refs subcommand subp = subparsers.add_parser('get-refs', help='Output references for a basis set') subp.add_argument('basis', help='Name of the basis set to output the references for').completer = cli_bsname_completer subp.add_argument('reffmt', help='Which format to output the references as').completer = cli_reffmt_completer subp.add_argument('--elements', help='Which elements to output the references for. Default is all defined in the given basis.') subp.add_argument('--version', help='Which version of the basis set to get the references for') # get-info subcommand subp = subparsers.add_parser('get-info', help='Output general info and metadata for a basis set') subp.add_argument('basis', help='Name of the basis set to output the info for').completer = cli_bsname_completer # get-notes subcommand subp = subparsers.add_parser('get-notes', help='Output the notes for a basis set') subp.add_argument('basis', help='Name of the basis set to output the notes for').completer = cli_bsname_completer # get-family subcommand subp = subparsers.add_parser('get-family', help='Output the family of a basis set') subp.add_argument('basis', help='Name of the basis set to output the family for').completer = cli_bsname_completer # get-versions subcommand subp = subparsers.add_parser('get-versions', help='Output a list all available versions of a basis set') subp.add_argument('basis', help='Name of the basis set to list the versions of').completer = cli_bsname_completer subp.add_argument('-n', '--no-description', action='store_true', help='Print only the version numbers') # get-family-notes subcommand subp = subparsers.add_parser('get-family-notes', help='Get the notes of a family of basis sets') subp.add_argument('family', type=str.lower, help='The basis set family to the get the notes of').completer = cli_family_completer ################################# # Converting basis sets ################################# subp = subparsers.add_parser('convert-basis', help='Convert basis set files from one format to another') subp.add_argument('input_file', type=str, help='Basis set file to convert') subp.add_argument('output_file', type=str, help='Converted basis set file') subp.add_argument('--in-fmt', type=str, default=None, help='Input format (default: autodetected from input filename').completer = cli_read_fmt_completer subp.add_argument('--out-fmt', type=str, default=None, help='Output format (default: autodetected from output filename').completer = cli_write_fmt_completer ################################# # Creating bundles ################################# subp = subparsers.add_parser('create-bundle', help='Create a bundle of basis sets') subp.add_argument('fmt', help='Which format to output the basis set as').completer = cli_write_fmt_completer subp.add_argument('reffmt', help='Which format to output the references as').completer = cli_reffmt_completer subp.add_argument('bundle_file', help='Bundle/Archive file to create') subp.add_argument('--archive-type', help='Override the type of archive to create (zip or tbz)') ############################# # DONE WITH SUBCOMMANDS ############################# # setup autocomplete argcomplete.autocomplete(parser, validator=cli_case_insensitive_validator) # Now parse and handle the args args = parser.parse_args() # Check and make sure basis sets, roles, etc, are valid args = cli_check_normalize_args(args) # Actually generate the output output = bse_cli_handle_subcmd(args) if args.output: with open(args.output, 'w', encoding='utf-8') as outfile: outfile.write(output) else: print(output) return 0

92bdca03049e78f08b91682f83e48976672f9a1b

py

Python

utils/get_season_things_price.py

vogelfenx/storagebot

64ab07b068bf645d7cdf5bb1cd5db91c0e2a9228

utils/get_season_things_price.py

vogelfenx/storagebot

64ab07b068bf645d7cdf5bb1cd5db91c0e2a9228

2021-11-24T18:20:00.000Z

2021-11-24T18:31:55.000Z

utils/get_season_things_price.py

vogelfenx/storagebot

64ab07b068bf645d7cdf5bb1cd5db91c0e2a9228

2021-11-24T16:40:28.000Z

2021-11-28T10:40:57.000Z

def get_season_things_price(thing, amount, price): if thing == 'wheel': wheel_price = price[thing]['month'] * amount return f'Стоимость составит {wheel_price}/месяц' else: other_thing_price_week = price[thing]['week'] * amount other_thing_price_month = price[thing]['month'] * amount return f'Стоимость составит {other_thing_price_week} р./неделю' + \ f' или {other_thing_price_month} р./месяц'

92ca0cfb3a6ca200081a09f8a2c36869b58c22cb

py

Python

example/bayesian-methods/data_loader.py

Vikas-kum/incubator-mxnet

ba02bf2fe2da423caa59ddb3fd5e433b90b730bf

2018-11-27T06:00:52.000Z

2022-03-24T09:41:01.000Z

example/bayesian-methods/data_loader.py

Vikas-kum/incubator-mxnet

ba02bf2fe2da423caa59ddb3fd5e433b90b730bf

2017-07-04T17:45:51.000Z

2019-09-12T06:56:27.000Z

example/bayesian-methods/data_loader.py

Vikas-kum/incubator-mxnet

ba02bf2fe2da423caa59ddb3fd5e433b90b730bf

2019-07-12T05:10:25.000Z

2021-07-28T16:19:06.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. from __future__ import print_function import numpy import os import ssl def load_mnist(training_num=50000): data_path = os.path.join(os.path.dirname(os.path.realpath('__file__')), 'mnist.npz') if not os.path.isfile(data_path): from six.moves import urllib origin = ( 'https://github.com/sxjscience/mxnet/raw/master/example/bayesian-methods/mnist.npz' ) print('Downloading data from %s to %s' % (origin, data_path)) ctx = ssl._create_unverified_context() with urllib.request.urlopen(origin, context=ctx) as u, open(data_path, 'wb') as f: f.write(u.read()) print('Done!') dat = numpy.load(data_path) X = (dat['X'][:training_num] / 126.0).astype('float32') Y = dat['Y'][:training_num] X_test = (dat['X_test'] / 126.0).astype('float32') Y_test = dat['Y_test'] Y = Y.reshape((Y.shape[0],)) Y_test = Y_test.reshape((Y_test.shape[0],)) return X, Y, X_test, Y_test def load_toy(): training_data = numpy.loadtxt('toy_data_train.txt') testing_data = numpy.loadtxt('toy_data_test_whole.txt') X = training_data[:, 0].reshape((training_data.shape[0], 1)) Y = training_data[:, 1].reshape((training_data.shape[0], 1)) X_test = testing_data[:, 0].reshape((testing_data.shape[0], 1)) Y_test = testing_data[:, 1].reshape((testing_data.shape[0], 1)) return X, Y, X_test, Y_test def load_synthetic(theta1, theta2, sigmax, num=20): flag = numpy.random.randint(0, 2, (num,)) X = flag * numpy.random.normal(theta1, sigmax, (num,)) \ + (1.0 - flag) * numpy.random.normal(theta1 + theta2, sigmax, (num,)) return X

92ca255eec01c1e82a3ad0136582786783c1c0bd

py

Python

start.py

mickeyckm/nanodegree-freshtomatoes

12776f7e46d6c42a4755a0b81e60eb1a5a65de08

2016-10-13T05:25:36.000Z

2016-10-13T05:25:36.000Z

start.py

mickeyckm/freshtomatoes

12776f7e46d6c42a4755a0b81e60eb1a5a65de08

start.py

mickeyckm/freshtomatoes

12776f7e46d6c42a4755a0b81e60eb1a5a65de08

import os import tmdbsimple as tmdb import media import fresh_tomatoes as ft movies = [] if os.environ.get('TMDB_API', False): # Retrieve API KEY tmdb.API_KEY = os.environ['TMDB_API'] # TMDB Movie Ids movie_ids = [271110, 297761, 246655, 278154, 135397, 188927] # Get Configuration configuration = tmdb.Configuration().info() image_base_url = configuration['images']['secure_base_url'] image_width = "w500" for movie_id in movie_ids: m = tmdb.Movies(movie_id) # Retrieve Image URL minfo = m.info() poster_image_url = image_base_url + image_width + minfo['poster_path'] # Retrieve Youtube Video URL videos = m.videos() video = videos['results'][0] youtube_url = 'https://youtube.com/watch?v=' + video['key'] # Append Movie object movie = media.Movie(m.title) movie.storyline = m.overview movie.poster_url = poster_image_url movie.trailer_url = youtube_url movies.append(movie) else: # Avatar avatar = media.Movie("Avatar") avatar.storyline = ("A paraplegic marine dispatched to the moon Pandora " "on a unique mission becomes torn between following " "his orders and protecting the world he feels is " "his home.") avatar.poster_url = ("https://upload.wikimedia.org/wikipedia/" "en/b/b0/Avatar-Teaser-Poster.jpg") avatar.trailer_url = "https://www.youtube.com/watch?v=-9ceBgWV8io" # Deadpool deadpool = media.Movie("Deadpool") deadpool.storyline = ("A fast-talking mercenary with a morbid sense of " "humor is subjected to a rogue experiment that " "leaves him with accelerated healing powers and a " "quest for revenge.") deadpool.poster_url = ("https://upload.wikimedia.org/wikipedia/en/4/46/" "Deadpool_poster.jpg") deadpool.trailer_url = "https://www.youtube.com/watch?v=gtTfd6tISfw" # Ghostbusters ghostbusters = media.Movie("Ghostbusters") ghostbusters.storyline = ("Following a ghost invasion of Manhattan, " "paranormal enthusiasts Erin Gilbert and Abby " "Yates, nuclear engineer Jillian Holtzmann, " "and subway worker Patty Tolan band together " "to stop the otherworldly threat.") ghostbusters.poster_url = ("https://upload.wikimedia.org/wikipedia/" "en/3/32/Ghostbusters_2016_film_poster.png") ghostbusters.trailer_url = "https://www.youtube.com/watch?v=w3ugHP-yZXw" # Olympus olympus = media.Movie("Olympus Has Fallen") olympus.storyline = ("Disgraced Secret Service agent (and former " "presidential guard) Mike Banning finds himself " "trapped inside the White House in the wake of a " "terrorist attack; using his inside knowledge, " "Banning works with national security to rescue " "the President from his kidnappers.") olympus.poster_url = ("https://upload.wikimedia.org/wikipedia/en/b/bf/" "Olympus_Has_Fallen_poster.jpg") olympus.trailer_url = "https://www.youtube.com/watch?v=vwx1f0kyNwI" # Angry Birds angry_birds = media.Movie("The Angry Birds Movie") angry_birds.storyline = ("Find out why the birds are so angry. When an " "island populated by happy, flightless birds " "is visited by mysterious green piggies, it's " "up to three unlikely outcasts - Red, Chuck " "and Bomb - to figure out what the pigs are up " "to.") angry_birds.poster_url = ("https://upload.wikimedia.org/wikipedia/en/f/" "f9/The_Angry_Birds_Movie_poster.png") angry_birds.trailer_url = "https://www.youtube.com/watch?v=1U2DKKqxHgE" # Ironman ironman = media.Movie("Iron Man") ironman.storyline = ("After being held captive in an Afghan cave, " "billionaire engineer Tony Stark creates a unique " "weaponized suit of armor to fight evil.") ironman.poster_url = ("https://upload.wikimedia.org/wikipedia/en/7/70/" "Ironmanposter.JPG") ironman.trailer_url = "https://www.youtube.com/watch?v=8hYlB38asDY" movies = [avatar, deadpool, ghostbusters, olympus, angry_birds, ironman] ft.open_movies_page(movies)

92d135cd3396bc2bfc2ba5711e29b118672c8503

py

Python

setup.py

dolfim/django-mail-gmailapi

c2f7319329d07d6ecd41e4addc05e47c38fd5e19

setup.py

dolfim/django-mail-gmailapi

c2f7319329d07d6ecd41e4addc05e47c38fd5e19

setup.py

dolfim/django-mail-gmailapi

c2f7319329d07d6ecd41e4addc05e47c38fd5e19

import re from setuptools import setup, find_packages import sys if sys.version_info < (3, 5): raise 'must use Python version 3.5 or higher' with open('./gmailapi_backend/__init__.py', 'r') as f: MATCH_EXPR = "__version__[^'\"]+(['\"])([^'\"]+)" VERSION = re.search(MATCH_EXPR, f.read()).group(2).strip() setup( name='django-gmailapi-backend', version=VERSION, packages=find_packages(), author="Michele Dolfi", author_email="michele.dolfi@gmail.com", license="Apache License 2.0", entry_points={ 'console_scripts': [ 'gmail_oauth2 = gmailapi_backend.bin.gmail_oauth2:main', ] }, install_requires=[ 'google-api-python-client~=2.0', 'google-auth>=1.16.0,<3.0.0dev', ], url="https://github.com/dolfim/django-gmailapi-backend", long_description_content_type='text/markdown', long_description=open('README.md').read(), description='Email backend for Django which sends email via the Gmail API', classifiers=[ 'Intended Audience :: Developers', 'License :: OSI Approved :: Apache Software License', 'Operating System :: MacOS :: MacOS X', 'Operating System :: Microsoft :: Windows', 'Operating System :: POSIX', 'Programming Language :: Python', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Framework :: Django', 'Topic :: Communications :: Email', 'Development Status :: 4 - Beta' ], )

92d2be755f1c0894c43d329732b414de4bf31ab2

py

Python

atcoder/abc132A_fifty_fifty.py

uninhm/kyopro

bf6ed9cbf6a5e46cde0291f7aa9d91a8ddf1f5a3

2020-05-13T01:07:55.000Z

2021-07-13T07:53:26.000Z

atcoder/abc132A_fifty_fifty.py

uninhm/kyopro

bf6ed9cbf6a5e46cde0291f7aa9d91a8ddf1f5a3

2020-05-20T07:22:09.000Z

2021-07-19T03:52:13.000Z

atcoder/abc132A_fifty_fifty.py

uninhm/kyopro

bf6ed9cbf6a5e46cde0291f7aa9d91a8ddf1f5a3

2020-05-11T05:58:36.000Z

2021-12-07T03:20:43.000Z

# Vicfred # https://atcoder.jp/contests/abc132/tasks/abc132_a # implementation S = list(input()) if len(set(S)) == 2: if S.count(S[0]) == 2: print("Yes") quit() print("No")

92e1c91fec4c34f39e9e2622024fad4489b61749

py

Python

scripts/C189/C189Checkin.py

xiaopowanyi/py_scripts

29f240800eefd6e0f91fd098c35ac3c451172ff8

2020-11-14T05:42:49.000Z

2020-11-14T05:43:13.000Z

scripts/C189/C189Checkin.py

J220541674/py_scripts

2b72e23041392a2e5f0a7305d7e9802054978384

scripts/C189/C189Checkin.py

J220541674/py_scripts

2b72e23041392a2e5f0a7305d7e9802054978384

import requests, time, re, rsa, json, base64 from urllib import parse s = requests.Session() username = "" password = "" if(username == "" or password == ""): username = input("账号：") password = input("密码：") def main(): login(username, password) rand = str(round(time.time()*1000)) surl = f'https://api.cloud.189.cn/mkt/userSign.action?rand={rand}&clientType=TELEANDROID&version=8.6.3&model=SM-G930K' url = f'https://m.cloud.189.cn/v2/drawPrizeMarketDetails.action?taskId=TASK_SIGNIN&activityId=ACT_SIGNIN' url2 = f'https://m.cloud.189.cn/v2/drawPrizeMarketDetails.action?taskId=TASK_SIGNIN_PHOTOS&activityId=ACT_SIGNIN' headers = { 'User-Agent':'Mozilla/5.0 (Linux; Android 5.1.1; SM-G930K Build/NRD90M; wv) AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/74.0.3729.136 Mobile Safari/537.36 Ecloud/8.6.3 Android/22 clientId/355325117317828 clientModel/SM-G930K imsi/460071114317824 clientChannelId/qq proVersion/1.0.6', "Referer" : "https://m.cloud.189.cn/zhuanti/2016/sign/index.jsp?albumBackupOpened=1", "Host" : "m.cloud.189.cn", "Accept-Encoding" : "gzip, deflate", } response = s.get(surl,headers=headers) netdiskBonus = response.json()['netdiskBonus'] if(response.json()['isSign'] == "false"): print(f"未签到，签到获得{netdiskBonus}M空间") else: print(f"已经签到过了，签到获得{netdiskBonus}M空间") headers = { 'User-Agent':'Mozilla/5.0 (Linux; Android 5.1.1; SM-G930K Build/NRD90M; wv) AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/74.0.3729.136 Mobile Safari/537.36 Ecloud/8.6.3 Android/22 clientId/355325117317828 clientModel/SM-G930K imsi/460071114317824 clientChannelId/qq proVersion/1.0.6', "Referer" : "https://m.cloud.189.cn/zhuanti/2016/sign/index.jsp?albumBackupOpened=1", "Host" : "m.cloud.189.cn", "Accept-Encoding" : "gzip, deflate", } response = s.get(url,headers=headers) try: if ("errorCode" in response.text): print(response.json()['errorCode']) elif (response.json().has_key('description')): description = response.json()['description'] print(f"抽奖获得{description}") except: print(f"抽奖1完成，解析时失败") try: response2 = s.get(url2,headers=headers) if ("errorCode" in response2.text): print(response.json()['errorCode']) elif (response2.json().has_key('description')): description = response2.json()['description'] print(f"抽奖2获得{description}") except: print(f"抽奖2完成，解析时失败") BI_RM = list("0123456789abcdefghijklmnopqrstuvwxyz") def int2char(a): return BI_RM[a] b64map = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/" def b64tohex(a): d = "" e = 0 c = 0 for i in range(len(a)): if list(a)[i] != "=": v = b64map.index(list(a)[i]) if 0 == e: e = 1 d += int2char(v >> 2) c = 3 & v elif 1 == e: e = 2 d += int2char(c << 2 | v >> 4) c = 15 & v elif 2 == e: e = 3 d += int2char(c) d += int2char(v >> 2) c = 3 & v else: e = 0 d += int2char(c << 2 | v >> 4) d += int2char(15 & v) if e == 1: d += int2char(c << 2) return d def rsa_encode(j_rsakey, string): rsa_key = f"-----BEGIN PUBLIC KEY-----\n{j_rsakey}\n-----END PUBLIC KEY-----" pubkey = rsa.PublicKey.load_pkcs1_openssl_pem(rsa_key.encode()) result = b64tohex((base64.b64encode(rsa.encrypt(f'{string}'.encode(), pubkey))).decode()) return result def calculate_md5_sign(params): return hashlib.md5('&'.join(sorted(params.split('&'))).encode('utf-8')).hexdigest() def login(username, password): url = "https://cloud.189.cn/udb/udb_login.jsp?pageId=1&redirectURL=/main.action" r = s.get(url) captchaToken = re.findall(r"captchaToken' value='(.+?)'", r.text)[0] lt = re.findall(r'lt = "(.+?)"', r.text)[0] returnUrl = re.findall(r"returnUrl = '(.+?)'", r.text)[0] paramId = re.findall(r'paramId = "(.+?)"', r.text)[0] j_rsakey = re.findall(r'j_rsaKey" value="(\S+)"', r.text, re.M)[0] s.headers.update({"lt": lt}) username = rsa_encode(j_rsakey, username) password = rsa_encode(j_rsakey, password) url = "https://open.e.189.cn/api/logbox/oauth2/loginSubmit.do" headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:74.0) Gecko/20100101 Firefox/76.0', 'Referer': 'https://open.e.189.cn/', } data = { "appKey": "cloud", "accountType": '01', "userName": f"{{RSA}}{username}", "password": f"{{RSA}}{password}", "validateCode": "", "captchaToken": captchaToken, "returnUrl": returnUrl, "mailSuffix": "@189.cn", "paramId": paramId } r = s.post(url, data=data, headers=headers, timeout=5) if(r.json()['result'] == 0): print(r.json()['msg']) else: print(r.json()['msg']) redirect_url = r.json()['toUrl'] r = s.get(redirect_url) return s if __name__ == "__main__": main()

92fa730397bfd4949cfd5d8aa12c70a6b5cb5576

py

Python

examples/send_governance_vote_transaction.py

Algofiorg/algofi-py-sdk

6100a6726d36db4d4d3287064f0ad1d0b9a05e03

2021-12-30T02:32:57.000Z

2022-03-23T22:09:16.000Z

examples/send_governance_vote_transaction.py

Algofiorg/algofi-py-sdk

6100a6726d36db4d4d3287064f0ad1d0b9a05e03

2021-11-03T00:14:46.000Z

2022-03-28T02:17:33.000Z

examples/send_governance_vote_transaction.py

Algofiorg/algofi-py-sdk

6100a6726d36db4d4d3287064f0ad1d0b9a05e03

2021-12-15T05:29:55.000Z

2022-02-08T03:45:11.000Z

# This sample is provided for demonstration purposes only. # It is not intended for production use. # This example does not constitute trading advice. import os from dotenv import dotenv_values from algosdk import mnemonic, account from algofi.v1.asset import Asset from algofi.v1.client import AlgofiTestnetClient, AlgofiMainnetClient from algofi.utils import get_ordered_symbols, prepare_payment_transaction, get_new_account from example_utils import print_market_state, print_user_state ### run setup.py before proceeding. make sure the .env file is set with mnemonic + storage_mnemonic. # Hardcoding account keys is not a great practice. This is for demonstration purposes only. # See the README & Docs for alternative signing methods. my_path = os.path.abspath(os.path.dirname(__file__)) ENV_PATH = os.path.join(my_path, ".env") # load user passphrase user = dotenv_values(ENV_PATH) sender = mnemonic.to_public_key(user['mnemonic']) key = mnemonic.to_private_key(user['mnemonic']) # IS_MAINNET IS_MAINNET = False client = AlgofiMainnetClient(user_address=sender) if IS_MAINNET else AlgofiTestnetClient(user_address=sender) # NOTE: Get the live governance address at https://governance.algorand.foundation/api/periods/ # under "sign_up_address" for the relevant governance period # Specify your vote according to the formats that are permissible in the Algorand Foundation Spec # https://github.com/algorandfoundation/governance/blob/main/af-gov1-spec.md # Get the idx, vote choices based on the relevant voting session from https://governance.algorand.foundation/api/periods/ address = sender governance_address = "" vote_note = b'af/gov1:j[6,"a","c"]' # NOTE: an example, not to be used in live voting necessarily vault_address = client.manager.get_storage_address(address) print("~"*100) print("Processing send_governance_vote_transaction transaction for vault address " + vault_address) print("~"*100) txn = client.prepare_send_governance_vote_transactions(governance_address, note=vote_note, address=address) txn.sign_with_private_key(sender, key) txn.submit(client.algod, wait=True) # After sending, check your vote at # https://governance.algorand.foundation/api/periods/<governance-period-slug>/governors/<vault_address> # to confirm successful vote in voting session # print final state print("~"*100) print("Final State") print("Sent governance transaction with note: " + str(vote_note)) print("~"*100)

92feee19e193679cb75cdd6152ceb20caad92e8b

gyp

Python

notification/app/node_modules/hiredis/binding.gyp

c2gconsulting/bulkpay

224a52427f80a71f66613c367a5596cbd5e97294

2015-01-07T03:50:56.000Z

2022-03-21T03:34:12.000Z

binding.gyp

badboy/hiredis-node-win

d113945a182ba1d616f8fba06e2d80dc9f09552b

2015-01-11T09:54:16.000Z

2019-11-21T14:07:43.000Z

binding.gyp

badboy/hiredis-node-win

d113945a182ba1d616f8fba06e2d80dc9f09552b

2015-01-10T20:54:13.000Z

2022-02-02T14:08:01.000Z

{ 'targets': [ { 'target_name': 'hiredis', 'sources': [ 'src/hiredis.cc' , 'src/reader.cc' ], 'include_dirs': ["<!(node -e \"require('nan')\")"], 'dependencies': [ 'deps/hiredis.gyp:hiredis-c' ], 'defines': [ '_GNU_SOURCE' ], 'cflags': [ '-Wall', '-O3' ] } ] }

1300e7747076d34572209fef1029da836f1dbf7b

py

Python

video/cloud-client/quickstart/quickstart.py

nasirdec/GCP-AppEngine-Example

3f5ad26ad2c1e3c8deceb5844adfb40cf7c2e53f

2019-11-17T08:59:14.000Z

2019-11-17T08:59:14.000Z

video/cloud-client/quickstart/quickstart.py

nasirdec/GCP-AppEngine-Example

3f5ad26ad2c1e3c8deceb5844adfb40cf7c2e53f

2019-06-15T00:02:56.000Z

2021-03-25T23:22:38.000Z

video/cloud-client/quickstart/quickstart.py

nasirdec/GCP-AppEngine-Example

3f5ad26ad2c1e3c8deceb5844adfb40cf7c2e53f

2019-02-11T16:16:11.000Z

2019-04-19T21:34:37.000Z

#!/usr/bin/env python # Copyright 2017 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """This application demonstrates label detection on a demo video using the Google Cloud API. Usage: python quickstart.py """ def run_quickstart(): # [START video_quickstart] from google.cloud import videointelligence video_client = videointelligence.VideoIntelligenceServiceClient() features = [videointelligence.enums.Feature.LABEL_DETECTION] operation = video_client.annotate_video( 'gs://demomaker/cat.mp4', features=features) print('\nProcessing video for label annotations:') result = operation.result(timeout=120) print('\nFinished processing.') # first result is retrieved because a single video was processed segment_labels = result.annotation_results[0].segment_label_annotations for i, segment_label in enumerate(segment_labels): print('Video label description: {}'.format( segment_label.entity.description)) for category_entity in segment_label.category_entities: print('\tLabel category description: {}'.format( category_entity.description)) for i, segment in enumerate(segment_label.segments): start_time = (segment.segment.start_time_offset.seconds + segment.segment.start_time_offset.nanos / 1e9) end_time = (segment.segment.end_time_offset.seconds + segment.segment.end_time_offset.nanos / 1e9) positions = '{}s to {}s'.format(start_time, end_time) confidence = segment.confidence print('\tSegment {}: {}'.format(i, positions)) print('\tConfidence: {}'.format(confidence)) print('\n') # [END video_quickstart] if __name__ == '__main__': run_quickstart()

1308f0dd9c15ba9ea58abe836ba21f50ef3863ef

py

Python

homework_05/graficos_3.py

ufpa-organization-repositories/evolutionary-computing

e16786f9619e2b357b94ab91ff3a7b352e6a0d92

homework_05/graficos_3.py

ufpa-organization-repositories/evolutionary-computing

e16786f9619e2b357b94ab91ff3a7b352e6a0d92

homework_05/graficos_3.py

ufpa-organization-repositories/evolutionary-computing

e16786f9619e2b357b94ab91ff3a7b352e6a0d92

# ensaio = [[[[1, 999.4951009067408, 999.495100909791, '1001100.11100010011001100001001', '100011.10010111010000111110100', '1', '1'], [2, 999.5052434400473, 999.5052434497359, '0000100.11100010011001100001001', '111011.10010111010000111110000', '1', '2'], [3, 999.51676448592, 999.516764613072, '0000100.11100010011001100001001', '011011.10010111010000111110100', '1', '3'], [4, 999.5986670278455, 999.5986691897469, '0000100.11100010011001100001001', '001011.10010111010000111110100', '1', '4'], [5, 999.8231043912172, 999.8231154915733, '0000100.11100010011001100001001', '000011.10010111010000111110100', '1', '5'], [6, 999.8507392915436, 999.8507498599146, '0000100.11101010011001100001001', '000011.10010111010000111110100', '1', '6'], [7, 999.8770250807991, 999.8770357110892, '0000100.11101010011001100001001', '000011.10011011010000111110110', '1', '7'], [8, 999.9035511429103, 999.9035563402527, '0000100.11111011011001100001001', '000011.10011011010000111110110', '1', '8'], [9, 999.8985266375895, 999.8985377843169, '0000100.11111011011001100001001', '000011.11011011010000111110110', '1', '9'], [10, 999.9175205241293, 999.9175299982971, '0000100.11111001011001100001001', '000011.11011011010000111110110', '1', '10']]], [[[999.7693956630327, 999.5712824548395, 999.5712938998612, '-1111.1100110000001100100111', '1100.0111101110100011011001101', '2', '1'], [999.772264826825, 999.722709716149, 999.7227150806862, '-1111.1100110000001100000111', '1100.0101101110011011011001101', '2', '2'], [999.772309110711, 999.7568109989896, 999.7568135752206, '-1111.1100110000001100000101', '1100.0101111110011011011001101', '2', '3'], [999.7723098264468, 999.7626773116484, 999.762679240235, '-1111.1100110010001000000111', '1100.0101111110011011011001101', '2', '4'], [999.772309861109, 999.7628189867448, 999.7628208837242, '-1111.1100110010101100000111', '1100.0101111111011011011001101', '2', '5'], [999.7723098614766, 999.7575339099722, 999.7575364450361, '-1111.1100110010011100000111', '1100.0101111111001011011001101', '2', '6'], [999.7723098614781, 999.7330120594124, 999.7330190985555, '-1111.1100110010011100000111', '1100.0101111111001011011101101', '2', '7'], [999.7723098614792, 999.7425919826176, 999.7425978232334, '-1111.1100110010011100000011', '1100.0101111111001011011101101', '2', '8'], [999.7723098614795, 999.7521383886242, 999.7521421922053, '-1111.1100110010011100000011', '1100.0101111111001011011111101', '2', '9'], [999.7723098614797, 999.7479881509024, 999.7479935597561, '-1111.1100110010011100000010', '1100.0101111111001011011111101', '2', '10']]]] ensaio = [[[[999.5055172457077, 999.4950089601775, 999.4950089625081, '1000110.11100010011001100001001', '110011.10010111010000111110100', '1', '1'], [999.5061559955897, 999.5023090273177, 999.502309034424, '1000100.01100010011001100001001', '110111.10010111010000111110110', '1', '2'], [999.5064522811073, 999.503907723421, 999.503907729031, '1000110.11110010001001100001001', '110011.11010111010000111110110', '1', '3'], [999.5121423697065, 999.5035214104588, 999.5035214189329, '1000100.01100010001001100001001', '010111.11010111010000111110110', '1', '4'], [999.5129192569484, 999.5073323118404, 999.5073323302529, '1000100.01100010001001100001001', '010111.01010111010000111110110', '1', '5'], [999.5129217445863, 999.5088300870693, 999.5088303022028, '1000100.01100010001001100001001', '010111.01010011010000111100000', '1', '6'], [999.5129221606866, 999.5109518591257, 999.5109518758048, '1000100.01100010001001100001001', '010111.01010010010000111100000', '1', '7'], [999.5129230124272, 999.512166424112, 999.5121664266934, '1000100.01100000001001100001001', '010111.01010011010000111100000', '1', '8'], [999.5129230131629, 999.5124005902164, 999.5124005938198, '1000100.01100000001001100001001', '010111.01010011010010111100000', '1', '9'], [999.5129230148639, 999.5103974240145, 999.5103976354789, '1000100.01100000001011100001001', '010111.01010011010010111110000', '1', '10'], [999.5129230160566, 999.5122248009202, 999.5122248072961, '1000100.01100000001011100001001', '010111.01010011011010111110000', '1', '11'], [999.5129230160816, 999.5098512171988, 999.5098514317501, '1000100.01100000001011101001001', '010111.01010011011010111111010', '1', '12'], [999.5129230161706, 999.5117481943298, 999.5117482051002, '1000100.01100000001011100001101', '010111.01010011011110111110000', '1', '13'], [999.512923016171, 999.5123140953751, 999.5123140998094, '1000100.01100000001011100000101', '010111.01010011011110111110000', '1', '14'], [999.5129230161734, 999.5118310368094, 999.5118310431579, '1000100.01100000001011100000101', '010111.01010011011110101100000', '1', '15'], [999.5129230161741, 999.5121210327977, 999.5121210375976, '1000100.01100000001011100000101', '010111.01010011011110011000000', '1', '16'], [999.5129230161741, 999.5094388460799, 999.5094390635309, '1000100.01100000001011100001101', '010111.01010011011110011000000', '1', '17'], [999.6136428564632, 999.5131524131325, 999.5131524699873, '0000100.01100000001011100000111', '011111.01010011011110011000000', '1', '18'], [999.6171227592827, 999.5505819522255, 999.5505841236918, '0000100.00100000001011100000111', '011111.01010011011110011000000', '1', '19'], [999.6260388885507, 999.6021087614022, 999.6021098942948, '0000100.00100000001011100001111', '011111.00010011011110011000000', '1', '20'], [999.6264039047687, 999.6120960828682, 999.6120968350307, '0000100.01000000001011100001111', '011111.00010011011110011000000', '1', '21'], [999.8211587180026, 999.6202616252683, 999.6202623370596, '0000100.01000000101011100001111', '001111.00010011011110011000000', '1', '22'], [999.8217737535546, 999.697569365876, 999.6975767463806, '0000100.01100000101011100001111', '001111.00010011001110011000000', '1', '23'], [999.821774465545, 999.7883631635897, 999.7883680067487, '0000100.01100000101011100001111', '001111.00010011001010011000000', '1', '24'], [999.82177567708, 999.7936505713287, 999.7936562996696, '0000100.01100000101011100001111', '001111.00010011000010011000000', '1', '25'], [999.8217757540084, 999.7949952836876, 999.7949996579591, '0000100.01100000101001100001111', '001111.00010011000010011000000', '1', '26'], [999.8217757867357, 999.770910115756, 999.7709198320904, '0000100.01100000101001100001110', '001111.00010011000010001000000', '1', '27'], [999.8217760768566, 999.7999669197359, 999.7999704691948, '0000100.01100000100001100001111', '001111.00010011000010001000000', '1', '28'], [999.8217761040349, 999.7895584591176, 999.7895643944065, '0000100.01100000100000100001111', '001111.00010011000010001100000', '1', '29'], [999.8217763006218, 999.8015467435569, 999.8015498310361, '0000100.01100000100001100001111', '001111.00010011000000001100000', '1', '30'], [999.821777162837, 999.8026923323965, 999.8026955300638, '0000100.01100000000000100001111', '001111.00010011000000001100000', '1', '31'], [999.8217771727744, 999.7826338356463, 999.7826402977803, '0000100.01100000000000000001111', '001111.00010011000000001100000', '1', '32'], [999.8217771730834, 999.7954080350157, 999.7954132850714, '0000100.01100000000000000000111', '001111.00010011000000001100000', '1', '33'], [999.8217771814129, 999.7891788101246, 999.7891832957444, '0000100.01100000000000000001011', '001111.00010011000000000100000', '1', '34'], [999.8217771814129, 999.779756867161, 999.7797618660151, '0000100.01100000000000000001011', '001111.00010011000000000100000', '1', '35'], [999.8217771859341, 999.7965076465391, 999.7965124112385, '0000100.01100000000000000000011', '001111.00010011000000000000000', '1', '36'], [999.8217771859341, 999.7767424591482, 999.7767507895039, '0000100.01100000000000000000011', '001111.00010011000000000000000', '1', '37'], [999.8217771859341, 999.7955815446758, 999.7955854201596, '0000100.01100000000000000000011', '001111.00010011000000000000000', '1', '38'], [999.8217771860104, 999.8015952900396, 999.8015986343482, '0000100.01100000000000000000001', '001111.00010011000000000000000', '1', '39'], [999.8217771860104, 999.7934819396916, 999.7934871695738, '0000100.01100000000000000000001', '001111.00010011000000000000000', '1', '40'], [999.8217771860486, 999.7773839039404, 999.7773933561947, '0000100.01100000000000000000000', '001111.00010011000000000000000', '1', '41'], [999.8217771860486, 999.783660016008, 999.7836662811018, '0000100.01100000000000000000000', '001111.00010011000000000000000', '1', '42'], [999.8217771860486, 999.7958411966919, 999.795845719919, '0000100.01100000000000000000000', '001111.00010011000000000000000', '1', '43'], [999.8217771860486, 999.7972260972415, 999.7972300549476, '0000100.01100000000000000000000', '001111.00010011000000000000000', '1', '44'], [999.8217771860486, 999.7875592201804, 999.7875655527954, '0000100.01100000000000000000000', '001111.00010011000000000000000', '1', '45'], [999.8217771860486, 999.7986952413885, 999.7986981703359, '0000100.01100000000000000000000', '001111.00010011000000000000000', '1', '46'], [999.8368643971163, 999.7873402119594, 999.7873465619066, '0000110.01100000000000000000000', '001011.00010011000000000000000', '1', '47'], [999.8539918915938, 999.743968963303, 999.7439774564771, '0000110.01000000000000000000000', '001011.00010011000000000000000', '1', '48'], [999.8718376250218, 999.8329135403696, 999.8329160040116, '0000110.00000000000000000000000', '001011.00010011000000000001000', '1', '49'], [999.8730076853732, 999.8170345524384, 999.8170444276267, '0000110.00000000000000000000000', '001011.00000111000000000000000', '1', '50'], [999.8730079454864, 999.8534036100392, 999.8534080537578, '0000110.00000000000100000000000', '001011.00000111000000000000000', '1', '51'], [999.8730094220132, 999.8254442447443, 999.8254545384234, '0000110.00000000000100000000000', '001011.00000111100000000000000', '1', '52'], [999.8730094609027, 999.8240493025111, 999.8240596888387, '0000110.00000000000000000000010', '001011.00000111100000000000000', '1', '53'], [999.8730094609308, 999.8567791347726, 999.8567827934108, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '54'], [999.8730094609308, 999.8250568887524, 999.8250663348676, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '55'], [999.8730094609308, 999.8330185330742, 999.8330279534193, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '56'], [999.8730094609308, 999.8252124106773, 999.8252255327653, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '57'], [999.8730094609308, 999.8392233081582, 999.839230947986, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '58'], [999.8730094609308, 999.8523466142693, 999.8523506989067, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '59'], [999.8730094609308, 999.8497053440487, 999.8497109413688, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '60'], [999.8730094609308, 999.8437574953132, 999.8437620179748, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '61'], [999.8730094609308, 999.8509939903805, 999.850997999749, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '62'], [999.8730094609308, 999.8342054835687, 999.8342140911984, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '63'], [999.8730094609308, 999.8243653301047, 999.8243759247314, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '64'], [999.8730094609308, 999.8458875734631, 999.8458915389679, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '65'], [999.8730094609308, 999.8091485027719, 999.8091642934783, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '66'], [999.8730094609308, 999.840855350452, 999.8408632817996, 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'0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '74'], [999.8730094609308, 999.8456758352268, 999.8456828038658, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '75'], [999.8730094609308, 999.8196782007191, 999.8196884936841, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '76'], [999.8730094609308, 999.8441604144226, 999.8441675238747, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '77'], [999.8730094609308, 999.8310132904959, 999.8310222173927, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '78'], [999.8730094609308, 999.8408824791213, 999.8408885346764, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '79'], [999.8730094609308, 999.8241164986337, 999.8241269556786, '0000110.00000000000000000000000', '001011.00000111100000000000000', '1', '80'], [999.8730094609308, 999.833255096412, 999.8332647952477, 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'50', '96'], [999.6878968594276, 999.6619993921432, 999.6620030672873, '10111.011110001101110111111111', '-1001.0000111100100000111', '50', '97'], [999.6878968594276, 999.6767364740043, 999.6767381465787, '10111.011110001101110111111111', '-1001.0000111100100000111', '50', '98'], [999.6878968594276, 999.6674371363, 999.6674397163673, '10111.011110001101110111111111', '-1001.0000111100100000111', '50', '99'], [999.6878968594276, 999.6818107105054, 999.6818115173727, '10111.011110001101110111111111', '-1001.0000111100100000111', '50', '100']]]] fitness = [] media = [] desvio = [] experimento_plot = [] from matplotlib import pyplot as plt import numpy as np for index, experimento in enumerate(ensaio): for populacao in experimento: for x, individuo in enumerate(populacao): fitness.append(individuo[0]) media.append(individuo[1]) desvio.append(individuo[2]) x = np.arange(1, fitness.__len__() + 1) plt.plot(x, fitness) experimento_plot.append([fitness, media, desvio]) fitness = [] media = [] desvio = [] plt.show()

130f0d527db89218f9714b016db75a6b60750779

py

Python

setup.py

Ms2ger/python-zstandard

b8ea1f6722a710e252b452554442b84c81049439

setup.py

Ms2ger/python-zstandard

b8ea1f6722a710e252b452554442b84c81049439

setup.py

Ms2ger/python-zstandard

b8ea1f6722a710e252b452554442b84c81049439

#!/usr/bin/env python # Copyright (c) 2016-present, Gregory Szorc # All rights reserved. # # This software may be modified and distributed under the terms # of the BSD license. See the LICENSE file for details. import os import sys from setuptools import setup try: import cffi except ImportError: cffi = None import setup_zstd SUPPORT_LEGACY = False SYSTEM_ZSTD = False WARNINGS_AS_ERRORS = False if os.environ.get('ZSTD_WARNINGS_AS_ERRORS', ''): WARNINGS_AS_ERRORS = True if '--legacy' in sys.argv: SUPPORT_LEGACY = True sys.argv.remove('--legacy') if '--system-zstd' in sys.argv: SYSTEM_ZSTD = True sys.argv.remove('--system-zstd') if '--warnings-as-errors' in sys.argv: WARNINGS_AS_ERRORS = True sys.argv.remote('--warning-as-errors') # Code for obtaining the Extension instance is in its own module to # facilitate reuse in other projects. extensions = [ setup_zstd.get_c_extension(name='zstd', support_legacy=SUPPORT_LEGACY, system_zstd=SYSTEM_ZSTD, warnings_as_errors=WARNINGS_AS_ERRORS), ] install_requires = [] if cffi: import make_cffi extensions.append(make_cffi.ffi.distutils_extension()) # Need change in 1.10 for ffi.from_buffer() to handle all buffer types # (like memoryview). # Need feature in 1.11 for ffi.gc() to declare size of objects so we avoid # garbage collection pitfalls. install_requires.append('cffi>=1.11') version = None with open('c-ext/python-zstandard.h', 'r') as fh: for line in fh: if not line.startswith('#define PYTHON_ZSTANDARD_VERSION'): continue version = line.split()[2][1:-1] break if not version: raise Exception('could not resolve package version; ' 'this should never happen') setup( name='zstandard', version=version, description='Zstandard bindings for Python', long_description=open('README.rst', 'r').read(), url='https://github.com/indygreg/python-zstandard', author='Gregory Szorc', author_email='gregory.szorc@gmail.com', license='BSD', classifiers=[ 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', 'License :: OSI Approved :: BSD License', 'Programming Language :: C', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', ], keywords='zstandard zstd compression', packages=['zstandard'], ext_modules=extensions, test_suite='tests', install_requires=install_requires, )

130f1aca25388c2ce8dd308d2bb872e5263f8305

py

Python

Escolas/Curso em Video/Back-End/Curso de Python/Mundos/Mundo 01/Exercicio_16.py

c4st1lh0/Projetos-de-Aula

e8abc9f4bce6cc8dbc6d7fb5da0f549ac8ef5302

Escolas/Curso em Video/Back-End/Curso de Python/Mundos/Mundo 01/Exercicio_16.py

c4st1lh0/Projetos-de-Aula

e8abc9f4bce6cc8dbc6d7fb5da0f549ac8ef5302

Escolas/Curso em Video/Back-End/Curso de Python/Mundos/Mundo 01/Exercicio_16.py

c4st1lh0/Projetos-de-Aula

e8abc9f4bce6cc8dbc6d7fb5da0f549ac8ef5302

import math num = float(input('Digite um numero real qualquer: ')) print('O numero: {} tem a parte inteira {}'.format(num, math.trunc(num)))

13178607e92d499e0a8fa091130826ae93f57d37

py

Python

setup.py

Liang813/einops

9edce3d9a2d0a2abc51a6aaf86678eac43ffac0c

2018-10-30T08:38:50.000Z

2022-03-31T17:35:50.000Z

setup.py

Liang813/einops

9edce3d9a2d0a2abc51a6aaf86678eac43ffac0c

2018-10-30T09:04:01.000Z

2022-03-27T11:27:30.000Z

setup.py

Liang813/einops

9edce3d9a2d0a2abc51a6aaf86678eac43ffac0c

2018-11-09T02:50:30.000Z

2022-03-30T05:46:44.000Z

__author__ = 'Alex Rogozhnikov' from setuptools import setup setup( name="einops", version='0.3.2', description="A new flavour of deep learning operations", long_description=open('README.md', encoding='utf-8').read(), long_description_content_type='text/markdown', url='https://github.com/arogozhnikov/einops', author='Alex Rogozhnikov', packages=['einops', 'einops.layers'], classifiers=[ 'Intended Audience :: Science/Research', 'Programming Language :: Python :: 3 ', ], keywords='deep learning, neural networks, tensor manipulation, machine learning, ' 'scientific computations, einops', install_requires=[ # no run-time or installation-time dependencies ], )

1321da1b77c6741566badad243b4f02ccf184f31

py

Python

src/plot_timeseries_outstanding_bytes.py

arunksaha/heap_tracker

0755c6b9c3e4e621efda31c144421a1e67e51a9c