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import numpy as np
import streamlit as st
import funcs
import pandas as pd
import getpass
# import pymysql
import matplotlib.pyplot as plt
from sqlalchemy import create_engine
def variogram(nugget=0.0, srange=100., struct_type='Spherical'):
var = 1.-nugget
h = np.arange(0,150.,5.)
gamma = h
if struct_type == 'Spherical':
gamma = nugget + var*((3*h)/(2*srange)-(h**3)/(2*srange**3))
gamma[h>srange]=1.0
gamma[0] = nugget
elif struct_type == 'Power':
gamma = nugget + var*(h/srange)**1.5
else:
gamma = var*(1.0-np.cos((h**2/srange**2)*np.pi)*np.exp((-3*h)/(srange*1.2))) + nugget
return gamma, h;
def ex_var(example=1,
hint='Hint: Contrary to popular flat earther beliefs.',
key_nugget='nug1', key_range='range1', key_stype='stype1',
im='sim1.jpg'):
st.markdown("### Example " + str(example) + ":")
st.markdown(hint)
col1, col2 = st.beta_columns([1, 2])
with col1:
struct_type = st.selectbox("Structure Type", options=["Spherical", "Power", "Hole Effect"], index=0, key=key_stype)
nugget = st.slider('Nugget', 0.0, 1.0, 0.1, 0.05, key=key_nugget)
srange = st.slider('Range', 0.0, 120., 100., 10., key=key_range)
gamma, h = variogram(nugget, srange, struct_type)
fig, ax = plt.subplots()
plt.plot([0, 120.], [1.0, 1.0], '--k')
plt.plot(h, gamma, '-r')
plt.xlabel('Range (m)')
plt.ylabel('Gamma')
plt.xlim((0.,120.))
plt.ylim((0.,1.5))
st.pyplot(fig)
with col2:
st.write("")
st.write("")
st.write("")
st.image("images//" + im, width=500)
return struct_type, nugget, srange
def variograms():
st.title("Variogram Exercise")
st.write("")
st.markdown("## Model the appropriate variogram for each grade pattern observed")
text = funcs.get_text_block("variography_intro.txt")
st.markdown(text)
results = []
s,n,r = ex_var(example=1,
hint='Hint: Contrary to popular flat earther beliefs.',
key_nugget='nug1', key_range='range1', key_stype='stype1',
im='sim1.jpg')
results.append([1, s,n,r])
s,n,r = ex_var(example=2,
hint='Hint: Think about the seasons.',
key_nugget='nug2', key_range='range2', key_stype='stype2',
im='sim2.jpg')
results.append([2, s,n,r])
s,n,r = ex_var(example=3,
hint='Hint: Think about sand...',
key_nugget='nug3', key_range='range3', key_stype='stype3',
im='sim3.jpg')
results.append([3, s,n,r])
s,n,r = ex_var(example=4,
hint='Hint: This is when you wonder why you bother to get out of bed in the morning.',
key_nugget='nug4', key_range='range4', key_stype='stype4',
im='sim4.jpg')
results.append([4, s,n,r])
df = pd.DataFrame(data=results,
columns=['Example', 'Structure Type', 'Nugget', 'Range'])
uname = getpass.getuser()
st.table(df)
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