# Import libraries
import pandas as pd
import streamlit as st
import matplotlib.pyplot as plt
#----------------------- Stress - Strain-----------------------
# Load data from source file
df = pd.read_excel(
    io = 'MRE.xlsx',
    engine='openpyxl',
    sheet_name='Sheet1',
    skiprows=0,
    usecols='A:E',
    nrows=11168,
)
#SIDEBAR -> add things that can be filtered for
st.sidebar.header('Enter filter for Stress and Strain display')
spec = st.sidebar.multiselect(
    'Select spec:',
    options=df['Spec'].unique(),
    default=df['Spec'].unique()
)
df_selection = df.query(
    'Spec == @spec'
)
# Plot data and add legend, title, ...
fig = plt.figure()
ax = fig.add_subplot()
df_selection.groupby("Spec").plot(x="Average strain (%)",
                                  y="Average stress (MPa)",
                                  legend=False,
                                  ax=ax,
                                  linewidth = 0.65,
                                  figsize=(10,6))
plt.xlabel('Strain (%/100)')
plt.ylabel('Stress (MPa)')
plt.title('Stress-Strain diagram')
plt.grid(visible=True)
# Shrink current axis's height by 10% on the bottom
# box = ax.get_position()
# ax.set_position([box.x0, box.y0 + box.height * 0.1,
#                   box.width, box.height * 0.9])
# # Put a legend below current axis
plt.legend(df_selection['Spec'].unique(),loc='upper center', bbox_to_anchor=(0.5, -0.15),
          ncol=5)
plt.show()
st.pyplot(fig)

t = pd.DataFrame();
u = pd.DataFrame();
    values = range(0,len(spec));
for i in values:
    t[i] = new_df_strain.iloc[:,i];
    u[i] = new_df_stress.iloc[:,i];
t2 = t.set_axis(axis = 1, labels = spec, inplace=False);
u2 = u.set_axis(axis = 1, labels = spec, inplace=False);
# Plot data and add legend, title, ...
fig = plt.figure();
plt.rcParams['font.size'] = 35;
ax = fig.add_subplot();
plt.plot(t2,
     u2,
     linewidth = 1.5,);
plt.xlabel('Strain (%)');
plt.ylabel('Stress (MPa)');