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Functions.py
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Functions.py
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import pandas as pd
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
import os
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
def plot_set_experiments(experimetal_data_dictionary):
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
name = experimetal_data_dictionary['name']
del experimetal_data_dictionary['name']
marker = ['s', 'o', '^', '*']
color = ['red', 'blue']
fig, ax1 = plt.subplots()
ax1.grid()
ax2 = ax1.twinx()
for i in range(len(experimetal_data_dictionary)):
x = experimetal_data_dictionary[i].iloc[:,0].to_numpy()
y1 = experimetal_data_dictionary[i].iloc[:,1].to_numpy()
y2 = 6 - experimetal_data_dictionary[i].iloc[:,2].to_numpy()
ax1.set_xlabel('Time (s)')
ax1.set_ylabel('Force [N]')
ax1.plot(x, y1, color = color[0], marker = marker[i], markevery = 1500)
ax2.set_ylabel('Displacement [mm]')
ax2.plot(x, y2, color = color[1], marker = marker[i], markevery = 1500)
ax1.set_xlim(0,1000)
ax1.set_ylim(0,600)
sfile = 'Graphics'
if os.path.exists(sfile) == False:
os.makedirs(sfile)
fig.savefig(sfile + '/' + name + '_experimental_data.png')
experimetal_data_dictionary['name'] = name
def plot_statistical_analysis(experimetal_data_dictionary):
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
name = experimetal_data_dictionary['name']
del experimetal_data_dictionary['name']
fig, ax1 = plt.subplots()
ax1.set_ylim(0,600)
ax1.set_xlim(0,900)
ax1.grid()
ax2 = ax1.twinx()
x_ = np.arange(0, 890, 0.01)
columns1 = ['y1_' + str(i) for i in range(len(experimetal_data_dictionary))] + ['Time (s)']
df_force = pd.DataFrame(columns = columns1)
columns2 = ['y2_' + str(i) for i in range(len(experimetal_data_dictionary))] + ['Time (s)']
df_displacement = pd.DataFrame(columns = columns2)
for i in range(len(experimetal_data_dictionary)):
x = experimetal_data_dictionary[i].iloc[:,0].to_numpy() - experimetal_data_dictionary[i].iloc[0,0]
y1 = experimetal_data_dictionary[i].iloc[:,1].to_numpy()
y2 = 6 - experimetal_data_dictionary[i].iloc[:,2].to_numpy()
interp_func_1 = interp1d(x, y1)
interp_func_2 = interp1d(x, y2)
df_force['y1_' + str(i)] = interp_func_1(x_)
df_displacement['y2_' + str(i)] = interp_func_2(x_)
ax1.set_xlabel('Time (s)')
ax1.set_ylabel('Force [N]')
ax1.plot(x_, df_force.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1).to_numpy(), color = 'red', label = 'Force [N]')
ax1.fill_between(x_, df_force.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1).to_numpy() - df_force.iloc[:, 0:len(experimetal_data_dictionary)].std(axis = 1).to_numpy(),
df_force.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1).to_numpy() + df_force.iloc[:, 0:len(experimetal_data_dictionary)].std(axis = 1).to_numpy(),
color = 'red', alpha = 0.4)
ax2.set_ylabel('Displacement [mm]')
ax2.plot(x_, df_displacement.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1).to_numpy(), color = 'blue', label = 'Displacement [mm')
ax2.fill_between(x_, df_displacement.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1).to_numpy() - df_displacement.iloc[:, 0:len(experimetal_data_dictionary)].std(axis = 1).to_numpy(),
df_displacement.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1).to_numpy() + df_displacement.iloc[:, 0:len(experimetal_data_dictionary)].std(axis = 1).to_numpy(),
color = 'blue', alpha = 0.4)
fig.legend(loc='upper right', bbox_to_anchor=(0.9, 0.9))
sfile = 'Graphics'
if os.path.exists(sfile) == False:
os.makedirs(sfile)
fig.savefig(sfile + '/' + name + '_statistical.png')
experimetal_data_dictionary['name'] = name
df = pd.DataFrame()
df['Time'] = x_
df['Force-mean'] = df_force.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1)
df['Force-std'] = df_force.iloc[:, 0:len(experimetal_data_dictionary)].std(axis = 1)
df['Displacement-mean'] = df_displacement.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1)
df['Displacement-std'] = df_displacement.iloc[:, 0:len(experimetal_data_dictionary)].std(axis = 1)
sfile = 'Spreadsheet'
if os.path.exists(sfile) == False:
os.makedirs(sfile)
df_force = df_force[(df_force['Time (s)'] > 210) & (df_force['Time (s)'] < 320)]
df_force['Average'] = df_force.iloc[:, 0:len(experimetal_data_dictionary)].mean(axis = 1)
df_force.to_csv(sfile + '/' + 'output' + str(name) + '.csv', columns=['Average','Time (s)'],index=False)
return df
def comparison_plot(data_dictionary):
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True
fig, ax1 = plt.subplots()
ax1.set_ylim(0,600)
ax1.set_xlim(0,900)
ax1.grid()
ax2 = ax1.twinx()
for i in range(len(data_dictionary)):
x = data_dictionary[i]['Time'].to_numpy()
y1 = data_dictionary[i]['Force-mean'].to_numpy()
y2 = data_dictionary[i]['Displacement-mean'].to_numpy()
y1_std = data_dictionary[i]['Force-std'].to_numpy()
y2_std = data_dictionary[i]['Displacement-std'].to_numpy()
ax1.plot(x, y1)
ax2.plot(x, y2)
# NAO FUNCIONA!
ax1.fill_between(x, y1 - y1_std,
y1 + y1_std,
color = 'red', alpha = 0.4)