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import seaborn as sns
import matplotlib.pyplot as plt
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import numpy as np
def f_get_results_plot_seaborn(data, title, graph_size=20):
fig = plt.figure(figsize=(15, 9))
ax = fig.add_subplot()
ax.plot(data['epochs'], data['train_loss'], color='salmon', label='train loss')
ax2 = ax.twinx()
ax2.plot(data['epochs'], data['train_cost'], color='cornflowerblue', label='train cost')
ax2.plot(data['epochs'], data['val_cost'], color='darkblue', label='val cost')
if graph_size == 20:
am_val = 6.4
else:
am_val = 10.98
plt.axhline(y=am_val, color='black', linestyle='--', linewidth=1.5, label='AM article best score')
fig.legend(loc="upper right", bbox_to_anchor=(1,1), bbox_transform=ax.transAxes)
ax.set_ylabel('Loss')
ax2.set_ylabel('Cost')
ax.set_xlabel('Epochs')
ax.grid(False)
ax2.grid(False)
ax2.set_yticks(np.arange(min(data['val_cost'].min(), data['train_cost'].min())-0.2,
max(data['val_cost'].max(), data['train_cost'].max())+0.1,
0.1).round(2))
plt.title('Learning Curve: ' + title)
plt.show()
def f_get_results_plot_plotly(data, title, graph_size=20):
# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
fig.add_trace(
go.Scatter(x=data['epochs'], y=data['train_loss'], name="train loss", marker_color='salmon'),
secondary_y=False,
)
fig.add_trace(
go.Scatter(x=data['epochs'], y=data['train_cost'], name="train cost", marker_color='cornflowerblue'),
secondary_y=True,
)
fig.add_trace(
go.Scatter(x=data['epochs'], y=data['val_cost'], name="val cost", marker_color='darkblue'),
secondary_y=True,
)
# Add figure title
fig.update_layout(
title_text="Learning Curve: " + title,
width=950,
height=650,
# plot_bgcolor='rgba(0,0,0,0)'
template="plotly_white"
)
# Set x-axis title
fig.update_xaxes(title_text="Number of epoch")
# Set y-axes titles
fig.update_yaxes(title_text="<b>Loss", secondary_y=False, showgrid=False, zeroline=False)
fig.update_yaxes(title_text="<b>Cost", secondary_y=True, dtick=0.1)#, nticks=20)
fig.show() |