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171 | import customtkinter
import seaborn as sns
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import matplotlib.pyplot as plt
from matplotlib.figure import Figure
import json
import tkinter
import numpy as np
class ModelPlots(customtkinter.CTkToplevel):
def __init__(self, parent):
super().__init__(parent)
self.parent = parent
self.title("Model Plots")
posx = int(self.winfo_screenwidth()/2 - 400)
posy = int(self.winfo_screenheight()/2 - 300)
self.geometry("800x600+{}+{}".format(posx, posy))
self.grab_set()
self.focus_set()
self.resizable(True, True)
with open(f'models/ups_metrics.json', 'r') as f:
self.ups_metrics = json.load(f)
with open(f'models/num_comments_metrics.json', 'r') as f:
self.num_comments_metrics = json.load(f)
self.create_widgets()
def create_widgets(self):
self.tabview = customtkinter.CTkTabview(self)
self.tabview.add('R-Squares')
self.tabview.add('MAE')
self.tabview.add('MSE')
self.tabview.add('R-Square Comparison')
self.tabview.add('Predictions')
self.tabview.add('Residuals')
# R-Squares
fig, ax = plt.subplots(1, 2, figsize=(15, 3), dpi=36)
ups_m = {}
for k, v in self.ups_metrics.items():
ups_m[k] = v['r2']
sns.barplot(x=list(ups_m.keys()), y=list(ups_m.values()), ax=ax[0], palette='Blues_d')
ax[0].set_title('R-Square for Ups')
num_comments_m = {}
for k, v in self.num_comments_metrics.items():
num_comments_m[k] = v['r2']
sns.barplot(x=list(num_comments_m.keys()), y=list(num_comments_m.values()), ax=ax[1], palette='Greens_d')
ax[1].set_title('R-Square for Number of Comments')
for i in range(2):
ax[i].set_xticklabels(ax[i].get_xticklabels(), rotation=45)
self.r2plot = FigureCanvasTkAgg(fig, self.tabview.tab('R-Squares'))
self.r2plot.figure.tight_layout()
self.r2plot.get_tk_widget().pack(side=tkinter.TOP, fill=tkinter.BOTH, expand=1)
# MAE
fig, ax = plt.subplots(1, 2, figsize=(15, 3), dpi=36)
ups_m = {}
for k, v in self.ups_metrics.items():
ups_m[k] = v['mae']
sns.barplot(x=list(ups_m.keys()), y=list(ups_m.values()), ax=ax[0], palette='Reds_d')
ax[0].set_title('MAE for Ups')
num_comments_m = {}
for k, v in self.num_comments_metrics.items():
num_comments_m[k] = v['mae']
sns.barplot(x=list(num_comments_m.keys()), y=list(num_comments_m.values()), ax=ax[1], palette='Oranges_d')
ax[1].set_title('MAE for Number of Comments')
for i in range(2):
ax[i].set_xticklabels(ax[i].get_xticklabels(), rotation=45)
self.maeplot = FigureCanvasTkAgg(fig, self.tabview.tab('MAE'))
self.maeplot.figure.tight_layout()
self.maeplot.get_tk_widget().pack(side=tkinter.TOP, fill=tkinter.BOTH, expand=1)
# MSE
fig, ax = plt.subplots(1, 2, figsize=(15, 3), dpi=36)
ups_m = {}
for k, v in self.ups_metrics.items():
ups_m[k] = v['mse']
sns.barplot(x=list(ups_m.keys()), y=list(ups_m.values()), ax=ax[0], palette='Purples_d')
ax[0].set_title('MSE for Ups')
num_comments_m = {}
for k, v in self.num_comments_metrics.items():
num_comments_m[k] = v['mse']
sns.barplot(x=list(num_comments_m.keys()), y=list(num_comments_m.values()), ax=ax[1], palette='Greys_d')
ax[1].set_title('MSE for Number of Comments')
for i in range(2):
ax[i].set_xticklabels(ax[i].get_xticklabels(), rotation=45)
self.mseplot = FigureCanvasTkAgg(fig, self.tabview.tab('MSE'))
self.mseplot.figure.tight_layout()
self.mseplot.get_tk_widget().pack(side=tkinter.TOP, fill=tkinter.BOTH, expand=1)
# R-Square Comparison
fig, ax = plt.subplots(1, 2, figsize=(20, 5), dpi=36)
# Ups
ax[0].set_title('Ups')
ax[0].set_xlabel('Model')
ax[0].set_ylabel('R2 Score')
sns.barplot(x=list(self.ups_metrics.keys()), y=[r2['r2'] for r2 in self.ups_metrics.values()], ax=ax[0], palette='Blues_d')
ax[0].set_xticklabels(ax[0].get_xticklabels(), rotation=45)
# Number of Comments
ax[1].set_title('Number of Comments')
ax[1].set_xlabel('Model')
ax[1].set_ylabel('R2 Score')
sns.barplot(x=list(self.num_comments_metrics.keys()), y=[r2['r2'] for r2 in self.num_comments_metrics.values()], ax=ax[1], palette='Greens_d')
ax[1].set_xticklabels(ax[1].get_xticklabels(), rotation=45)
self.r2comparisonplot = FigureCanvasTkAgg(fig, self.tabview.tab('R-Square Comparison'))
self.r2comparisonplot.figure.tight_layout()
self.r2comparisonplot.get_tk_widget().pack(side=tkinter.TOP, fill=tkinter.BOTH, expand=1)
# Predictions
fig, ax = plt.subplots(7, 2, figsize=(12, 16), dpi=24)
for i, (k, v) in enumerate(self.ups_metrics.items()):
# ups
ax[i, 0].set_title('Ups - {}'.format(k))
ax[i, 0].set_xlabel('Actual')
ax[i, 0].set_ylabel('Predicted')
sns.regplot(x=v['actual'], y=v['pred'], ax=ax[i, 0], color='blue', scatter_kws={'alpha': 0.3})
# num_comments
ax[i, 1].set_title('Number of Comments - {}'.format(k))
ax[i, 1].set_xlabel('Actual')
ax[i, 1].set_ylabel('Predicted')
sns.regplot(x=self.num_comments_metrics[k]['actual'], y=self.num_comments_metrics[k]['pred'], ax=ax[i, 1], color='green', scatter_kws={'alpha': 0.3})
self.predplot = FigureCanvasTkAgg(fig, self.tabview.tab('Predictions'))
self.predplot.figure.tight_layout()
self.predplot.get_tk_widget().pack(side=tkinter.TOP, fill=tkinter.BOTH, expand=1)
# Residuals
fig, ax = plt.subplots(7, 6, figsize=(20, 16), dpi=16)
for i, (k, v) in enumerate(self.ups_metrics.items()):
# ups model
ax[i, 0].set_title(k + ' - Ups Residuals')
ax[i, 0].set_xlabel('Residuals')
ax[i, 0].set_ylabel('Frequency')
sns.distplot(np.array(v['actual']) - np.array(v['pred']), ax=ax[i, 0], color='blue', kde=False)
ax[i, 1].set_title(k + ' Ups Test Scores')
ax[i, 1].set_xlabel('Ups')
ax[i, 1].set_ylabel('Frequency')
sns.distplot(v['actual'], ax=ax[i, 1], color='blue', kde=False)
ax[i, 2].set_title(k + ' Ups Predicted Scores')
ax[i, 2].set_xlabel('Ups')
ax[i, 2].set_ylabel('Frequency')
sns.distplot(v['pred'], ax=ax[i, 2], kde=False, color='red')
# num_comments model
ax[i, 3].set_title(k + ' - Number of Comments Residuals')
ax[i, 3].set_xlabel('Residuals')
ax[i, 3].set_ylabel('Frequency')
sns.distplot(np.array(self.num_comments_metrics[k]['actual']) - np.array(self.num_comments_metrics[k]['pred']), ax=ax[i, 3], color='green', kde=False)
ax[i, 4].set_title(k + ' Number of Comments Test Scores')
ax[i, 4].set_xlabel('Number of Comments')
ax[i, 4].set_ylabel('Frequency')
sns.distplot(self.num_comments_metrics[k]['actual'], ax=ax[i, 4], kde=False, color='green')
ax[i, 5].set_title(k + ' Number of Comments Predicted Scores')
ax[i, 5].set_xlabel('Number of Comments')
ax[i, 5].set_ylabel('Frequency')
sns.distplot(self.num_comments_metrics[k]['pred'], ax=ax[i, 5], kde=False, color='red')
self.residualplot = FigureCanvasTkAgg(fig, self.tabview.tab('Residuals'))
self.residualplot.figure.tight_layout()
self.residualplot.get_tk_widget().pack(side=tkinter.TOP, fill=tkinter.BOTH, expand=1)
self.tabview.pack(fill='both', expand=True)
|
