ultima versao

app.py

@@ -1,19 +1,18 @@
 import gradio as gr
 import pandas as pd
-import plotly.express as px
 import matplotlib.pyplot as plt
-import statistics
+import numpy as np
 
-LIBRARIES = ["ALOY", "APSTUD", "CLI", "TIMOB", "XD"]
 
+LIBRARIES = ["ALOY", "APSTUD", "CLI", "TIMOB", "XD"]
 
 def grafico(list_output_mean, list_output_neosp, nome_projeto, pip_choices):
     list_output_mean = [3.152778, 3.375000, 1.423820, 1.052039, 1.297747, 1.224785, 2.250000, 2.375000, 1.540773, 1.847639, 1.491953, 1.052039, 0.983369, 1.669528,
                         1.665236, 1.412554, 1.375000, 1.078326, 1.556330, 1.625000, 1.860515, 1.491953, 1.160944, 1.675966, 1.987661, 2.369099, 1.431867, 1.944742, 2.329399, 1.925429]
     list_output_NEOSP = [3.191631, 3.417342, 1.202562, 0.867979, 1.225224, 1.028501, 2.165318, 2.291910, 1.141041, 1.785504, 1.086850, 0.875381, 0.714992, 1.604599,
                          1.833541, 0.860600, 1.393656, 1.152935, 1.364006, 1.647414, 1.527748, 1.236909, 1.403306, 1.655692, 1.770828, 1.937058, 0.861534, 1.341726, 1.904503, 1.449757]
-    list_results = [["Median Regressor", statistics.mean(list_output_mean)], [
-        "NEOSP-SVR Regressor", statistics.mean(list_output_NEOSP)]]
+    list_results = [["Median Regressor", np.mean(list_output_mean)], [
+        "NEOSP-SVR Regressor", np.mean(list_output_NEOSP)]]
     fig, (ax1, ax2) = plt.subplots(1, 2)
     # ax1
     if "Median Regressor" in pip_choices:

requirements.txt

@@ -1,2 +1,4 @@
-plotly
-helpers
+matplotlib
+gradio
+pandas
+numpy