ultima versao

app.py

@@ -4,6 +4,7 @@ import matplotlib.pyplot as plt
 import numpy as np
 import csv
 from scipy.stats import wilcoxon
+import matplotlib.gridspec as gridspec
 
 LIBRARIES = ["ALOY", "APSTUD", "CLI", "CLOV", "COMPASS", "CONFCLOUD", "CONFSERVER", "DAEMON", "DM", "DNN", "DURACLOUD", "EVG", "FAB", 
              "MDL", "MESOS" ,"MULE", "NEXUS", "SERVER", "STL", "TIDOC", "TIMOB", "TISTUD", "XD"]
@@ -13,44 +14,52 @@ def grafico(list_output_MbR, list_output_NEOSP, nome_projeto, pip_choices):
     df = pd.DataFrame(list_results, columns=["Model", "MAE"])
     df_list_output_MbR = pd.DataFrame(list_output_MbR, columns=["MAE"])
     df_list_output_NEOSP = pd.DataFrame(list_output_NEOSP, columns=["MAE"])
-    fig, (ax1, ax2, ax3)= plt.subplots(1, 3)
+    fig, ax = plt.subplots(2, 2)
+    
+    G = gridspec.GridSpec(2, 2)
+    axes_1 = plt.subplot(G[0, :])
+    axes_2 = plt.subplot(G[1, 0])
+    axes_3 = plt.subplot(G[1, 1])
     
     # ax1
-    ax1.set_xlabel("Index Execução")
-    ax1.set_ylabel("MAE")
-    ax1.legend()
+    axes_1.set_xlabel("Index Execução")
+    axes_1.set_ylabel("MAE")
+    axes_1.legend()
+    axes_1.grid(True, which = "both", axis = "x" )
+    axes_1.minorticks_on()
     if "MbR Regressor" in pip_choices:
-        ax1.plot(df_list_output_MbR.index, df_list_output_MbR["MAE"],  label="MbR Regressor", color="red",  alpha=0.5)
+        axes_1.scatter(range(1,51), df_list_output_MbR["MAE"].loc[1:50],  label="MbR Regressor", color="red", alpha=0.5,)
     if "NEOSP-SVR Regressor" in pip_choices:
-        ax1.plot(df_list_output_NEOSP.index, df_list_output_NEOSP["MAE"], label="NEOSP-SVR Regressor", color="blue",  alpha=0.5)
+        axes_1.scatter(range(1,51), df_list_output_NEOSP["MAE"].loc[1:50], label="NEOSP-SVR Regressor", color = "blue",  alpha=0.5)
 
     # ax2
-    ax2.set_ylabel("MAE Médio")
-    ax2.set_xlabel("Modelos")
+    axes_2.set_ylabel("MAE Médio")
+    axes_2.set_xlabel("Modelos")
     if "MbR Regressor" in pip_choices:
-        graf1 = ax2.bar(df["Model"].iloc[[0]], df["MAE"].iloc[[0]], color="red", alpha=0.5)
-        ax2.bar_label(graf1, fmt="%.01f", size=10, label_type="edge")    
+        graf1 = axes_2.bar(df["Model"].iloc[[0]], df["MAE"].iloc[[0]], color="red", alpha=0.5)
+        axes_2.bar_label(graf1, fmt="%.01f", size=10, label_type="edge")    
     if "NEOSP-SVR Regressor" in pip_choices:
-        graf2 = ax2.bar(df["Model"].iloc[[1]], df["MAE"].iloc[[1]], color = "blue",  alpha=0.5)
-        ax2.bar_label(graf2, fmt="%.01f", size=10, label_type="edge")
+        graf2 = axes_2.bar(df["Model"].iloc[[1]], df["MAE"].iloc[[1]], color = "blue",  alpha=0.5)
+        axes_2.bar_label(graf2, fmt="%.01f", size=10, label_type="edge")
     
-    ax3.set_xlabel("MAE")
-    ax3.set_ylabel("Frequência")
+    # ax3
+    axes_3.set_xlabel("MAE")
+    axes_3.set_ylabel("Frequência")
     if "MbR Regressor" in pip_choices:
-        ax3.hist(df_list_output_MbR["MAE"], color="red",  alpha=0.5)
+        axes_3.hist(df_list_output_MbR["MAE"], color="red",  alpha=0.5)
     if "NEOSP-SVR Regressor" in pip_choices:
-        ax3.hist(df_list_output_NEOSP["MAE"], color="blue", alpha=0.5)
+        axes_3.hist(df_list_output_NEOSP["MAE"], color="blue", alpha=0.5)
             
     # graficos geral
     fig.set_figwidth(15)
-    fig.set_figheight(4)
+    fig.set_figheight(8)
     fig.suptitle("Projeto {}".format(nome_projeto))
     # text
         
     resultado = ""
-    if ("MbR Regressor" and "NEOSP-SVR Regressor") in pip_choices:
+    if  (pip_choices == ["NEOSP-SVR Regressor", "MbR Regressor"]) or (pip_choices == ["MbR Regressor", "NEOSP-SVR Regressor"]):
         res = wilcoxon(list_output_MbR, list_output_NEOSP)
-        resultado = "MbR vs. NEOSP-SVR -> Wilcoxon -> Statistics: {} | valor-p: {}".format(res.statistic, res.pvalue)
+        resultado = "MbR vs. NEOSP-SVR => Statistics: {} | valor-p: {}".format(res.statistic, res.pvalue)
     
     return gr.update(value=plt, visible=True), gr.update(value=resultado, visible=True)
 
@@ -86,8 +95,9 @@ with demo:
         fetch = gr.Button(value="Fetch")
     with gr.Row():
         with gr.Column():
+            star_plot = gr.Text(visible=False, label="Wilcoxon Test")
             pip_plot = gr.Plot(visible=False)
-            star_plot = gr.Text(visible=False)
+            
             # issue_plot = gr.Plot(visible=False)
 
     fetch.click(create_pip_plot, inputs=[libraries, pip], outputs=[pip_plot, star_plot])