ajustes en las gráficas de iaucs y distr. de comidas reportadas

estadisticas.py

@@ -220,49 +220,91 @@ def triareas(pacientes):
         )
     return figura
 
-def comidas_datos(datos):
-    columnas = ["hc_total", "kcal_total", "fiber_total", "protein_total", "pre-AUC", "post-AUC", "iAUC", "N-alimentos"]
+def comidas_iaucs(datos):
+    columnas = ["pre-AUC", "post-AUC", "iAUC"]
     datos["N-alimentos"] = datos["foods"].apply(lambda x: len(x))
 
-    figura = make_subplots(cols=4, rows=2, shared_xaxes=True, vertical_spacing=0.1,
-                           subplot_titles=columnas)
-    lrow = 1
+    fig = make_subplots(cols=3, rows=1,  vertical_spacing=0.25) 
+    lcol = 1
+    seq = 1
+    for columna in columnas:
+        datosfil = datos[np.abs(stats.zscore(datos[columna], nan_policy='omit')) < 3]
+        fig.add_trace(
+            go.Scatter(y=datosfil[columna], name=columna, mode="markers"),
+            row=1, col=lcol
+        )
+        fig['layout']['yaxis' + str(seq)]['title']=columna
+        fig['layout']['xaxis' + str(seq)]['title']="Comida ID"                        
+        seq = seq + 1
+        lcol = lcol + 1
+    fig.update_layout(showlegend=False)
+    return fig
+
+def comidas_iauc_describe(datos):
+    columnas = ["pre-AUC", "post-AUC", "iAUC"]
+    fig = make_subplots(cols=3, rows=1, vertical_spacing=0.25)
+    seq = 1
     lcol = 1
     for columna in columnas:
         datosfil = datos[np.abs(stats.zscore(datos[columna], nan_policy='omit')) < 3]
+        fig.add_trace(
+            go.Histogram(x=datosfil[columna], name=columna),
+            row=1, col=lcol
+        )
+        fig['layout']['yaxis' + str(seq)]['title']=columna
+        seq = seq + 1
+        lcol = lcol + 1 
+
+
+    fig.update_layout(
+        showlegend = False,
+        bargap=0.05, # gap between bars of adjacent location coordinates
+        bargroupgap=0.05 # gap between bars of the same location coordinates
+    )
+    return fig
+
+def comidas_macro_contenido(datos):
+    columnas = ["hc_total", "lipids_total", "fiber_total", "protein_total"]
+    datos["N-alimentos"] = datos["foods"].apply(lambda x: len(x))
+
+    figura = make_subplots(cols=4, rows=1,  vertical_spacing=0.24)
+    lcol = 1
+    seq = 1
+    for columna in columnas:
+        datosfil = datos[np.abs(stats.zscore(datos[columna], nan_policy='omit')) < 3]
         figura.add_trace(
             go.Scatter(y=datosfil[columna], name=columna, mode="markers"),
-            row=lrow, col=lcol
+            row=1, col=lcol
         )
-        lrow = lrow + (lcol // 4)
+        figura['layout']['yaxis' + str(seq)]['title']=columna
+        figura['layout']['xaxis' + str(seq)]['title']="Comida ID"                        
+        seq = seq + 1
         lcol = lcol + 1 if lcol < 4 else 1
     figura.update_layout(showlegend=False)
     return figura
 
-def comidas_describe(datos):
-    columnas = ["hc_total", "kcal_total", "fiber_total", "protein_total", "pre-AUC", "post-AUC", "iAUC", "N-alimentos"]
-    datos["N-alimentos"] = datos["foods"].apply(lambda x: len(x))
-    print(datos.columns)
-    figura = make_subplots(cols=4, rows=2, shared_yaxes=True,
-                           subplot_titles=columnas)
-    lrow = 1
+def comidas_macro_describe(datos):
+    columnas = ["hc_total", "lipids_total", "fiber_total", "protein_total"]
+    fig = make_subplots(cols=4, rows=1, vertical_spacing=0.25)
+    seq = 1
     lcol = 1
     for columna in columnas:
         datosfil = datos[np.abs(stats.zscore(datos[columna], nan_policy='omit')) < 3]
-        figura.add_trace(
+        fig.add_trace(
             go.Histogram(x=datosfil[columna], name=columna),
-            row=lrow, col=lcol
+            row=1, col=lcol
         )
-        lrow = lrow + (lcol // 4)
+        fig['layout']['yaxis' + str(seq)]['title']=columna
+        seq = seq + 1
         lcol = lcol + 1 if lcol < 4 else 1
 
 
-    figura.update_layout(
+    fig.update_layout(
         showlegend = False,
         bargap=0.05, # gap between bars of adjacent location coordinates
         bargroupgap=0.05 # gap between bars of the same location coordinates
     )
-    return figura
+    return fig
 
 def comidas_porcentajes(datos):
     columnas = ["hc_total", "fiber_total", "protein_total", "lipids_total"]
@@ -551,30 +593,37 @@ app.layout = html.Div(children=[
         dcc.Graph(id="figCorrelaciones")
     ]),
     # correlaciones transpuesta
-    html.Div(children= [
-        html.Div(children= [html.H1("Relación de iAUC/Controlados con diversos índices (traspuesta)", className = "header-title2")]),
-        dcc.Graph(figure=correlaciones_v2(visitas_incluidos, "Glucosa"))
-    ]),
+    # html.Div(children= [
+    #     html.Div(children= [html.H1("Relación de iAUC/Controlados con diversos índices (traspuesta)", className = "header-title2")]),
+    #     dcc.Graph(figure=correlaciones_v2(visitas_incluidos, "Glucosa"))
+    # ]),
 
     # areas de tres pacientes
     html.Div(children= [
         html.Div(children= [html.H1("Ejemplos de iAUC de Glucosa", className = "header-title2")]),
         dcc.Graph(figure=triareas([85,148,177]))
     ]),
-    # heatmap
+    # # heatmap
+    # html.Div(children= [
+    #     html.Div(children= [html.H1("Mapa de calor de iAUC/alimentos controlados", className = "header-title2")]),
+    #     dcc.Graph(figure=heatmap(visitas_incluidos))
+    # ,]),
+    # datos de comidas
     html.Div(children= [
-        html.Div(children= [html.H1("Mapa de calor de iAUC/alimentos controlados", className = "header-title2")]),
-        dcc.Graph(figure=heatmap(visitas_incluidos))
+        html.Div(children= [html.H1("iAUCs de las comidas reportadas", className = "header-title2")]),
+        dcc.Graph(figure=comidas_iaucs(comidas)),
+        dcc.Graph(figure=comidas_iauc_describe(comidas))
     ,]),
     # datos de comidas
     html.Div(children= [
-        html.Div(children= [html.H1("Macronutrientes / AUCs de comidas", className = "header-title2")]),
-        dcc.Graph(figure=comidas_datos(comidas))
+        html.Div(children= [html.H1("Contenido de macronutrientes de las comidas", className = "header-title2")]),
+        dcc.Graph(figure=comidas_macro_contenido(comidas))
     ,]),
+
     # descripcion de comidas
     html.Div(children= [
         html.Div(children= [html.H1("Distribución de Macronutrientes de comidas", className = "header-title2")]),
-        dcc.Graph(figure=comidas_describe(comidas))
+        dcc.Graph(figure=comidas_macro_describe(comidas))
     ,]),
     # descripcion de componentes de macronutrientes de comidas
     html.Div(children= [
@@ -626,7 +675,7 @@ def update_correlacion(controlado):
     datos_sorted = datos_fil.sort_values(by=controlado, ascending=True)
     datos_sorted.reset_index(inplace=True)
     metricas = ["imc", "age", "glucose", "hba1c"]
-    figura = make_subplots(rows=2, cols=2, vertical_spacing=0.25)
+    figura = make_subplots(rows=1, cols=4, vertical_spacing=0.25)
     lrow = 1
     lcol = 1
     seq = 1
@@ -635,18 +684,17 @@ def update_correlacion(controlado):
 
         figura.add_trace(
             go.Scatter(x=datos_sorted.index, y=datos_sorted[metrica], name=metrica, mode='markers'),
-            row=lrow, col=lcol
+            row=1, col=lcol
         )
         figura.add_trace(
             go.Scatter(x=datos_sorted.index, y=datos_sorted[metrica].rolling(5).mean(), name="PM(5)"),
-            row=lrow, col=lcol
+            row=1, col=lcol
         )
         corr = datos_sorted[[metrica]].corrwith(datos_sorted[controlado]).values[0]
-        figura.add_annotation(row=lrow, col=lcol, text="R = " + "{:.2f}".format(corr))
-        figura["layout"]['xaxis'  + str(seq)]['title']="Ranqueo de pacientes por su iAUC de" + controlado
+        figura.add_annotation(row=1, col=lcol, text="R = " + "{:.2f}".format(corr))
+        figura["layout"]['xaxis'  + str(seq)]['title']="Ranqueo de pacientes por iAUC: " + controlado
         figura["layout"]['yaxis'  + str(seq)]['title']= metrica
-        lcol = lcol + 1 if lcol < 2 else 1
-        lrow = lrow + (lcol % 2)
+        lcol = lcol + 1
         seq = seq + 1
     figura["layout"]["yaxis1"]["range"] = [15,45]
     figura["layout"]["yaxis2"]["range"] = [17,80]
@@ -654,7 +702,7 @@ def update_correlacion(controlado):
     figura["layout"]["yaxis4"]["range"] = [5,7]    
     
     figura.update_layout(showlegend=False)
-    figura.update_layout(height=600, width=800)    
+    #figura.update_layout(height=600, width=800)    
     return  figura
 
 if __name__ == "__main__":