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import marimo |
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__generated_with = "0.9.20" |
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app = marimo.App(width="medium", app_title="Thomas Saaty", css_file="") |
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@app.cell(hide_code=True) |
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def __(): |
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import numpy as np |
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import marimo as mo |
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import pandas as pd |
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import gspread |
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import random |
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import datetime |
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import time |
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class Criterio: |
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def __init__(self, criteriol, criterior, tooltipl, tooltipr): |
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self.criteriol = criteriol |
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self.criterior = criterior |
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self.tooltipl = tooltipl |
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self.tooltipr = tooltipr |
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def show(self): |
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score = mo.ui.range_slider( |
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start=-9, stop=9, step=1, value=[-1, 1], full_width=True |
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) |
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textl = mo.md(f'''<div data-tooltip = "{self.tooltipl}" style="text-decoration: none; text-align: left;"> |
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{self.criteriol} |
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</div>''') |
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textr = mo.md(f'''<div data-tooltip = "{self.tooltipr}" style="text-decoration: none; text-align: right;"> |
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{self.criterior} |
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</div>''') |
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return [textl, score, textr] |
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class Titles: |
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def __init__(self, title, nbs): |
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self.title = title |
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self.nbs = nbs |
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def show(self): |
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spaces = '<br/>' * self.nbs |
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return mo.vstack( |
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[mo.md(f"{spaces}"), mo.md(f"# {self.title}"), mo.md(f"{spaces}")] |
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) |
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class Nivel: |
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def __init__(self, icono, nivel, color): |
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self.icono = icono |
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self.nivel = nivel |
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self.color = color |
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def show(self): |
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return mo.md(f'''<div style = "text-align: center;"> |
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{mo.icon(icon_name = self.icono, color = self.color, size = 40)}<br/>{self.nivel} |
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</div>''') |
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def CompareLayoutValues(criterios, factores): |
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pares = [] |
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for i in range(1, criterios + 1): |
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for j in range(1, criterios + 1): |
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if i < j: |
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pares.append( |
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[ |
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"Factor de riesgo " + str(i), |
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"Factor de riesgo " + str(j), |
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factores.iat[i - 1, 0], |
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factores.iat[j - 1, 0] |
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] |
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) |
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compares = [] |
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hstacks = [] |
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for i in range(int((criterios * (criterios - 1)) / 2)): |
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compares.append(Criterio(pares[i][0], pares[i][1], pares[i][2], pares[i][3]).show()) |
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hstacks.append( |
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mo.hstack( |
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compares[i], |
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justify="space-between", |
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align="center", |
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widths=[1, 6, 1], |
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gap=1.0, |
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) |
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) |
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vstack = mo.vstack(hstacks) |
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return compares, vstack |
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def ShowMatrix(compares, criterios): |
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try: |
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with mo.status.spinner(title = 'Iniciando c谩lculos ...', subtitle = ':)', remove_on_exit = True) as spinner1: |
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time.sleep(1) |
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spinner1.update(title = "Calculando ...", subtitle = 'Matriz de consistencia') |
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values = [] |
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for i in range(len(compares)): |
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values.append( |
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abs(compares[i][1].value[0]) / abs(compares[i][1].value[1]) if compares[i][1].value[0] != 0 and compares[i][1].value[1] != 0 else 1 |
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) |
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matrix0 = pd.DataFrame([[1] * criterios] * criterios, dtype=float) |
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names = [] |
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k = -1 |
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for i in range(criterios): |
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names.append("Factor de riesgo " + str(i + 1)) |
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for j in range(criterios): |
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if j > i: |
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k += 1 |
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matrix0.iat[i, j] = values[k] |
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elif j < i: |
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matrix0.iat[i, j] = 1 / matrix0.iat[j, i] |
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names = pd.DataFrame(names) |
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matrix0 = pd.concat([names, matrix0], axis=1, ignore_index=True) |
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matrix0.columns = [ |
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"Factores de riesgo\n VS\nFactores de riesgo" |
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] + names.loc[:, 0].to_list() |
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spinner1.update(title = "Calculando ...", subtitle = 'Matriz normalizada') |
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matrix1 = matrix0.iloc[:, 1:] |
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matrix1 = matrix1.div(matrix1.sum(axis=0), axis=1) |
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matrix1 = pd.concat([names, matrix1], axis=1, ignore_index=True) |
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matrix1.columns = [ |
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"Factores de riesgo\n VS\nFactores de riesgo" |
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] + names.loc[:, 0].to_list() |
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matrix2 = matrix1.iloc[:, 1:] |
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matrix2 = matrix2.mean(axis=1) |
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matrix3 = matrix0.iloc[:, 1:].T.reset_index(drop=True).T |
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matrix3 = matrix3.dot(matrix2) |
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matrix4 = matrix3.div(matrix2) |
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spinner1.update(title = "Calculando ...", subtitle = 'Matriz de vectores') |
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matrix5 = pd.concat( |
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[names, matrix2, matrix3, matrix4], axis=1, ignore_index=True |
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) |
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matrix5.columns = [ |
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" Vectores\n VS\nFactores de riesgo", |
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"Vector promedio", |
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"Vector producto", |
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"Vector cociente", |
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] |
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ym = matrix4.mean() |
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ci = (ym - criterios) / (criterios - 1) |
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cr = ci / np.polyval([-8.44988345e-04, 2.56164206e-02, -2.95897436e-01, 1.61445934e+00, -2.23388889e+00], criterios) * 100 |
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if criterios <= 3: |
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consistencia = 'es consistente.' if cr <= 5 else 'no es consistente.' |
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elif criterios == 4: |
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consistencia = 'es consistente.' if cr <= 9 else 'no es consistente.' |
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else: |
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consistencia = 'es consistente.' if cr <= 10 else 'no es consistente.' |
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text1 = mo.md(f"El cociente promedio resultante es {str(round(ym, 3))}, por lo que el 铆ndice CI es igual a {str(round(ci, 3))} y el 铆ndice CR es igual {str(round(cr, 3))}%; en concecuencia la matriz de consistencias {consistencia}") |
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matrixs = [ |
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Titles("Matriz de consistencias", 1).show(), |
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matrix0, |
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Titles("Matriz normalizada", 1).show(), |
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matrix1, |
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Titles("Matriz de vectores", 1).show(), |
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matrix5, |
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mo.callout(text1, kind = 'success' if consistencia == "es consistente." else 'danger'), |
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] |
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spinner1.update(title = "C谩lculos finalizados", subtitle = ":)") |
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time.sleep(1) |
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return matrixs, consistencia |
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except: |
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with mo.status.spinner(title = 'Ocurri贸 un error', subtitle = ':(', remove_on_exit = True) as spinner1: |
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time.sleep(2) |
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def MeanMatrix(factores, sheets, valores, unidades, error): |
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try: |
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with mo.status.spinner(title = 'Iniciando c谩lculos ...', subtitle = ':)', remove_on_exit = True) as spinner1: |
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time.sleep(1) |
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spinner1.update(title = "Calculando ...", subtitle = 'Matriz de consistencia resultante') |
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try: |
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error = float(error.value) if float(error.value) >= 0.0001 else 0.0001 |
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except: |
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error = 0.0001 |
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riesgos = factores.shape[0] |
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names1 = [] |
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names2 = [] |
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for i in range(riesgos): |
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names1.append(['Factor de riesgo ' + str(i + 1)]) |
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names2.append('Factor de riesgo ' + str(i + 1)) |
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names1 = pd.DataFrame(names1) |
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names0 = [sheet.title for sheet in sheets.worksheets()] |
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exclude = ["Factores de riesgo", "Valores normalizados", "Unidades", "Plan operativo anual"] |
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matrices = [] |
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for i in names0: |
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if i not in exclude: |
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worksheet = sheets.worksheet(i) |
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matriz = pd.DataFrame(worksheet.get_all_records()).iloc[:, 1:riesgos + 1] |
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if matriz.shape[0] == riesgos: |
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matrices.append(matriz) |
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matrix0 = pd.concat(matrices).groupby(level=0).prod() ** (1 / len(matrices)) |
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matrix1 = matrix0.div(matrix0.sum(axis=0), axis=1) |
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matrix2 = matrix1.mean(axis=1) |
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matrix3 = matrix0.T.reset_index(drop=True).T |
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matrix3 = matrix3.dot(matrix2) |
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matrix4 = matrix3.div(matrix2) |
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matrix5 = pd.concat( |
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[names1, matrix0, matrix2, matrix3, matrix4], axis=1, ignore_index=True |
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) |
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matrix5.columns = ['Par谩metros de c谩lculo\n VS\n Factores de riesgo'] + names2 + ["Vector promedio", "Vector producto", "Vector cociente"] |
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ym = matrix4.mean() |
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ci = (ym - riesgos) / (riesgos - 1) |
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cr = ci / np.polyval([-8.44988345e-04, 2.56164206e-02, -2.95897436e-01, 1.61445934e+00, -2.23388889e+00], riesgos) * 100 |
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if riesgos <= 3: |
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consistencia = 'es consistente.' if cr <= 5 else 'no es consistente.' |
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elif riesgos == 4: |
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consistencia = 'es consistente.' if cr <= 9 else 'no es consistente.' |
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else: |
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consistencia = 'es consistente.' if cr <= 10 else 'no es consistente.' |
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text1 = mo.md(f"El cociente promedio resultante es {str(round(ym, 3))}, por lo que el 铆ndice CI es igual a {str(round(ci, 3))} y el 铆ndice CR es igual {str(round(cr, 3))}%; en concecuencia la matriz de consistencias {consistencia}") |
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matrix6 = matrix0.T.reset_index(drop=True).T |
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matrix7 = [] |
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columns = ['Vectores promedio\n vs\nFactores de riesgo'] |
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counter = 0 |
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spinner1.update(title = "Calculando ...", subtitle = 'Matriz de convergencia') |
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while True: |
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counter += 1 |
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columns.append('Iteraci贸n ' + str(counter)) |
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matrix6, matrix8 = Convergencia(matrix6) |
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matrix7.append(matrix8) |
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if len(matrix7) > 1: |
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if matrix7[-1].sub(matrix7[-2]).abs().sum() < error: |
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break |
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columns[-1] = 'Vector promedio final' |
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matrix7 = pd.concat([names1, pd.concat(matrix7, axis = 1)], axis = 1) |
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matrix7.columns = columns |
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matrix8 = matrix7['Vector promedio final'] |
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matrix9 = valores.iloc[:, 1:].replace(',', '.', regex = True).apply(pd.to_numeric, errors='coerce') |
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matrix9 = matrix9 * matrix8.values |
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matrix10 = pd.DataFrame(matrix9.sum(axis=1), columns=['Nivel de riesgo total']) |
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matrix11 = pd.DataFrame(valores.iloc[:,0]) |
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spinner1.update(title = "Calculando ...", subtitle = 'Matriz de nivel de riesgo') |
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matrix12 = pd.concat([matrix11, matrix9, matrix10], axis=1, ignore_index=False) |
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matrix13 = [] |
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for i in matrix11['Registro de Hidrocarburos']: |
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ubicacion = unidades[unidades['REGISTRO'] == i][['DEPARTAMENTO', 'PROVINCIA', 'DISTRITO']] |
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matrix13.append([Direccion(ubicacion, filtroprovincial, filtrodistrital)]) |
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matrix13 = pd.DataFrame(matrix13, columns = ['Regi贸n']) |
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matrix14 = pd.concat([matrix11, matrix13, matrix10], axis=1, ignore_index=False) |
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spinner1.update(title = "C谩lculos finalizados", subtitle = ":)") |
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time.sleep(1) |
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return [mo.vstack([Titles("Matriz de consistencia resultante", 1).show(), matrix5, mo.callout(text1, kind = 'success' if consistencia == "es consistente." else 'danger'), Titles("Matriz de convergencia", 1).show(), matrix7, Titles("Matriz de nivel de riesgo", 1).show(), matrix12]), matrix14] |
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except: |
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with mo.status.spinner(title = 'Ocurri贸 un error', subtitle = ':(', remove_on_exit = True) as spinner1: |
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time.sleep(2) |
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def CreateSheet(sheets, text, matrixs): |
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try: |
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with mo.status.spinner(title = 'Validando credenciales ...', subtitle = ':)', remove_on_exit = True) as spinner1: |
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time.sleep(1) |
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spinner1.update(title = "Registrando ...", subtitle = 'Matriz de consistencia') |
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name = text.value |
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if name == "": |
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name = str(datetime.datetime.now()) |
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names = [sheet.title for sheet in sheets.worksheets()] |
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if name not in names: |
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sheet = sheets.add_worksheet(title=name, rows="20", cols="20") |
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else: |
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sheet = sheets.worksheet(name) |
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sheet.clear() |
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matrix = pd.concat([matrixs[1], matrixs[5].iloc[:, 1:]], axis=1, ignore_index=True) |
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matrix.columns = ['Par谩metros de c谩lculo\n VS\n Factores de riesgo'] + list(matrixs[1].columns[1:]) + list(matrixs[5].columns[1:]) |
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set_2(2) |
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sheet.update([matrix.columns.values.tolist()] + matrix.values.tolist()) |
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set_2(1) |
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spinner1.update(title = "Registro finalizado", subtitle = ":)") |
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time.sleep(1) |
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except: |
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with mo.status.spinner(title = 'Ocurri贸 un error', subtitle = ':(', remove_on_exit = True) as spinner1: |
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time.sleep(2) |
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def Convergencia(matrix0): |
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matrix1 = matrix0.dot(matrix0) |
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matrix2 = matrix1.sum(axis = 1) |
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matrix2 = matrix2.div(matrix2.sum()) |
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return matrix1, matrix2 |
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def Direccion(ubicacion, filtroprovincial, filtrodistrital): |
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departamento = ubicacion['DEPARTAMENTO'].iat[0] |
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provincia = ubicacion['PROVINCIA'].iat[0] |
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distrito = ubicacion['DISTRITO'].iat[0] |
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if departamento != 'PROV. CONST. DEL CALLAO' and departamento != 'LIMA': |
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region = ubicacion['DEPARTAMENTO'].iat[0] |
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else: |
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if provincia in filtroprovincial or distrito in filtrodistrital: |
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region = 'LIMA SUR' |
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else: |
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region = 'LIMA NORTE' |
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return region |
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def Distribucion(valor): |
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cociente, residuo = valor // 12, valor % 12 |
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lista = [cociente] * 12 |
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for i in range(residuo): |
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lista[i] += 1 |
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random.shuffle(lista) |
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return lista + [sum(lista)] |
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def FixRange(): |
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if get_3()[0] < 0.05: |
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set_3([0.05, get_3()[1]]) |
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if get_3()[1] > 0.95: |
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set_3([get_3()[0], 0.95]) |
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@mo.cache |
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def LoadData(valor): |
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gs = gspread.service_account(filename = valor) |
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clasificacion = pd.read_excel("https://docs.google.com/spreadsheets/d/1CsDG8_l9r-aKX2UvFYASff-pqNSnD2wIz42Z8a-D3EQ/export?format=xlsx&gid=484881519", sheet_name='Clasificaci贸n de departamentos') |
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filtroprovincial = clasificacion[clasificacion['OR2'] == 'LIMA SUR']['PROVINCIAS'].to_list() |
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filtrodistrital = clasificacion[clasificacion['OR3'] == 'LIMA SUR']['DISTRITOS'].to_list() |
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niveles = [Nivel("mingcute:safety-certificate-fill", "BAJO", "green").show(), Nivel("fluent:shield-28-filled", "MEDIO", "orange").show(), Nivel("clarity:shield-x-solid", "ALTO", "red").show()] |
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return gs, filtroprovincial, filtrodistrital, niveles |
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@mo.cache |
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def SelectSheets(valor, gs): |
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if valor == "Actividad 050: Estaciones de Servicios y Grifos": |
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url = "2PACX-1vSi7zXsaq2CiXhtAVq_E4h3RJYVvnaj1yATmid_indbg1aEMIgJ_xUYw8QPiBxzJv9wMZHCB4Edr37P" |
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key = "1kgP3kfkXM2ixQyGK_ycvzkZMbp9RkU8vdSg60ucGZT8" |
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elif valor == "Actividad 060: Transporte de combustibles l铆quidos y OPDH": |
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url = "2PACX-1vTkJhSkqGEIvirM5GGd1SeDHq5Iu2xrwhl8D7tEsAfi347zSOJ-R_EhaGCG5Qo74mmuMesFMFehkE9f" |
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key = "1sSKv_1fNfZGH2tuKq781vb58xh3w8cx-yxChzwxY7C0" |
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elif valor == "Actividad 071: Gasocentro de GLP": |
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url = "2PACX-1vRPv-_mtVtmuUGLXDgbJ941volRsan8Hbf3GwN-5HtUhqhQTRhTdDsMwa-SxFtHNC6H21DjztadBdbz" |
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key = "1MYSVV1MHVYFZxVNpNzloG6kcfX5z7TJXHB9Y687lVpU" |
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iframe = mo.iframe(f''' |
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<iframe src="https://docs.google.com/spreadsheets/d/e/{url}/pubhtml?widget=true&headers=false" width="100%" height="350" frameborder="0"></iframe> |
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''') |
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sheets = gs.open_by_key(key) |
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factores = pd.DataFrame(sheets.worksheet("Factores de riesgo").get_all_records()) |
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valores = sheets.worksheet("Valores normalizados").get_all_values() |
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valores = pd.DataFrame(valores[1:], columns = valores[0]) |
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unidades = sheets.worksheet("Unidades").get_all_values() |
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unidades = pd.DataFrame(unidades[1:], columns = unidades[0]) |
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poa = pd.DataFrame(sheets.worksheet("Plan operativo anual").get_all_records()) |
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return iframe, sheets, factores, valores, unidades, poa |
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|
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get_1, set_1 = mo.state("Actividad 050: Estaciones de Servicios y Grifos") |
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get_2, set_2 = mo.state(0) |
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get_3, set_3 = mo.state([0.5, 0.7]) |
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gs, filtroprovincial, filtrodistrital, niveles = LoadData('credentials.json') |
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|
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mo.output.replace(mo.vstack([ |
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mo.md(f'''<div style="text-align: center;"> |
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{mo.md(f'''<div style="font-size: 40px;"> |
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M脡TODO DEL PROCESO JER脕RQUICO ANAL脥TICO |
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</div>''')} |
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</div>'''), |
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mo.md('---'), |
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])) |
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icon1 = mo.icon('mdi:fossil-fuel-outline', size = 50, color = "black") |
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md1 = mo.md("Seleccion el tipo de actividad que desea analizar :") |
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dropdown1 = mo.ui.dropdown(options = ["Actividad 050: Estaciones de Servicios y Grifos", "Actividad 060: Transporte de combustibles l铆quidos y OPDH", "Actividad 071: Gasocentro de GLP"], value = get_1(), full_width = True, on_change = set_1) |
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mo.output.append(mo.hstack([icon1, md1, dropdown1], align = "center", widths = [1, 8, 7], justify = "space-between", gap = 1.0)) |
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return ( |
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CompareLayoutValues, |
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Convergencia, |
|
|
CreateSheet, |
|
|
Criterio, |
|
|
Direccion, |
|
|
Distribucion, |
|
|
FixRange, |
|
|
LoadData, |
|
|
MeanMatrix, |
|
|
Nivel, |
|
|
SelectSheets, |
|
|
ShowMatrix, |
|
|
Titles, |
|
|
datetime, |
|
|
dropdown1, |
|
|
filtrodistrital, |
|
|
filtroprovincial, |
|
|
get_1, |
|
|
get_2, |
|
|
get_3, |
|
|
gs, |
|
|
gspread, |
|
|
icon1, |
|
|
md1, |
|
|
mo, |
|
|
niveles, |
|
|
np, |
|
|
pd, |
|
|
random, |
|
|
set_1, |
|
|
set_2, |
|
|
set_3, |
|
|
time, |
|
|
) |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(SelectSheets, get_1, gs, mo): |
|
|
iframe, sheets, factores, valores, unidades, poa = SelectSheets(get_1(), gs) |
|
|
mo.output.replace(mo.vstack([mo.accordion({'Base de datos': iframe}, lazy = True), mo.md("<br/>")])) |
|
|
icon2 = mo.icon('fluent-mdl2:compare', size = 50, color = "black") |
|
|
md2 = mo.md("Establesca el n煤mero de factores de riesgo a comparar : ") |
|
|
criterios = mo.ui.number( |
|
|
start=2, |
|
|
stop=factores.shape[0], |
|
|
step=1, |
|
|
value=factores.shape[0], |
|
|
full_width=True, |
|
|
) |
|
|
mo.output.append(mo.hstack([icon2, md2, criterios], align = "center", widths = [1, 8, 7], justify = "space-between", gap = 1.0)) |
|
|
return ( |
|
|
criterios, |
|
|
factores, |
|
|
icon2, |
|
|
iframe, |
|
|
md2, |
|
|
poa, |
|
|
sheets, |
|
|
unidades, |
|
|
valores, |
|
|
) |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(CompareLayoutValues, criterios, factores, mo): |
|
|
compares, vstack = CompareLayoutValues(criterios.value, factores) |
|
|
mo.output.replace(vstack) |
|
|
return compares, vstack |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(ShowMatrix, compares, criterios, mo): |
|
|
calcs = mo.ui.button( |
|
|
label=f"{mo.icon('eos-icons:rotating-gear', size = 15, color = "black")} C谩lcular matrices de c谩lculo", |
|
|
tooltip="Define las matrices de consistencias", |
|
|
kind="success", |
|
|
full_width=True, |
|
|
on_click=lambda _: ShowMatrix(compares, criterios.value), |
|
|
) |
|
|
return (calcs,) |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(calcs, mo): |
|
|
mo.output.replace(mo.vstack(items = [mo.md("<br/>"), calcs])) |
|
|
return |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(CreateSheet, calcs, mo, sheets): |
|
|
try: |
|
|
matrixs, consistencia = calcs.value |
|
|
mo.lazy(mo.output.replace(mo.vstack(matrixs)), show_loading_indicator=True) |
|
|
text = mo.ui.text( |
|
|
placeholder='Ingrese su nombre aqu铆 ...', |
|
|
kind='text', |
|
|
full_width=True, |
|
|
) |
|
|
update = mo.ui.button( |
|
|
label=f"{mo.icon('ic:baseline-cloud-upload', size = 15, color = "black")} Registrar matriz de consistencia", |
|
|
kind="success", |
|
|
full_width=True, |
|
|
on_click=lambda _: CreateSheet(sheets, text, matrixs), |
|
|
) |
|
|
except: |
|
|
pass |
|
|
return consistencia, matrixs, text, update |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(consistencia, mo, text, update): |
|
|
try: |
|
|
if consistencia == "es consistente.": |
|
|
mo.output.replace(mo.hstack([text, update], justify='space-between', align='center', widths=[1, 1])) |
|
|
except: |
|
|
pass |
|
|
return |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(get_2, mo, set_2, time): |
|
|
if get_2() != 0: |
|
|
if get_2() == 1: |
|
|
mo.output.replace(mo.callout(value = mo.md("Matriz de consistencia registrada con exito !"), kind = 'success')) |
|
|
elif get_2() == 2: |
|
|
mo.output.replace(mo.callout(value = mo.md("Matriz de consistencia registrada sin exito !"), kind = 'danger')) |
|
|
set_2(0) |
|
|
time.sleep(3) |
|
|
mo.output.clear() |
|
|
return |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(get_3, mo, set_3): |
|
|
error = mo.ui.text(value = "0.0001", label = "Error de convergencia permisible:", full_width = True) |
|
|
porcentaje = mo.ui.number(start = 0, stop = 100, step = 1, value = 70, label = "Porcentaje de fiscalizaciones", full_width = True) |
|
|
rango = mo.ui.range_slider(start = 0, stop = 1, step = 0.05, value = get_3(), label = "Nivel de riesgo", on_change = set_3, full_width = True) |
|
|
mo.output.replace(mo.vstack(items = [mo.md("<br/>"), mo.hstack(items = [error, porcentaje], align = "center", justify = "space-between", widths = [1, 1]), rango])) |
|
|
return error, porcentaje, rango |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(FixRange, get_3, mo, niveles, np): |
|
|
FixRange() |
|
|
menor, mayor = get_3() |
|
|
anchos = np.array([menor - 0, mayor - menor, 1 - mayor]) |
|
|
anchos = anchos / anchos.min() |
|
|
anchos = anchos.tolist() |
|
|
mo.output.replace(mo.hstack(items = niveles, align = "center", justify = "space-between", widths = anchos)) |
|
|
return anchos, mayor, menor |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(MeanMatrix, error, factores, mo, sheets, unidades, valores): |
|
|
meanmatrix = mo.ui.button( |
|
|
label=f"{mo.icon('eos-icons:rotating-gear', size = 15, color = "black")} C谩lcular matrices de resultados", |
|
|
tooltip="Depende de las matrices de consistencias previamente definidas", |
|
|
kind="success", |
|
|
full_width=True, |
|
|
on_click=lambda _: MeanMatrix(factores, sheets, valores, unidades, error), |
|
|
) |
|
|
return (meanmatrix,) |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(meanmatrix, mo): |
|
|
mo.output.replace(mo.vstack([mo.md("<br>"), meanmatrix])) |
|
|
return |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(meanmatrix, mo): |
|
|
try: |
|
|
mo.lazy(mo.output.replace(meanmatrix.value[0]), show_loading_indicator=True) |
|
|
except: |
|
|
pass |
|
|
return |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(Distribucion, Titles, meanmatrix, mo, pd, poa, porcentaje): |
|
|
try: |
|
|
regiones = pd.DataFrame(meanmatrix.value[1]["Regi贸n"].value_counts()) |
|
|
oficina = mo.ui.dropdown(options=sorted(regiones.index.to_list()), label="Seleccione la regi贸n que desea analizar: ", value= sorted(regiones.index.to_list())[0], full_width=True) |
|
|
departamentos = pd.DataFrame(sorted(regiones.index.to_list()), columns = ['Regiones']) |
|
|
distribucion = [] |
|
|
for i in departamentos['Regiones']: |
|
|
acciones = int(poa[poa['REGIONES'] == i]['ACCIONES'].iat[0] * porcentaje.value / 100) |
|
|
distribucion.append(Distribucion(acciones)) |
|
|
distribucion = pd.DataFrame(distribucion, columns= ["Enero", "Febrero", "Marzo", "Abril", "Mayo", "Junio", "Julio", "Agosto", "Septiembre", "Octubre", "Noviembre", "Diciembre", "Total"]) |
|
|
mo.lazy(mo.output.replace(mo.vstack([Titles('Matriz de fiscalizaci贸n nacional', 1).show(), pd.concat([departamentos, distribucion], ignore_index=False, axis = 1), Titles("Matriz de fiscalizaci贸n regional", 1).show(), oficina])), show_loading_indicator=True) |
|
|
except: |
|
|
pass |
|
|
return acciones, departamentos, distribucion, i, oficina, regiones |
|
|
|
|
|
|
|
|
@app.cell(hide_code=True) |
|
|
def __(get_3, meanmatrix, mo, np, oficina, pd, poa, porcentaje, regiones): |
|
|
try: |
|
|
matrix1 = meanmatrix.value[1][meanmatrix.value[1]['Regi贸n'] == oficina.value].sort_values(by = 'Nivel de riesgo total', ascending = False) |
|
|
matrix1.index = np.arange(1, matrix1.shape[0] + 1) |
|
|
matrix2 = pd.DataFrame(['ALTA'] * int(matrix1[matrix1['Nivel de riesgo total'] >= get_3()[1]].shape[0]) + ['MEDIA'] * int(matrix1[(matrix1['Nivel de riesgo total'] < get_3()[1]) & (matrix1['Nivel de riesgo total'] >= get_3()[0])].shape[0]) + ['BAJA'] * int(matrix1[matrix1['Nivel de riesgo total'] < get_3()[0]].shape[0]), columns=['Prioridad']) |
|
|
matrix2.index = np.arange(1, matrix2.shape[0] + 1) |
|
|
matrix3 = pd.concat([matrix1, matrix2], axis=1, ignore_index=False) |
|
|
callout = mo.callout(value = mo.md(f"La region {oficina.value.title()} cuenta con {regiones.loc[oficina.value].iat[0]} unidades, y seg煤n el Plan Operativo Anual 2024, esta debe cumplir con {poa[poa['REGIONES'] == oficina.value]['ACCIONES'].iat[0]} acciones de fiscalizaci贸n, por lo cual, debera ejecutar {int(poa[poa['REGIONES'] == oficina.value]['ACCIONES'].iat[0] * porcentaje.value / 100)} fiscalizaciones basadas en riesgos, siguiendo el orden de la matriz de fiscalizaci贸n regional correspondiente."), kind = 'success') |
|
|
mo.lazy(mo.output.replace(mo.vstack([matrix3, callout])), show_loading_indicator=True) |
|
|
except: |
|
|
pass |
|
|
return callout, matrix1, matrix2, matrix3 |
|
|
|
|
|
|
|
|
if __name__ == "__main__": |
|
|
app.run() |
|
|
|
