Module Diabetes-Detection-Web-Application.testing.tests.unit_tests.test_model

"""
    Unit Test cases for model.py file
    """
    import pytest
    import numpy as np
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.model_selection import train_test_split
    import src.modelbuilding.model as M
    import pandas as pd
    import os
    from src.modelbuilding.model import ModelBuilding

    def test_split(mocker):
        mocker.patch("src.modelbuilding.model.ModelBuilding.train", return_value=None)
        mocker.patch("src.modelbuilding.model.ModelBuilding.predict", return_value=None)
        df = pd.read_csv("tests/unit_tests/test_data/sample.csv")
        class plot:
            def __init__(self, df, path):
                print("mock init")
            def hist_observation():
                print("mock hist")
            def heatmap():
                print("mock heatmap- no saving")
        mocker.patch.object(M, "Plot", plot)
        m = ModelBuilding(df, path="test_data")
        assert isinstance(m.X_train, pd.DataFrame)
        assert isinstance(m.X_test, pd.DataFrame)
        assert isinstance(m.y_train, pd.Series)
        assert isinstance(m.y_test, pd.Series)

    @pytest.fixture()
    def sample_split(mocker):
        data = pd.read_csv("tests/unit_tests/test_data/sample.csv")
        X = data[['Pregnancies', 'Glucose', 'BloodPressure',
           'SkinThickness', 'Insulin',
           'BMI', 'DiabetesPedigreeFunction', 'Age']]
        y = data['Outcome']
        X_train, X_test, y_train, y_test = train_test_split(X, y,
            test_size=0.2)
        return X_train, X_test, y_train, y_test
    
    def test_train(mocker, sample_split):
        mocker.patch("src.modelbuilding.model.ModelBuilding.split", return_value=None)
        mocker.patch("src.modelbuilding.model.ModelBuilding.predict", return_value=None)
        df = pd.read_csv("tests/unit_tests/test_data/sample.csv")
        class plot:
            def __init__(self, df, path):
                print("mock init")
            def hist_observation():
                print("mock hist")
            def heatmap():
                print("mock heatmap- no saving")
        mocker.patch.object(M, "Plot", plot)
        print("sample split")
        print(sample_split[0])
        m = ModelBuilding(df, X_train= sample_split[0], X_test=sample_split[1],
        y_train=sample_split[2], y_test=sample_split[3], path="test_data")
        assert m.rcb is not None
    
    def test_visualize(mocker, sample_split):
        mocker.patch("src.modelbuilding.model.ModelBuilding.split", return_value=None)
        mocker.patch("src.modelbuilding.model.ModelBuilding.predict", return_value=None)
        mocker.patch("src.modelbuilding.model.ModelBuilding.train", return_value=None)
        class plot:
            def __init__(self, df, path):
                print("mock init")
            def hist_observation():
                print("mock hist")
            def heatmap():
                print("mock heatmap- no saving")
        mocker.patch.object(M, "Plot", plot)
        m = ModelBuilding(None, X_train= sample_split[0], X_test=sample_split[1],
        y_train=sample_split[2], y_test=[33, 34, 77], path="test_data")
        m.y_pred = [35, 22, 79]
        m.visualize("tests/unit_tests/test_data/comparison.png")
        assert os.path.isfile("tests/unit_tests/test_data/comparison.png")