Test your AI Agents with the all-new Agent to Agent Testing Platform.Learn More

How to use one_sample_ttest method in pandera

Best Python code snippet using pandera_python

test_ttests.py

Source:test_ttests.py

...129        passed = 0130        n_iter = 500131        for _ in range(n_iter):132            data1 = rng.normal(-5, 2, 100)133            ttest = one_sample_ttest(data1, -5)134            if ttest['P_value'] < .05:135                passed +=1136        self.assertAlmostEqual(passed / n_iter, .05, delta=.01)        137    def test_onesample_left_tailed(self):138        """Testing onesample left tailed."""139        rng = np.random.default_rng(9876138761251)140        passed = 0141        n_iter = 500142        for _ in range(n_iter):143            data1 = rng.normal(15, 1, 100)144            ttest = one_sample_ttest(data1, 15, 'left')145            if ttest['P_value'] < .05:146                passed +=1147        self.assertAlmostEqual(passed / n_iter, .05, delta=.01)        148    def test_one_sample_right_tailed(self):149        """Testing onesample right tailed."""150        rng = np.random.default_rng(615419864354)151        passed = 0152        n_iter = 500153        for _ in range(n_iter):154            data1 = rng.normal(12.2, 1, 100)155            ttest = one_sample_ttest(data1, 12.2, 'right')156            if ttest['P_value'] < .05:157                passed +=1158        self.assertAlmostEqual(passed / n_iter, .05, delta=.01)159class TestMiscTest(unittest.TestCase):160    """Test Fixture for random ttests."""161    def test_fail_tailed_option(self):162        """Testing bad tailed option."""163        with self.assertRaises(ValueError):164            _p_value_and_confidence_intervals(2.3, 100, 'greater')165    def test_confidence_intervals(self):166        """Testing the confidence interval test."""167        # Taken from a T-Test table168        # Two Tailed169        p, ci = _p_value_and_confidence_intervals(2.228, 10, 'two')...

StatsPythonRaw.py

Source:StatsPythonRaw.py

...34    except Exception as inst:35        report_exception(inst)363738def one_sample_ttest(df: pd.DataFrame) -> None:39    """ Perform a one-sample t-test """40    try:41        weight: list = df.iloc[:, 0].tolist()42        results = Stats.OneSampleTTest(25, weight)43        print_results(results, "One-sample t-test.")44    except Exception as inst:45        report_exception(inst)464748def two_sample_ttest(df_x1: pd.DataFrame, df_x2: pd.DataFrame) -> None:49    """ Run more statistical tests """50    try:51        x1: list = df_x1.iloc[:, 0].tolist()52        x2: list = df_x2.iloc[:, 0].tolist()5354        results: dict = Stats.TwoSampleTTest(x1, x2)55        print_results(results, "Two-sample t-test.")56    except Exception as inst:57        report_exception(inst)585960def plot_data(df_x1: pd.DataFrame, df_x2: pd.DataFrame) -> None:61    """ Plot the data """62    x1: list = df_x1.iloc[:, 0].tolist()63    x2: list = df_x2.iloc[:, 0].tolist()64    data: list = [x1, x2]65    66    green_diamond = dict(markerfacecolor='g', marker='D')67    fig1, ax = plt.subplots()68    ax.set_title('US versus Japan Petrol Consumption (mpg)')69    ax.set_xticklabels(['US', 'Japan'])70    ax.boxplot(data, flierprops=green_diamond)71    plt.show()727374if __name__ == "__main__":75    """ Define standard data sets used elsewhere """76    xs: list = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]77    ys: list = [1, 3, 2, 5, 7, 8, 8, 9, 10, 12]7879    run_descriptive_statistics(xs)80    run_linear_regression(xs, ys)8182    ttest_summary_data()8384    filename: str = "../Data/weight.txt"8586    # Read in data frame87    df: pd.DataFrame = pd.read_csv(filename, header=None)8889    one_sample_ttest(df)9091    us_df: pd.DataFrame = pd.read_csv("../Data/us-mpg.txt", header=None)92    jp_df: pd.DataFrame = pd.read_csv("../Data/jp-mpg.txt", header=None)9394    plot_data(us_df, jp_df)95
...

compare-2maps-within-subjects.py

Source:compare-2maps-within-subjects.py

...5from nilearn.image import math_img, mean_img, threshold_img6from nistats.second_level_model import SecondLevelModel7from nistats.thresholding import map_threshold8from nilearn.plotting import plot_glass_brain9def one_sample_ttest(filenames, name):10    design_matrix = pd.DataFrame([1] * len(filenames), columns=['intercept'])11    second_level_model = SecondLevelModel().fit(filenames, design_matrix=design_matrix)12    z_map = second_level_model.compute_contrast(output_type='z_score')13    nib.save(zmap, name + '.nii')14    thmap, threshold1 = map_threshold(z_map, level=.001, height_control='fpr', cluster_threshold=10)15    display = plot_glass_brain(thmap, display_mode='lzry', threshold=0, colorbar=True)16    display.savefig(name + '.png')17    display.close()18def compute_diffmaps(scans_A, scans_B):19    assert len(scans_A) == len(scans_B)20    list_fnames = []21    for sub, a, b in enumerate(zip(scans_A, scans_B)):22        diff =  math_img('a - b', img1=a, img=b)23        fname = f'diff_{sub:03}'24        nib.save(fname, diff)25        list_fnames.append(fname)26    return fnames27def compare_2conds_within_subjects(scans_A, scans_B, name):28    files = compute_diffmaps(scans_A, scans_B)...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.