def test_passing_bablok_basic_with_ci(): fig, ax = plt.subplots(1, 1) passingbablok(method1, method2, line_CI=True, ax=ax) return fig
def test_passing_bablok_basic_squared(): fig, ax = plt.subplots(1, 1) passingbablok(method1, method2, square=True, ax=ax) return fig
def test_passing_bablok_basic(): fig, ax = plt.subplots(1, 1) passingbablok(method1, method2, ax=ax) return fig
def test_passing_bablok_basic_title(): fig, ax = plt.subplots(1, 1) passingbablok(method1, method2, title='Test', ax=ax) return fig
def test_passing_bablok_basic_squared(): fig, ax = plt.subplots(1, 1) with pytest.deprecated_call(): passingbablok(method1, method2, square=True, ax=ax) return fig
def test_passing_bablok_basic_with_ci(): fig, ax = plt.subplots(1, 1) with pytest.deprecated_call(): passingbablok(method1, method2, line_CI=True, ax=ax) return fig
def test_passing_bablok_basic_title(): fig, ax = plt.subplots(1, 1) with pytest.deprecated_call(): passingbablok(method1, method2, title="Test", ax=ax) return fig
16.12, 16.94, 18.09, 19.13, 19.54, ] CI = 0.95 fig, axs = plt.subplots(1, 2, figsize=(10, 5)) # Legacy method passingbablok( method1, method2, CI=CI, ax=axs[0], square=True, x_label="$M_1$", y_label="$M_2$", title="Passing-Bablok: Legacy", ) # Regressor method - preferred approach PassingBablok(method1, method2, CI=CI).plot( ax=axs[1], square=True, x_label="$M_1$", y_label="$M_2$", title="Passing-Bablok: Regressor", ) plt.show()
from methcomp import passingbablok import matplotlib.pyplot as plt method1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20] method2 = [1.03, 2.05, 2.79, 3.67, 5.00, 5.82, 7.16, 7.69, 8.53, 10.38, 11.11, 12.17, 13.47, 13.83, 15.15, 16.12, 16.94, 18.09, 19.13, 19.54] passingbablok(method1, method2, CI=.95) plt.show()