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()
