Test_plot_simultaneous

Example Python program Test_plot_simultaneous.py

Modules

from statsmodels.compat.testing import skipif
from statsmodels.compat.python import BytesIO, asbytes, range
import warnings
import numpy as np
import pandas as pd
import scipy.stats as stats
from numpy.testing import assert_, assert_allclose, assert_almost_equal, assert_equal, \
from statsmodels.stats.multicomp import (tukeyhsd, pairwise_tukeyhsd,
import matplotlib.pyplot as plt # makes plt available for test functions

Classes

class CheckTuckeyPlotSimultaneous(object):

Methods

def setup_class_(cls):
def test_plot_simultaneous(self):

Code

Python example

from statsmodels.compat.testing import skipif
from statsmodels.compat.python import BytesIO, asbytes, range

import warnings

import numpy as np
import pandas as pd
import scipy.stats as stats
from numpy.testing import assert_, assert_allclose, assert_almost_equal, assert_equal, \
    assert_raises

from statsmodels.stats.multicomp import (tukeyhsd, pairwise_tukeyhsd,
                                         MultiComparison)

try:
    import matplotlib.pyplot as plt  # makes plt available for test functions
    have_matplotlib = True
except ImportError:
    have_matplotlib = False

races =   ["asian","black","hispanic","other","white"]

# Generate random data
voter_race = np.random.choice(a= races,
                              p = [0.05, 0.15 ,0.25, 0.05, 0.5],
                              size=1000)

# Use a different distribution for white ages
white_ages = stats.poisson.rvs(loc=18, 
                              mu=32,
                              size=1000)

voter_age = stats.poisson.rvs(loc=18,
                              mu=30,
                              size=1000)

voter_age = np.where(voter_race=="white", white_ages, voter_age)

class CheckTuckeyPlotSimultaneous(object):

    @classmethod
    def setup_class_(cls):
        cls.endog = voter_age
        cls.groups = voter_race
        cls.alpha = 0.05
        cls.mc = MultiComparison(cls.endog, cls.groups)
        cls.res = cls.mc.tukeyhsd(alpha=cls.alpha)

    @skipif(not have_matplotlib, reason='matplotlib not available')
    def test_plot_simultaneous(self):
        result = pairwise_tukeyhsd(self.endog, self.groups, alpha=self.alpha)
        # Smoke test for figure
        fig = result.plot_simultaneous()
        assert_equal(isinstance(fig, plt.Figure), True)
        plt.close(fig)

Useful Links

Articles: https://python-commandments.org/
Python shell: https://bsdnerds.org/learn-python/
Tutorial: https://pythonprogramminglanguage.com/