CLN: Remove unused imports

Remove imports of matplotlib that are no longer needed

statsmodels/conftest.py

@@ -30,10 +30,11 @@ def pytest_runtest_setup(item):
  if 'example' in item.keywords and item.config.getoption("--skip-examples"):
  pytest.skip("skipping due to --skip-examples")
 
- if 'requires_matplotlib' in item.keywords and item.config.getoption("--skip-matplotlib"):
+ if 'matplotlib' in item.keywords and \
+ item.config.getoption("--skip-matplotlib"):
  pytest.skip("skipping due to --skip-matplotlib")
 
- if 'requires_matplotlib' in item.keywords and not HAVE_MATPLOTLIB:
+ if 'matplotlib' in item.keywords and not HAVE_MATPLOTLIB:
  pytest.skip("skipping since matplotlib is not intalled")
 
 

statsmodels/discrete/tests/test_diagnostic.py

@@ -9,6 +9,7 @@
 
 import numpy as np
 from numpy.testing import assert_allclose
+import pytest
 
 from statsmodels.discrete.discrete_model import Poisson
 import statsmodels.discrete._diagnostics_count as dia
@@ -57,6 +58,7 @@ def test_count(self):
  tzi3_1 = (0.79863597832443878, 0.67077736750318928, 2, 2)
  assert_allclose(tzi3, tzi3_1, rtol=5e-4)
 
+ @pytest.mark.matplotlib
  def test_probs(self, close_figures):
  nobs = self.nobs
  probs = self.res.predict_prob()
@@ -68,9 +70,4 @@ def test_probs(self, close_figures):
  assert_allclose(tzi[:2], tzi1, rtol=5e-5)
 
  # smoke test for plot
-
- try:
- import matplotlib.pyplot as plt
- except ImportError:
- return
- fig = dia.plot_probs(freq, probs.mean(0))
+ dia.plot_probs(freq, probs.mean(0))

statsmodels/duration/tests/test_survfunc.py

@@ -188,7 +188,7 @@ def test_survdiff():
  assert_allclose(stat, 13.35259, atol=1e-4, rtol=1e-4)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_plot_km(close_figures):
 
  if pdf_output:

statsmodels/genmod/tests/test_gee.py

@@ -155,7 +155,7 @@ def test_margins_multinomial(self):
  assert_allclose(marg.margeff, np.r_[-0.41197961], rtol=1e-5)
  assert_allclose(marg.margeff_se, np.r_[0.1379962], rtol=1e-6)
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_nominal_plot(self, close_figures):
  np.random.seed(34234)
  endog = np.r_[0, 0, 0, 0, 1, 1, 1, 1]
@@ -801,7 +801,7 @@ def test_nominal_independence(self):
  model1 = NominalGEE(y, x, groups, cov_struct=nmi)
  model1.fit()
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_ordinal_plot(self, close_figures):
  family = Binomial()
 
@@ -1554,7 +1554,7 @@ def test_wrapper(self):
  check_wrapper(rslt2)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_plots(close_figures):
 
  np.random.seed(378)

statsmodels/genmod/tests/test_glm.py

@@ -28,11 +28,6 @@
 DECIMAL_1 = 1
 DECIMAL_0 = 0
 
-try:
- import matplotlib.pyplot as plt
-except:
- pass
-
 pdf_output = False
 
 if pdf_output:
@@ -901,7 +896,7 @@ def test_formula_missing_exposure():
  exposure=exposure, family=family)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_plots(close_figures):
 
  np.random.seed(378)
@@ -914,7 +909,6 @@ def test_plots(close_figures):
  model = sm.GLM(endog, exog, family=sm.families.Binomial())
  result = model.fit()
 
- import matplotlib.pyplot as plt
  import pandas as pd
  from statsmodels.graphics.regressionplots import add_lowess
 

statsmodels/graphics/tests/test_agreement.py

@@ -11,7 +11,7 @@
  pass
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_mean_diff_plot(close_figures):
 
  # Seed the random number generator.

statsmodels/graphics/tests/test_boxplots.py

@@ -10,7 +10,7 @@
  pass
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_violinplot_beanplot(close_figures):
  # Test violinplot and beanplot with the same dataset.
  data = anes96.load_pandas()

statsmodels/graphics/tests/test_correlation.py

@@ -4,13 +4,8 @@
 from statsmodels.graphics.correlation import plot_corr, plot_corr_grid
 from statsmodels.datasets import randhie
 
-try:
- import matplotlib.pyplot as plt
-except ImportError:
- pass
 
-
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_plot_corr(close_figures):
  hie_data = randhie.load_pandas()
  corr_matrix = np.corrcoef(hie_data.data.values.T)
@@ -22,7 +17,7 @@ def test_plot_corr(close_figures):
  plot_corr(corr_matrix, normcolor=True, title='', cmap='jet')
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_plot_corr_grid(close_figures):
  hie_data = randhie.load_pandas()
  corr_matrix = np.corrcoef(hie_data.data.values.T)

statsmodels/graphics/tests/test_dotplot.py

@@ -9,7 +9,6 @@
 
 try:
  import matplotlib.pyplot as plt
- import matplotlib
 except ImportError:
  pass
 
@@ -19,7 +18,7 @@ def close_or_save(pdf, fig):
  pdf.savefig(fig)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_all(close_figures):
 
  if pdf_output:

statsmodels/graphics/tests/test_factorplots.py

@@ -7,7 +7,6 @@
 
 try:
  import matplotlib.pyplot as plt
- import matplotlib
 except ImportError:
  pass
 
@@ -21,17 +20,17 @@ def setup_class(cls):
  cls.duration = np.random.randint(1,3,size=60)
  cls.days = np.log(np.random.randint(1,30, size=60))
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_plot_both(self, close_figures):
  fig = interaction_plot(self.weight, self.duration, self.days,
  colors=['red','blue'], markers=['D','^'], ms=10)
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_plot_rainbow(self, close_figures):
  fig = interaction_plot(self.weight, self.duration, self.days,
  markers=['D','^'], ms=10)
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_plot_pandas(self, close_figures):
  weight = Series(self.weight, name='Weight')
  duration = Series(self.duration, name='Duration')
@@ -44,7 +43,7 @@ def test_plot_pandas(self, close_figures):
  assert_equal(ax.get_ylabel(), 'mean of Days')
  assert_equal(ax.get_xlabel(), 'Weight')
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_plot_string_data(self, close_figures):
  weight = Series(self.weight, name='Weight').astype('str')
  duration = Series(self.duration, name='Duration')
@@ -57,18 +56,18 @@ def test_plot_string_data(self, close_figures):
  assert_equal(ax.get_ylabel(), 'mean of Days')
  assert_equal(ax.get_xlabel(), 'Weight')
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_formatting(self, close_figures):
  fig = interaction_plot(self.weight, self.duration, self.days, colors=['r','g'], linestyles=['--','-.'])
  assert_equal(isinstance(fig, plt.Figure), True)
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_formatting_errors(self, close_figures):
  assert_raises(ValueError, interaction_plot, self.weight, self.duration, self.days, markers=['D'])
  assert_raises(ValueError, interaction_plot, self.weight, self.duration, self.days, colors=['b','r','g'])
  assert_raises(ValueError, interaction_plot, self.weight, self.duration, self.days, linestyles=['--','-.',':'])
 
- @pytest.mark.requires_matplotlib
+ @pytest.mark.matplotlib
  def test_plottype(self, close_figures):
  fig = interaction_plot(self.weight, self.duration, self.days, plottype='line')
  assert_equal(isinstance(fig, plt.Figure), True)

statsmodels/graphics/tests/test_functional.py

@@ -19,7 +19,7 @@
 data = data.raw_data[:, 1:]
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_basic(close_figures):
  _, hdr = hdrboxplot(data, labels=labels, seed=12345)
 
@@ -57,7 +57,7 @@ def test_hdr_basic(close_figures):
  assert_equal(labels[hdr.outliers_idx], outliers)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_basic_brute(close_figures):
  _, hdr = hdrboxplot(data, labels=labels, use_brute=True)
 
@@ -69,7 +69,7 @@ def test_hdr_basic_brute(close_figures):
  assert_almost_equal(hdr.median, median_t, decimal=2)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_plot(close_figures):
  fig = plt.figure()
  ax = fig.add_subplot(111)
@@ -83,7 +83,7 @@ def test_hdr_plot(close_figures):
  ax.set_xlim([-0.2, 11.2])
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_alpha(close_figures):
  _, hdr = hdrboxplot(data, alpha=[0.7], seed=12345)
  extra_quant_t = np.vstack([[25.1, 26.5, 27.0, 26.4, 25.4, 24.1,
@@ -93,7 +93,7 @@ def test_hdr_alpha(close_figures):
  assert_almost_equal(hdr.extra_quantiles, extra_quant_t, decimal=0)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_multiple_alpha(close_figures):
  _, hdr = hdrboxplot(data, alpha=[0.4, 0.92], seed=12345)
  extra_quant_t = [[25.712, 27.052, 27.711, 27.200,
@@ -112,7 +112,7 @@ def test_hdr_multiple_alpha(close_figures):
  decimal=0)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_threshold(close_figures):
  _, hdr = hdrboxplot(data, alpha=[0.8], threshold=0.93, seed=12345)
  labels_pos = np.all(np.in1d(data, hdr.outliers).reshape(data.shape),
@@ -121,15 +121,15 @@ def test_hdr_threshold(close_figures):
  assert_equal([1968, 1982, 1983, 1997, 1998], outliers)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_bw(close_figures):
  _, hdr = hdrboxplot(data, bw='cv_ml', seed=12345)
  median_t = [24.25, 25.64, 25.99, 25.04, 23.71, 22.38,
  21.31, 20.44, 20.24, 20.51, 21.19, 22.38]
  assert_almost_equal(hdr.median, median_t, decimal=2)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_hdr_ncomp(close_figures):
  _, hdr = hdrboxplot(data, ncomp=3, seed=12345)
  median_t = [24.33, 25.71, 26.04, 25.08, 23.74, 22.40,
@@ -172,7 +172,7 @@ def test_banddepth_MBD():
  assert_almost_equal(depth, expected_depth, decimal=4)
 
 
-@pytest.mark.requires_matplotlib
+@pytest.mark.matplotlib
 def test_fboxplot_rainbowplot(close_figures):
  # Test fboxplot and rainbowplot together, is much faster.
  def harmfunc(t):