Skip tests for optional/extra dependencies when not installed

.azure-pipelines/azure-pipelines-base.yml

@@ -5,6 +5,8 @@ jobs:
  variables:
  - name: NUMBA_DISABLE_JIT
  value: 1
+ - name: ARVIZ_CI_MACHINE
+ value: 1
  timeoutInMinutes: 360
  strategy:
  matrix:

.azure-pipelines/azure-pipelines-external.yml

@@ -5,6 +5,8 @@ jobs:
  variables:
  - name: NUMBA_DISABLE_JIT
  value: 1
+ - name: ARVIZ_CI_MACHINE
+ value: 1
  timeoutInMinutes: 360
  strategy:
  matrix:

.gitignore

@@ -62,6 +62,7 @@ target/
 
 # IDE configs
 .idea/
+.vscode/
 
 saved_animations/
 

CHANGELOG.md

@@ -8,6 +8,7 @@
 * Add `num_chains` and `pred_dims` arguments to io_pyro #1090
 * Integrate jointplot into pairplot, add point-estimate and overlay of plot kinds (#1079)
 * Allow xarray.Dataarray input for plots.(#1120)
+* Skip test for optional/extra dependencies when not installed (#1113)
 ### Maintenance and fixes
 * Fixed behaviour of `credible_interval=None` in `plot_posterior` (#1115)
 * Fixed hist kind of `plot_dist` with multidimensional input (#1115)
@@ -212,4 +213,3 @@
 ## v0.3.0 (2018 Dec 14)
 
 * First Beta Release
-

arviz/tests/base_tests/test_diagnostics.py

@@ -1,28 +1,28 @@
 """Test Diagnostic methods"""
 # pylint: disable=redefined-outer-name, no-member, too-many-public-methods
 import os
+
 import numpy as np
-from numpy.testing import assert_almost_equal, assert_array_almost_equal
 import pandas as pd
 import pytest
+from numpy.testing import assert_almost_equal, assert_array_almost_equal
 
-from ...data import load_arviz_data, from_cmdstan
+from ...data import from_cmdstan, load_arviz_data
 from ...plots.plot_utils import xarray_var_iter
-from ...stats import bfmi, rhat, ess, mcse, geweke
+from ...rcparams import rcParams
+from ...stats import bfmi, ess, geweke, mcse, rhat
 from ...stats.diagnostics import (
- ks_summary,
+ _conv_quantile,
  _ess,
  _ess_quantile,
- _multichain_statistics,
  _mc_error,
+ _multichain_statistics,
  _rhat,
  _rhat_rank,
- _z_scale,
- _conv_quantile,
  _split_chains,
+ _z_scale,
+ ks_summary,
 )
-from ...utils import Numba
-from ...rcparams import rcParams
 
 # For tests only, recommended value should be closer to 1.01-1.05
 # See discussion in https://github.com/stan-dev/rstan/pull/618
@@ -536,85 +536,3 @@ def test_split_chain_dims(self, chains, draws):
  if chains is None:
  chains = 1
  assert split_data.shape == (chains * 2, draws // 2)
-
-
-def test_numba_bfmi():
- """Numba test for bfmi."""
- state = Numba.numba_flag
- school = load_arviz_data("centered_eight")
- data_md = np.random.rand(100, 100, 10)
- Numba.disable_numba()
- non_numba = bfmi(school.posterior["mu"].values)
- non_numba_md = bfmi(data_md)
- Numba.enable_numba()
- with_numba = bfmi(school.posterior["mu"].values)
- with_numba_md = bfmi(data_md)
- assert np.allclose(non_numba_md, with_numba_md)
- assert np.allclose(with_numba, non_numba)
- assert state == Numba.numba_flag
-
-
-@pytest.mark.parametrize("method", ("rank", "split", "folded", "z_scale", "identity"))
-def test_numba_rhat(method):
- """Numba test for mcse."""
- state = Numba.numba_flag
- school = np.random.rand(100, 100)
- Numba.disable_numba()
- non_numba = rhat(school, method=method)
- Numba.enable_numba()
- with_numba = rhat(school, method=method)
- assert np.allclose(with_numba, non_numba)
- assert Numba.numba_flag == state
-
-
-@pytest.mark.parametrize("method", ("mean", "sd", "quantile"))
-def test_numba_mcse(method, prob=None):
- """Numba test for mcse."""
- state = Numba.numba_flag
- school = np.random.rand(100, 100)
- if method == "quantile":
- prob = 0.80
- Numba.disable_numba()
- non_numba = mcse(school, method=method, prob=prob)
- Numba.enable_numba()
- with_numba = mcse(school, method=method, prob=prob)
- assert np.allclose(with_numba, non_numba)
- assert Numba.numba_flag == state
-
-
-def test_ks_summary_numba():
- """Numba test for ks_summary."""
- state = Numba.numba_flag
- data = np.random.randn(100, 100)
- Numba.disable_numba()
- non_numba = (ks_summary(data)["Count"]).values
- Numba.enable_numba()
- with_numba = (ks_summary(data)["Count"]).values
- assert np.allclose(non_numba, with_numba)
- assert Numba.numba_flag == state
-
-
-def test_geweke_numba():
- """Numba test for geweke."""
- state = Numba.numba_flag
- data = np.random.randn(100)
- Numba.disable_numba()
- non_numba = geweke(data)
- Numba.enable_numba()
- with_numba = geweke(data)
- assert np.allclose(non_numba, with_numba)
- assert Numba.numba_flag == state
-
-
-@pytest.mark.parametrize("batches", (1, 20))
-@pytest.mark.parametrize("circular", (True, False))
-def test_mcse_error_numba(batches, circular):
- """Numba test for mcse_error."""
- data = np.random.randn(100, 100)
- state = Numba.numba_flag
- Numba.disable_numba()
- non_numba = _mc_error(data, batches=batches, circular=circular)
- Numba.enable_numba()
- with_numba = _mc_error(data, batches=batches, circular=circular)
- assert np.allclose(non_numba, with_numba)
- assert state == Numba.numba_flag

arviz/tests/base_tests/test_diagnostics_numba.py

@@ -0,0 +1,104 @@
+"""Test Diagnostic methods"""
+import importlib
+
+# pylint: disable=redefined-outer-name, no-member, too-many-public-methods
+import numpy as np
+import pytest
+
+from ...data import load_arviz_data
+from ..helpers import running_on_ci
+from ...rcparams import rcParams
+from ...stats import bfmi, geweke, mcse, rhat
+from ...stats.diagnostics import _mc_error, ks_summary
+from ...utils import Numba
+from .test_diagnostics import data # pylint: disable=unused-import
+
+
+pytestmark = pytest.mark.skipif( # pylint: disable=invalid-name
+ (importlib.util.find_spec("numba") is None) & ~running_on_ci(),
+ reason="test requires numba which is not installed",
+)
+
+rcParams["data.load"] = "eager"
+
+
+def test_numba_bfmi():
+ """Numba test for bfmi."""
+ state = Numba.numba_flag
+ school = load_arviz_data("centered_eight")
+ data_md = np.random.rand(100, 100, 10)
+ Numba.disable_numba()
+ non_numba = bfmi(school.posterior["mu"].values)
+ non_numba_md = bfmi(data_md)
+ Numba.enable_numba()
+ with_numba = bfmi(school.posterior["mu"].values)
+ with_numba_md = bfmi(data_md)
+ assert np.allclose(non_numba_md, with_numba_md)
+ assert np.allclose(with_numba, non_numba)
+ assert state == Numba.numba_flag
+
+
+@pytest.mark.parametrize("method", ("rank", "split", "folded", "z_scale", "identity"))
+def test_numba_rhat(method):
+ """Numba test for mcse."""
+ state = Numba.numba_flag
+ school = np.random.rand(100, 100)
+ Numba.disable_numba()
+ non_numba = rhat(school, method=method)
+ Numba.enable_numba()
+ with_numba = rhat(school, method=method)
+ assert np.allclose(with_numba, non_numba)
+ assert Numba.numba_flag == state
+
+
+@pytest.mark.parametrize("method", ("mean", "sd", "quantile"))
+def test_numba_mcse(method, prob=None):
+ """Numba test for mcse."""
+ state = Numba.numba_flag
+ school = np.random.rand(100, 100)
+ if method == "quantile":
+ prob = 0.80
+ Numba.disable_numba()
+ non_numba = mcse(school, method=method, prob=prob)
+ Numba.enable_numba()
+ with_numba = mcse(school, method=method, prob=prob)
+ assert np.allclose(with_numba, non_numba)
+ assert Numba.numba_flag == state
+
+
+def test_ks_summary_numba():
+ """Numba test for ks_summary."""
+ state = Numba.numba_flag
+ data = np.random.randn(100, 100)
+ Numba.disable_numba()
+ non_numba = (ks_summary(data)["Count"]).values
+ Numba.enable_numba()
+ with_numba = (ks_summary(data)["Count"]).values
+ assert np.allclose(non_numba, with_numba)
+ assert Numba.numba_flag == state
+
+
+def test_geweke_numba():
+ """Numba test for geweke."""
+ state = Numba.numba_flag
+ data = np.random.randn(100)
+ Numba.disable_numba()
+ non_numba = geweke(data)
+ Numba.enable_numba()
+ with_numba = geweke(data)
+ assert np.allclose(non_numba, with_numba)
+ assert Numba.numba_flag == state
+
+
+@pytest.mark.parametrize("batches", (1, 20))
+@pytest.mark.parametrize("circular", (True, False))
+def test_mcse_error_numba(batches, circular):
+ """Numba test for mcse_error."""
+ data = np.random.randn(100, 100)
+ state = Numba.numba_flag
+ Numba.disable_numba()
+ non_numba = _mc_error(data, batches=batches, circular=circular)
+ Numba.enable_numba()
+ with_numba = _mc_error(data, batches=batches, circular=circular)
+ assert np.allclose(non_numba, with_numba)
+ assert state == Numba.numba_flag

arviz/tests/base_tests/test_helpers.py

@@ -0,0 +1,18 @@
+import pytest
+from _pytest.outcomes import Skipped
+
+from ..helpers import importorskip
+
+
+def test_importorskip_local(monkeypatch):
+ """Test ``importorskip`` run on local machine with non-existent module, which should skip."""
+ monkeypatch.delenv("ARVIZ_CI_MACHINE", raising=False)
+ with pytest.raises(Skipped):
+ importorskip("non-existent-function")
+
+
+def test_importorskip_ci(monkeypatch):
+ """Test ``importorskip`` run on CI machine with non-existent module, which should fail."""
+ monkeypatch.setenv("ARVIZ_CI_MACHINE", 1)
+ with pytest.raises(ModuleNotFoundError):
+ importorskip("non-existent-function")

arviz/tests/base_tests/test_plot_utils.py

@@ -1,19 +1,22 @@
 # pylint: disable=redefined-outer-name
+import importlib
+
 import numpy as np
-import xarray as xr
 import pytest
+import xarray as xr
 
 from ...data import from_dict
+from ..helpers import running_on_ci
 from ...plots.plot_utils import (
- make_2d,
- xarray_to_ndarray,
- xarray_var_iter,
- get_bins,
- get_coords,
  filter_plotters_list,
  format_sig_figs,
+ get_bins,
+ get_coords,
  get_plotting_function,
+ make_2d,
  matplotlib_kwarg_dealiaser,
+ xarray_to_ndarray,
+ xarray_var_iter,
 )
 from ...rcparams import rc_context
 
@@ -194,6 +197,10 @@ def test_filter_plotter_list_warning():
  assert len(plotters_filtered) == 5
 
 
+@pytest.mark.skipif(
+ (importlib.util.find_spec("bokeh") is None) & ~running_on_ci(),
+ reason="test requires bokeh which is not installed",
+)
 def test_bokeh_import():
  """Tests that correct method is returned on bokeh import"""
  plot = get_plotting_function("plot_dist", "distplot", "bokeh")

arviz/tests/base_tests/test_plots_bokeh.py

@@ -1,21 +1,22 @@
 """Tests use the 'bokeh' backend."""
 # pylint: disable=redefined-outer-name,too-many-lines
 from copy import deepcopy
-import bokeh.plotting as bkp
-from pandas import DataFrame
+
 import numpy as np
 import pytest
+from pandas import DataFrame # pylint: disable=wrong-import-position
 
-from ...data import from_dict, load_arviz_data
-from ..helpers import ( # pylint: disable=unused-import
+from ...data import from_dict, load_arviz_data # pylint: disable=wrong-import-position
+from ..helpers import ( # pylint: disable=unused-import, wrong-import-position
+ create_model,
+ create_multidimensional_model,
  eight_schools_params,
+ importorskip,
  models,
- create_model,
  multidim_models,
- create_multidimensional_model,
 )
-from ...rcparams import rcParams, rc_context
-from ...plots import (
+from ...rcparams import rc_context, rcParams # pylint: disable=wrong-import-position
+from ...plots import ( # pylint: disable=wrong-import-position
  plot_autocorr,
  plot_compare,
  plot_density,
@@ -31,14 +32,18 @@
  plot_loo_pit,
  plot_mcse,
  plot_pair,
- plot_rank,
- plot_trace,
  plot_parallel,
  plot_posterior,
  plot_ppc,
+ plot_rank,
+ plot_trace,
  plot_violin,
 )
-from ...stats import compare, loo, waic
+from ...stats import compare, loo, waic # pylint: disable=wrong-import-position
+
+# Skip tests if bokeh not installed
+bkp = importorskip("bokeh.plotting") # pylint: disable=invalid-name
+
 
 rcParams["data.load"] = "eager"
 

arviz/tests/base_tests/test_plots_matplotlib.py

@@ -153,12 +153,8 @@ def test_plot_trace(models, kwargs):
  assert axes.shape
 
 
-@pytest.mark.parametrize(
- "compact", [True, False],
-)
-@pytest.mark.parametrize(
- "combined", [True, False],
-)
+@pytest.mark.parametrize("compact", [True, False])
+@pytest.mark.parametrize("combined", [True, False])
 def test_plot_trace_legend(compact, combined):
  idata = load_arviz_data("rugby")
  axes = plot_trace(