Merge pull request #46 from astrofrog/infrastructure

Update infratructure and fix compatibility with latest version of Hypothesis

.gitignore

@@ -59,3 +59,7 @@ htmlcov
 
 # PyCharm
 .idea
+
+.tox
+.tmp
+fast_histogram/version.py

CHANGES.rst

@@ -1,7 +1,8 @@
 0.8 (unreleased)
 ----------------
 
-- No changes yet.
+- Fixed compatibility of test suite with latest version of the
+  hypothesis package. [#40]
 
 0.7 (2019-01-09)
 ----------------

MANIFEST.in

@@ -1,3 +1,4 @@
 include LICENSE
 include README.rst
 include CHANGES.rst
+include pyproject.toml

azure-pipelines.yml

@@ -0,0 +1,44 @@
+resources:
+  repositories:
+  - repository: OpenAstronomy
+    type: github
+    endpoint: astrofrog
+    name: OpenAstronomy/azure-pipelines-templates
+    ref: master
+
+jobs:
+
+- template: run-tox-env.yml@OpenAstronomy
+  parameters:
+
+    coverage: codecov
+
+    envs:
+
+    - linux32: py36-test-numpy113
+    - linux32: py36-test-numpy114
+    - linux32: py36-test-numpy115
+    - linux32: py37-test-numpy116
+    - linux32: py37-test-numpy117
+    # - linux32: py38-test-numpy118
+
+    - linux: py36-test-numpy113
+    - linux: py36-test-numpy114
+    - linux: py36-test-numpy115
+    - linux: py37-test-numpy116
+    - linux: py37-test-numpy117
+    - linux: py38-test-numpy118
+
+    - macos: py36-test-numpy113
+    - macos: py36-test-numpy114
+    - macos: py36-test-numpy115
+    - macos: py37-test-numpy116
+    - macos: py37-test-numpy117
+    - macos: py38-test-numpy118
+
+    - windows: py36-test-numpy113
+    - windows: py36-test-numpy114
+    - windows: py36-test-numpy115
+    - windows: py37-test-numpy116
+    - windows: py37-test-numpy117
+    - windows: py38-test-numpy118

fast_histogram/__init__.py

@@ -1,3 +1,2 @@
 from .histogram import *
-
-__version__ = "0.8.dev0"
+from .version import version as __version__

fast_histogram/tests/test_histogram.py

@@ -2,7 +2,7 @@
 
 import pytest
 
-from hypothesis import given, settings, example, assume
+from hypothesis import given, settings, assume
 from hypothesis import strategies as st
 from hypothesis.extra.numpy import arrays
 
@@ -14,27 +14,34 @@
 # comparing to Numpy) test cases.
 
 
-@given(size=st.integers(0, 100),
+@given(values=arrays(dtype='<f8', shape=st.integers(0, 200),
+                     elements=st.floats(-1000, 1000), unique=True),
        nx=st.integers(1, 10),
-       xmin=st.floats(-1e10, 1e10), xmax=st.floats(-1e10, 1e10),
+       xmin=st.floats(-1e10, 1e10),
+       xmax=st.floats(-1e10, 1e10),
        weights=st.booleans(),
        dtype=st.sampled_from(['>f4', '<f4', '>f8', '<f8']))
-@settings(max_examples=5000)
-def test_1d_compare_with_numpy(size, nx, xmin, xmax, weights, dtype):
+@settings(max_examples=500)
+def test_1d_compare_with_numpy(values, nx, xmin, xmax, weights, dtype):
 
     if xmax <= xmin:
         return
 
-    x = arrays(dtype, size, elements=st.floats(-1000, 1000)).example()
+    values = values.astype(dtype)
+
+    size = len(values) // 2
+
     if weights:
-        w = arrays(dtype, size, elements=st.floats(-1000, 1000)).example()
+        w = values[:size]
     else:
         w = None
 
+    x = values[size:size * 2]
+
     try:
         reference = np.histogram(x, bins=nx, weights=w, range=(xmin, xmax))[0]
     except ValueError:
-        if 'f4' in dtype:
+        if 'f4' in str(x.dtype):
             # Numpy has a bug in certain corner cases
             # https://github.com/numpy/numpy/issues/11586
             return
@@ -43,7 +50,8 @@ def test_1d_compare_with_numpy(size, nx, xmin, xmax, weights, dtype):
 
     # First, check the Numpy result because it sometimes doesn't make sense. See
     # bug report https://github.com/numpy/numpy/issues/9435
-    inside = (x <= xmax) & (x >= xmin)
+    # FIXME: for now use < since that's what our algorithm does
+    inside = (x < xmax) & (x >= xmin)
     if weights:
         assume(np.allclose(np.sum(w[inside]), np.sum(reference)))
     else:
@@ -56,35 +64,40 @@ def test_1d_compare_with_numpy(size, nx, xmin, xmax, weights, dtype):
     # for 1D arrays. Since this is a summation variable it makes sense to
     # return 64-bit, so rather than changing the behavior of histogram1d, we
     # cast to 32-bit float here.
-    if 'f4' in dtype:
-        fast = fast.astype(np.float32)
+    if x.dtype.kind == 'f' and x.dtype.itemsize == 4:
+        rtol = 1e-7
+    else:
+        rtol = 1e-14
 
-    np.testing.assert_equal(fast, reference)
+    np.testing.assert_allclose(fast, reference, rtol=rtol)
 
 
-@given(size=st.integers(0, 100),
+@given(values=arrays(dtype='<f8', shape=st.integers(0, 300),
+                     elements=st.floats(-1000, 1000), unique=True),
        nx=st.integers(1, 10),
        xmin=st.floats(-1e10, 1e10), xmax=st.floats(-1e10, 1e10),
        ny=st.integers(1, 10),
        ymin=st.floats(-1e10, 1e10), ymax=st.floats(-1e10, 1e10),
        weights=st.booleans(),
        dtype=st.sampled_from(['>f4', '<f4', '>f8', '<f8']))
-@settings(max_examples=5000)
-@example(size=5, nx=1, xmin=0.0, xmax=84.17833763374462, ny=1, ymin=-999999999.9999989, ymax=0.0, weights=False, dtype='<f8')
-@example(size=1, nx=1, xmin=-2.2204460492503135e-06, xmax=0.0, ny=1, ymin=0.0, ymax=1.1102230246251567e-05, weights=False, dtype='<f8')
-@example(size=3, nx=1, xmin=0.0, xmax=841.7833941010146, ny=1, ymin=-135.92383885097095, ymax=0.0, weights=True, dtype='>f8')
-def test_2d_compare_with_numpy(size, nx, xmin, xmax, ny, ymin, ymax, weights, dtype):
+@settings(max_examples=500)
+def test_2d_compare_with_numpy(values, nx, xmin, xmax, ny, ymin, ymax, weights, dtype):
 
     if xmax <= xmin or ymax <= ymin:
         return
 
-    x = arrays(dtype, size, elements=st.floats(-1000, 1000)).example()
-    y = arrays(dtype, size, elements=st.floats(-1000, 1000)).example()
+    values = values.astype(dtype)
+
+    size = len(values) // 3
+
     if weights:
-        w = arrays(dtype, size, elements=st.floats(-1000, 1000)).example()
+        w = values[:size]
     else:
         w = None
 
+    x = values[size:size * 2]
+    y = values[size * 2:size * 3]
+
     try:
         reference = np.histogram2d(x, y, bins=(nx, ny), weights=w,
                                    range=((xmin, xmax), (ymin, ymax)))[0]
@@ -93,8 +106,9 @@ def test_2d_compare_with_numpy(size, nx, xmin, xmax, ny, ymin, ymax, weights, dt
         return
 
     # First, check the Numpy result because it sometimes doesn't make sense. See
-    # bug report https://github.com/numpy/numpy/issues/9435
-    inside = (x <= xmax) & (x >= xmin) & (y <= ymax) & (y >= ymin)
+    # bug report https://github.com/numpy/numpy/issues/9435.
+    # FIXME: for now use < since that's what our algorithm does
+    inside = (x < xmax) & (x >= xmin) & (y < ymax) & (y >= ymin)
     if weights:
         assume(np.allclose(np.sum(w[inside]), np.sum(reference)))
     else:
@@ -104,7 +118,12 @@ def test_2d_compare_with_numpy(size, nx, xmin, xmax, ny, ymin, ymax, weights, dt
     fast = histogram2d(x, y, bins=(nx, ny), weights=w,
                        range=((xmin, xmax), (ymin, ymax)))
 
-    np.testing.assert_equal(fast, reference)
+    if x.dtype.kind == 'f' and x.dtype.itemsize == 4:
+        rtol = 1e-7
+    else:
+        rtol = 1e-14
+
+    np.testing.assert_allclose(fast, reference, rtol=rtol)
 
 
 def test_nd_arrays():

pyproject.toml

@@ -0,0 +1,6 @@
+[build-system]
+requires = ["setuptools",
+            "setuptools_scm",
+            "wheel",
+            "oldest-supported-numpy"]
+build-backend = 'setuptools.build_meta'

setup.cfg

@@ -0,0 +1,23 @@
+[metadata]
+name = fast-histogram
+url = https://github.com/astrofrog/fast-histogram
+author = Thomas Robitaille
+author_email = [email protected]
+license = BSD
+description = Fast simple 1D and 2D histograms
+long_description = file: README.rst
+
+[options]
+zip_safe = False
+packages = find:
+setup_requires =
+	setuptools_scm
+install_requires =
+	numpy
+python_requires = >=3.6
+
+[options.extras_require]
+test =
+    pytest
+	pytest-cov
+	hypothesis[numpy]