Compare revisions

Jon Crall · Jon Crall · Jon Crall · Jon Crall · Jon Crall · Jon Crall
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
 # Autogenerated by ~/code/xcookie/xcookie/builders/gitlab_ci.py

-include:
- local: .gitlab/rules.yml
 stages:
 # TEMPLATES
 - lint
 - build
- test
 - gpgsign
+- test
 - deploy
 .common_template: &common_template
  tags:
@@ -28,7 +26,17 @@ stages:
  cache:
    paths:
    - .cache/pip
-.build_template: &build_template
+.build_sdist_template: &build_sdist_template
+  <<: *common_template
+  stage: build
+  script:
+  - python -m pip install setuptools>=0.8 wheel build twine
+  - python -m build --sdist --outdir dist
+  - python -m twine check ./dist/kwarray*.tar.gz
+  artifacts:
+    paths:
+    - ./dist/kwarray*.tar.gz
+.build_wheel_template: &build_wheel_template
  <<: *common_template
  stage: build
  before_script:
@@ -66,10 +74,16 @@ stages:
  - echo "Installing helpers"
  - pip install setuptools>=0.8 setuptools_scm wheel build -U
  - pip install tomli pkginfo
-  - export WHEEL_FPATH=$(python -c "import pathlib; 
-    print(str(sorted(pathlib.Path('dist').glob('kwarray*.whl'))[-1]).replace(chr(92),
-    chr(47)))")
-  - export MOD_VERSION=$(python -c "from pkginfo import Wheel; print(Wheel('$WHEEL_FPATH').version)")
+  - "export WHEEL_FPATH=$(python -c \"if 1:\n    import pathlib\n    dist_dpath =
+    pathlib.Path('dist')\n    candidates = list(dist_dpath.glob('kwarray*.whl'))\n\
+    \    candidates += list(dist_dpath.glob('kwarray*.tar.gz'))\n    fpath = sorted(candidates)[-1]\n\
+    \    print(str(fpath).replace(chr(92), chr(47)))\n\")"
+  - "export MOD_VERSION=$(python -c \"if 1:\n    from pkginfo import Wheel, SDist\n\
+    \    fpath = '$WHEEL_FPATH'\n    cls = Wheel if fpath.endswith('.whl') else SDist\n\
+    \    print(cls(fpath).version)\n\")"
+  - echo "WHEEL_FPATH=$WHEEL_FPATH"
+  - echo "INSTALL_EXTRAS=$INSTALL_EXTRAS"
+  - echo "MOD_VERSION=$MOD_VERSION"
  - pip install --prefer-binary "kwarray[$INSTALL_EXTRAS]==$MOD_VERSION" -f dist
  - echo "Install finished."
  - echo "Creating test sandbox directory"
@@ -115,10 +129,16 @@ stages:
  - echo "Installing helpers"
  - pip install setuptools>=0.8 setuptools_scm wheel build -U
  - pip install tomli pkginfo
-  - export WHEEL_FPATH=$(python -c "import pathlib; 
-    print(str(sorted(pathlib.Path('dist').glob('kwarray*.whl'))[-1]).replace(chr(92),
-    chr(47)))")
-  - export MOD_VERSION=$(python -c "from pkginfo import Wheel; print(Wheel('$WHEEL_FPATH').version)")
+  - "export WHEEL_FPATH=$(python -c \"if 1:\n    import pathlib\n    dist_dpath =
+    pathlib.Path('dist')\n    candidates = list(dist_dpath.glob('kwarray*.whl'))\n\
+    \    candidates += list(dist_dpath.glob('kwarray*.tar.gz'))\n    fpath = sorted(candidates)[-1]\n\
+    \    print(str(fpath).replace(chr(92), chr(47)))\n\")"
+  - "export MOD_VERSION=$(python -c \"if 1:\n    from pkginfo import Wheel, SDist\n\
+    \    fpath = '$WHEEL_FPATH'\n    cls = Wheel if fpath.endswith('.whl') else SDist\n\
+    \    print(cls(fpath).version)\n\")"
+  - echo "WHEEL_FPATH=$WHEEL_FPATH"
+  - echo "INSTALL_EXTRAS=$INSTALL_EXTRAS"
+  - echo "MOD_VERSION=$MOD_VERSION"
  - pip install --prefer-binary "kwarray[$INSTALL_EXTRAS]==$MOD_VERSION" -f dist
  - echo "Install finished."
  - echo "Creating test sandbox directory"
@@ -164,10 +184,16 @@ stages:
  - echo "Installing helpers"
  - pip install setuptools>=0.8 setuptools_scm wheel build -U
  - pip install tomli pkginfo
-  - export WHEEL_FPATH=$(python -c "import pathlib; 
-    print(str(sorted(pathlib.Path('dist').glob('kwarray*.whl'))[-1]).replace(chr(92),
-    chr(47)))")
-  - export MOD_VERSION=$(python -c "from pkginfo import Wheel; print(Wheel('$WHEEL_FPATH').version)")
+  - "export WHEEL_FPATH=$(python -c \"if 1:\n    import pathlib\n    dist_dpath =
+    pathlib.Path('dist')\n    candidates = list(dist_dpath.glob('kwarray*.whl'))\n\
+    \    candidates += list(dist_dpath.glob('kwarray*.tar.gz'))\n    fpath = sorted(candidates)[-1]\n\
+    \    print(str(fpath).replace(chr(92), chr(47)))\n\")"
+  - "export MOD_VERSION=$(python -c \"if 1:\n    from pkginfo import Wheel, SDist\n\
+    \    fpath = '$WHEEL_FPATH'\n    cls = Wheel if fpath.endswith('.whl') else SDist\n\
+    \    print(cls(fpath).version)\n\")"
+  - echo "WHEEL_FPATH=$WHEEL_FPATH"
+  - echo "INSTALL_EXTRAS=$INSTALL_EXTRAS"
+  - echo "MOD_VERSION=$MOD_VERSION"
  - pip install --prefer-binary "kwarray[$INSTALL_EXTRAS]==$MOD_VERSION" -f dist
  - echo "Install finished."
  - echo "Creating test sandbox directory"
@@ -213,10 +239,16 @@ stages:
  - echo "Installing helpers"
  - pip install setuptools>=0.8 setuptools_scm wheel build -U
  - pip install tomli pkginfo
-  - export WHEEL_FPATH=$(python -c "import pathlib; 
-    print(str(sorted(pathlib.Path('dist').glob('kwarray*.whl'))[-1]).replace(chr(92),
-    chr(47)))")
-  - export MOD_VERSION=$(python -c "from pkginfo import Wheel; print(Wheel('$WHEEL_FPATH').version)")
+  - "export WHEEL_FPATH=$(python -c \"if 1:\n    import pathlib\n    dist_dpath =
+    pathlib.Path('dist')\n    candidates = list(dist_dpath.glob('kwarray*.whl'))\n\
+    \    candidates += list(dist_dpath.glob('kwarray*.tar.gz'))\n    fpath = sorted(candidates)[-1]\n\
+    \    print(str(fpath).replace(chr(92), chr(47)))\n\")"
+  - "export MOD_VERSION=$(python -c \"if 1:\n    from pkginfo import Wheel, SDist\n\
+    \    fpath = '$WHEEL_FPATH'\n    cls = Wheel if fpath.endswith('.whl') else SDist\n\
+    \    print(cls(fpath).version)\n\")"
+  - echo "WHEEL_FPATH=$WHEEL_FPATH"
+  - echo "INSTALL_EXTRAS=$INSTALL_EXTRAS"
+  - echo "MOD_VERSION=$MOD_VERSION"
  - pip install --prefer-binary "kwarray[$INSTALL_EXTRAS]==$MOD_VERSION" -f dist
  - echo "Install finished."
  - echo "Creating test sandbox directory"
@@ -241,54 +273,16 @@ stages:
  - |-
    python -m pytest --verbose -p pytester -p no:doctest --xdoctest --cov-config ../pyproject.toml --cov-report term --durations=100 --cov="$MOD_NAME" "$MOD_DPATH" ../tests
  - echo "pytest command finished, moving the coverage file to the repo root"
-build/cp36-linux-x86_64:
-  <<: *build_template
-  image: python:3.6
-test/minimal-loose/cp36-linux-x86_64:
-  <<: *test_minimal-loose_template
-  image: python:3.6
-  needs:
-  - build/cp36-linux-x86_64
-test/full-loose/cp36-linux-x86_64:
-  <<: *test_full-loose_template
-  image: python:3.6
-  needs:
-  - build/cp36-linux-x86_64
-test/minimal-strict/cp36-linux-x86_64:
-  <<: *test_minimal-strict_template
-  image: python:3.6
-  needs:
-  - build/cp36-linux-x86_64
-test/full-strict/cp36-linux-x86_64:
-  <<: *test_full-strict_template
-  image: python:3.6
-  needs:
-  - build/cp36-linux-x86_64
-build/cp37-linux-x86_64:
-  <<: *build_template
-  image: python:3.7
-test/minimal-loose/cp37-linux-x86_64:
+build/sdist:
+  <<: *build_sdist_template
+  image: python:3.11
+test/sdist/minimal-loose/cp311-linux-x86_64:
  <<: *test_minimal-loose_template
-  image: python:3.7
-  needs:
-  - build/cp37-linux-x86_64
-test/full-loose/cp37-linux-x86_64:
-  <<: *test_full-loose_template
-  image: python:3.7
-  needs:
-  - build/cp37-linux-x86_64
-test/minimal-strict/cp37-linux-x86_64:
-  <<: *test_minimal-strict_template
-  image: python:3.7
-  needs:
-  - build/cp37-linux-x86_64
-test/full-strict/cp37-linux-x86_64:
-  <<: *test_full-strict_template
-  image: python:3.7
+  image: python:3.11
  needs:
-  - build/cp37-linux-x86_64
+  - build/sdist
 build/cp38-linux-x86_64:
-  <<: *build_template
+  <<: *build_wheel_template
  image: python:3.8
 test/minimal-loose/cp38-linux-x86_64:
  <<: *test_minimal-loose_template
@@ -311,7 +305,7 @@ test/full-strict/cp38-linux-x86_64:
  needs:
  - build/cp38-linux-x86_64
 build/cp39-linux-x86_64:
-  <<: *build_template
+  <<: *build_wheel_template
  image: python:3.9
 test/minimal-loose/cp39-linux-x86_64:
  <<: *test_minimal-loose_template
@@ -334,7 +328,7 @@ test/full-strict/cp39-linux-x86_64:
  needs:
  - build/cp39-linux-x86_64
 build/cp310-linux-x86_64:
-  <<: *build_template
+  <<: *build_wheel_template
  image: python:3.10
 test/minimal-loose/cp310-linux-x86_64:
  <<: *test_minimal-loose_template
@@ -357,7 +351,7 @@ test/full-strict/cp310-linux-x86_64:
  needs:
  - build/cp310-linux-x86_64
 build/cp311-linux-x86_64:
-  <<: *build_template
+  <<: *build_wheel_template
  image: python:3.11
 test/minimal-loose/cp311-linux-x86_64:
  <<: *test_minimal-loose_template
@@ -380,7 +374,7 @@ test/full-strict/cp311-linux-x86_64:
  needs:
  - build/cp311-linux-x86_64
 build/cp312-linux-x86_64:
-  <<: *build_template
+  <<: *build_wheel_template
  image: python:3.12
 test/minimal-loose/cp312-linux-x86_64:
  <<: *test_minimal-loose_template
@@ -419,6 +413,7 @@ gpgsign/wheels:
  artifacts:
    paths:
    - dist/*.asc
+    - dist/*.tar.gz
    - dist/*.whl
    - dist/*.ots
  only:
@@ -429,21 +424,6 @@ gpgsign/wheels:
    - master
    - main
    - release
-  needs:
-  - job: build/cp36-linux-x86_64
-    artifacts: true
-  - job: build/cp37-linux-x86_64
-    artifacts: true
-  - job: build/cp38-linux-x86_64
-    artifacts: true
-  - job: build/cp39-linux-x86_64
-    artifacts: true
-  - job: build/cp310-linux-x86_64
-    artifacts: true
-  - job: build/cp311-linux-x86_64
-    artifacts: true
-  - job: build/cp312-linux-x86_64
-    artifacts: true
  script:
  - ls dist
  - export GPG_EXECUTABLE=gpg
@@ -466,7 +446,7 @@ gpgsign/wheels:
  - GPG_SIGN_CMD="$GPG_EXECUTABLE --batch --yes --detach-sign --armor --local-user
    $GPG_KEYID"
  - |-
-    WHEEL_PATHS=(dist/*.whl)
+    WHEEL_PATHS=(dist/*.whl dist/*.tar.gz)
    WHEEL_PATHS_STR=$(printf '"%s" ' "${WHEEL_PATHS[@]}")
    echo "$WHEEL_PATHS_STR"
    for WHEEL_PATH in "${WHEEL_PATHS[@]}"
@@ -479,7 +459,20 @@ gpgsign/wheels:
    done
  - ls dist
  - python -m pip install opentimestamps-client
-  - ots stamp dist/*.whl dist/*.asc
+  - ots stamp dist/*.tar.gz dist/*.whl dist/*.asc
+  needs:
+  - job: build/sdist
+    artifacts: true
+  - job: build/cp38-linux-x86_64
+    artifacts: true
+  - job: build/cp39-linux-x86_64
+    artifacts: true
+  - job: build/cp310-linux-x86_64
+    artifacts: true
+  - job: build/cp311-linux-x86_64
+    artifacts: true
+  - job: build/cp312-linux-x86_64
+    artifacts: true
 deploy/wheels:
  <<: *common_template
  image: python:3.11
@@ -491,7 +484,7 @@ deploy/wheels:
  - pip install pyopenssl ndg-httpsclient pyasn1 requests[security] twine -U
  - ls dist
  - |-
-    WHEEL_PATHS=(dist/*.whl)
+    WHEEL_PATHS=(dist/*.whl dist/*.tar.gz)
    WHEEL_PATHS_STR=$(printf '"%s" ' "${WHEEL_PATHS[@]}")
    source dev/secrets_configuration.sh
    TWINE_PASSWORD=${!VARNAME_TWINE_PASSWORD}
@@ -500,7 +493,7 @@ deploy/wheels:
    for WHEEL_PATH in "${WHEEL_PATHS[@]}"
    do
        twine check $WHEEL_PATH.asc $WHEEL_PATH
-        twine upload --username $TWINE_USERNAME --password $TWINE_PASSWORD $WHEEL_PATH.asc $WHEEL_PATH || echo "upload already exists"
+        twine upload --username $TWINE_USERNAME --password $TWINE_PASSWORD $WHEEL_PATH || echo "upload already exists"
    done
  - |-
    # Have the server git-tag the release and push the tags

--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -4,10 +4,17 @@ This changelog follows the specifications detailed in: [Keep a Changelog](https:
 This project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html), although we have not yet reached a `1.0.0` release.


-## Version 0.6.20 - Unreleased
+## Version 0.7.0 - Unreleased

+### Removed
+* Removed support for Python 3.6 and 3.7

-## Version 0.6.19 - Released 2024-08-14
+### Fixed
+* Now correctly respect the shape arguments in `kwarray.distributions.Mixture.sample`
+* Binomial was previously broken and now returns correct values from sample.
+
+
+## Version 0.6.19 - Released 2024-06-19

 ### Added


--- a/MANIFEST.in
+++ b/MANIFEST.in
+include requirements/*.txt
\ No newline at end of file
--- a/dev/ci_public_gpg_key.pgp.enc
+++ b/dev/ci_public_gpg_key.pgp.enc
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--- a/dev/ci_secret_gpg_subkeys.pgp.enc
+++ b/dev/ci_secret_gpg_subkeys.pgp.enc
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--- a/dev/gpg_owner_trust.enc
+++ b/dev/gpg_owner_trust.enc
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--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -17,7 +17,7 @@ Notes:
    # need to edit the conf.py

    cd ~/code/kwarray/docs
-    sphinx-apidoc --private --separate -f -o ~/code/kwarray/docs/source/auto ~/code/kwarray/kwarray
+    sphinx-apidoc --private --separate --force --output-dir ~/code/kwarray/docs/source/auto ~/code/kwarray/kwarray

    # Note: the module should importable before running this
    # (e.g. install it in developer mode or munge the PYTHONPATH)
@@ -37,17 +37,17 @@ Notes:

        ### For gitlab

-        The user will need to enable the repo on their readthedocs account:
-        https://readthedocs.org/dashboard/import/manual/?
-
        To enable the read-the-docs go to https://readthedocs.org/dashboard/ and login

-        Make sure you have a .readthedocs.yml file
+        The user will need to enable the repo on their readthedocs account:
+        https://readthedocs.org/dashboard/import/manual/?

-        Click import project: (for github you can select, but gitlab you need to import manually)
+        Enter the following information:
            Set the Repository NAME: kwarray
            Set the Repository URL: https://gitlab.kitware.com/computer-vision/kwarray

+        Make sure you have a .readthedocs.yml file
+
        For gitlab you also need to setup an integrations. Navigate to:

            https://readthedocs.org/dashboard/kwarray/integrations/create/

--- a/kwarray/__init__.py
+++ b/kwarray/__init__.py
@@ -25,7 +25,7 @@ __explicit__ = [
    'ArrayAPI', 'dtype_info',
 ]

-__version__ = '0.6.20'
+__version__ = '0.7.0'

 from kwarray.arrayapi import ArrayAPI, dtype_info
 # Everything after this point is autogenerated

--- a/kwarray/arrayapi.py
+++ b/kwarray/arrayapi.py
@@ -65,6 +65,11 @@ import sys
 import ubelt as ub
 from functools import partial

+try:
+    from functools import cache
+except ImportError:
+    from ubelt import memoize as cache
+
 try:
    from packaging.version import parse as Version
 except ImportError:
@@ -150,7 +155,7 @@ Numeric = Union[Number, ArrayLike, Tensor]
 """


-class _ImplRegistry(object):
+class _ImplRegistry:
    def __init__(self):
        self.registered = {
            'torch': {},
@@ -217,6 +222,17 @@ class _ImplRegistry(object):
        """
        Checks to make sure all methods are implemented in both
        torch and numpy implementations as well as exposed in the ArrayAPI.
+
+        This is intended for developer use.
+
+        CommandLine:
+            REGEN=1 xdoctest -m kwarray.arrayapi _ImplRegistry._ensure_datamethods_names_are_registered
+
+        Example:
+            >>> # xdoctest: +REQUIRES(env:REGEN)
+            >>> import kwarray
+            >>> self = kwarray.arrayapi._REGISTERY
+            >>> self._ensure_datamethods_names_are_registered()
        """
        # Check that we didn't forget to add anything
        # api_names = {
@@ -288,7 +304,7 @@ _numpymethod = partial(_REGISTERY._implmethod, impl='numpy')
 _apimethod = _REGISTERY._apimethod


-class TorchImpls(object):
+class TorchImpls:
    """
    Torch backend for the ArrayAPI API
    """
@@ -1158,7 +1174,7 @@ class TorchImpls(object):
            return torch.softmax(data, dim=axis)


-class NumpyImpls(object):
+class NumpyImpls:
    """
    Numpy backend for the ArrayAPI API
    """
@@ -1658,6 +1674,9 @@ class ArrayAPI:

    array_equal = _apimethod('array_equal')

+    isclose = _apimethod('isclose', func_type='data_func')
+    allclose = _apimethod('allclose', func_type='data_func')
+
    log2 = _apimethod('log2', func_type='data_func')
    log = _apimethod('log', func_type='data_func')
    copy = _apimethod('copy', func_type='data_func')
@@ -1682,7 +1701,7 @@ TorchNumpyCompat = ArrayAPI  # backwards compat
 #     _REGISTERY._ensure_datamethods_names_are_registered()


-@ub.memoize
+@cache
 def _torch_dtype_lut():
    try:
        import torch

--- a/kwarray/distributions.py
+++ b/kwarray/distributions.py
@@ -28,7 +28,6 @@ import fractions  # NOQA
 from kwarray.util_random import ensure_rng

 inf = float('inf')
-# __all__ =  [


 class Value(ub.NiceRepr):
@@ -589,7 +588,7 @@ class Distribution(Parameterized, _RBinOpMixin):
                random coercable

        CommandLine:
-            xdoctest -m /home/joncrall/code/kwarray/kwarray/distributions.py Distribution.random --show
+            xdoctest -m kwarray.distributions Distribution.random --show

        Example:
            >>> # xdoctest: +REQUIRES(module:scipy)
@@ -679,10 +678,12 @@ class Distribution(Parameterized, _RBinOpMixin):
        Example:
            >>> from kwarray.distributions import Normal  # NOQA
            >>> self = Normal()
+            >>> # xdoctest: +REQUIRES(module:kwplot)
            >>> # xdoctest: +REQUIRES(--show)
            >>> import kwplot
            >>> kwplot.autompl()
            >>> self.plot(n=1000)
+            >>> kwplot.show_if_requested()
        """
        import seaborn as sns
        if isinstance(n, str):
@@ -802,19 +803,24 @@ class Mixture(MixedDistribution):
        >>> # Given two normal distributions,
        >>> from kwarray.distributions import Normal  # NOQA
        >>> from kwarray.distributions import *  # NOQA
-        >>> n1 = Normal(mean=11, std=3)
-        >>> n2 = Normal(mean=53, std=5)
+        >>> n1 = Normal(mean=11, std=3, rng=0)
+        >>> n2 = Normal(mean=53, std=5, rng=0)
        >>> composed = (n1 * 0.3) + (n2 * 0.7)
-        >>> mixture = Mixture([n1, n2], [0.3, 0.7])
+        >>> mixture = Mixture([n1, n2], [0.3, 0.7], rng=0)
+        >>> sample_scalar = mixture.sample()
+        >>> sample_vector = mixture.sample(2)
+        >>> sample_matrix = mixture.sample(2, 3)
+        >>> assert sample_scalar.shape == tuple()
+        >>> assert sample_vector.shape == (2,)
+        >>> assert sample_matrix.shape == (2, 3)
        >>> # xdoctest: +REQUIRES(--show)
        >>> import kwplot
        >>> kwplot.autompl()
        >>> kwplot.figure(fnum=1, pnum=(2, 2, 1))
        >>> ax = kwplot.figure(pnum=(2, 1, 1), title='n1 & n2').gca()
        >>> n = 10000
-        >>> plotkw = dict(stat='density', kde=1, bins=1000)
+        >>> #plotkw = dict(stat='density', kde=1, bins=1000)
        >>> plotkw = dict(stat='count', kde=1, bins=1000)
-        >>> #plotkw = dict(stat='frequency', kde=1, bins='auto')
        >>> n1.plot(n, ax=ax, **plotkw)
        >>> n2.plot(n, ax=ax, **plotkw)
        >>> ax=kwplot.figure(pnum=(2, 2, 3), title='composed').gca()
@@ -841,7 +847,7 @@ class Mixture(MixedDistribution):
        # Choose which distributions are picked for each sample
        idxs = self._idx_choice.sample(*shape)
        idx_to_nsamples = ub.dict_hist(idxs.ravel())
-        out = np.zeros(*shape)
+        out = np.zeros(shape)
        for idx, n in idx_to_nsamples.items():
            # Sample the from the distribution we picked
            mask = (idx == idxs)
@@ -919,6 +925,7 @@ class Composed(MixedDistribution):
        >>> kwplot.autompl()
        >>> kwplot.figure(fnum=1, doclf=True)
        >>> self.plot(1000, bins=100)
+        >>> kwplot.show_if_requested()

    Example:
        >>> # Binary operations result in composed distributions
@@ -935,6 +942,7 @@ class Composed(MixedDistribution):
        >>> kwplot.autompl()
        >>> kwplot.figure(fnum=1, doclf=True)
        >>> self.plot(5000, bins=100)
+        >>> kwplot.show_if_requested()

    """
    __params__ = ub.odict([
@@ -1005,6 +1013,7 @@ class Uniform(ContinuousDistribution):
        """
        from scipy.stats import uniform
        rv = uniform(self.low, self.high)
+        rv.random_state = self.rng
        return rv

    @classmethod
@@ -1038,6 +1047,7 @@ class Exponential(ContinuousDistribution):
        >>> kwplot.autompl()
        >>> kwplot.figure(fnum=1, doclf=True)
        >>> self.plot(500, bins=25)
+        >>> kwplot.show_if_requested()

    Args:
        scale (int) : no help given. Defaults to 1.
@@ -1059,6 +1069,7 @@ class Exponential(ContinuousDistribution):
        """
        from scipy.stats import expon
        rv = expon(self.scale)
+        rv.random_state = self.rng
        return rv


@@ -1134,6 +1145,7 @@ class Normal(ContinuousDistribution):
        >>> kwplot.autompl()
        >>> kwplot.figure(fnum=1, doclf=True)
        >>> self.plot(500, bins=25)
+        >>> kwplot.show_if_requested()
    """
    __params__ = ub.odict([
        ('mean', Value(0.0)),
@@ -1143,6 +1155,7 @@ class Normal(ContinuousDistribution):
    def __scipy__(self):
        from scipy.stats import norm
        rv = norm(self.mean, self.std)
+        rv.random_state = self.rng
        return rv

    def sample(self, *shape):
@@ -1175,7 +1188,7 @@ class TruncNormal(ContinuousDistribution):
        https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.truncnorm.html

    CommandLine:
-        xdoctest -m /home/joncrall/code/kwarray/kwarray/distributions.py TruncNormal
+        xdoctest -m kwarray.distributions TruncNormal

    Example:
        >>> # xdoctest: +REQUIRES(module:scipy)
@@ -1218,6 +1231,7 @@ class TruncNormal(ContinuousDistribution):
        self.a = (self.low - self.mean) / self.std
        self.b = (self.high - self.mean) / self.std
        self.rv = truncnorm(a=self.a, b=self.b, loc=self.mean, scale=self.std)
+        self.rv.random_state = self.rng

    @classmethod
    def random(cls, rng=None):
@@ -1260,6 +1274,7 @@ class Bernoulli(DiscreteDistribution):
        """
        from scipy.stats import bernoulli
        rv = bernoulli(self.p)
+        rv.random_state = self.rng
        return rv

    @classmethod
@@ -1281,7 +1296,16 @@ class Binomial(DiscreteDistribution):
    probability of success p and a probability of failure 1 - p.

    References:
-        https://en.wikipedia.org/wiki/Binomial_distribution
+        .. [BinomDistr] https://en.wikipedia.org/wiki/Binomial_distribution
+
+    Example:
+        >>> # xdoctest: +REQUIRES(module:scipy)
+        >>> from kwarray.distributions import *  # NOQA
+        >>> self = Binomial(p=0.1, n=100, rng=0)
+        >>> self.sample()
+        10
+        >>> self.sample(10)
+        array([12, 11, 10,  9, 11,  9, 14, 16,  9, 12])

    Example:
        >>> # xdoctest: +REQUIRES(module:scipy)
@@ -1298,10 +1322,14 @@ class Binomial(DiscreteDistribution):
    def __scipy__(self):
        from scipy.stats import binom
        rv = binom(self.n, self.p)
+        # References:
+        # https://stackoverflow.com/questions/16016959/scipy-stats-seed
+        rv.random_state = self.rng
        return rv

    def sample(self, *shape):
-        return self.rng.rand(*shape) > self.p
+        rv = self.__scipy__()
+        return rv.rvs(size=shape, random_state=self.rng)


 # class Multinomial(Distribution):
@@ -1461,6 +1489,7 @@ class PDF(Distribution):
        >>> kwplot.autompl()
        >>> kwplot.figure(fnum=1, doclf=True)
        >>> self.plot(5000, bins=50)
+        >>> kwplot.show_if_requested()
    """
    def __init__(self, x, p, rng=None):
        import scipy.interpolate as interpolate

--- a/kwarray/fast_rand.py
+++ b/kwarray/fast_rand.py
@@ -171,7 +171,10 @@ def standard_normal32(size, mean=0, std=1, rng=np.random):
    # The integer and float dtype must have the same number of bits
    dtype = np.float32
    int_dtype = np.uint32
-    MAX_INT = np.core.getlimits.iinfo(int_dtype).max
+    try:
+        MAX_INT = np.iinfo(int_dtype).max
+    except AttributeError:
+        MAX_INT = np.core.getlimits.iinfo(int_dtype).max

    # Preallocate output
    out = np.empty(size, dtype=dtype)
@@ -311,7 +314,10 @@ def uniform32(low=0.0, high=1.0, size=None, rng=np.random):
            # The cuttoff size seems to be (42 * 42).
            dtype = np.float32
            int_dtype = np.uint32
-            MAX_INT = np.core.getlimits.iinfo(int_dtype).max
+            try:
+                MAX_INT = np.iinfo(int_dtype).max
+            except AttributeError:
+                MAX_INT = np.core.getlimits.iinfo(int_dtype).max
            # Generate uniform-01 random numbers that we will transform
            out = rng.randint(0, MAX_INT - 1, size=size, dtype=int_dtype).astype(dtype)
            if low == 0 and high == 1.0:

--- a/kwarray/util_torch.py
+++ b/kwarray/util_torch.py
@@ -79,6 +79,7 @@ def one_hot_embedding(labels, num_classes, dim=1):
    """
    torch = sys.modules.get('torch', None)
    if torch is not None and torch.is_tensor(labels):
+        # TODO: dtype
        in_dims = labels.ndimension()
        if dim < 0:
            dim = in_dims - dim + 1

--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,7 +16,7 @@ repo_name = "kwarray"
 rel_mod_parent_dpath = "."
 #ci_cpython_versions = ["3.6", "3.7", "3.8", "3.9", "3.10", "3.11"]
 os = [ "osx", "all", "win", "linux",]
-min_python = 3.6
+min_python = 3.8
 max_python = 3.12
 version = "{mod_dpath}/__init__.py::__version__"
 author = "Kitware Inc., Jon Crall"

--- a/requirements/runtime.txt
+++ b/requirements/runtime.txt
@@ -7,7 +7,5 @@ numpy>=1.23.2    ; python_version < '3.12' and python_version >= '3.11'    # Pyt
 numpy>=1.21.6    ; python_version < '3.11' and python_version >= '3.10'  # Python 3.10
 numpy>=1.19.3  ; python_version < '3.10' and python_version >= '3.9'   # Python 3.9
 numpy>=1.19.3  ; python_version < '3.9' and python_version >= '3.8'    # Python 3.8
-numpy>=1.19.3,<2.0  ; python_version < '3.8' and python_version >= '3.7'    # Python 3.7
-numpy>=1.19.3,<2.0  ; python_version < '3.7' and python_version >= '3.6'    # Python 3.6

 packaging>=21.3
--- a/requirements/tests.txt
+++ b/requirements/tests.txt
 pytest >= 6.2.5            ; python_version < '4.0'    and python_version >= '3.11'      # Python 3.11+
 pytest >= 6.2.5            ; python_version < '3.11'   and python_version >= '3.10'      # Python 3.10
 pytest >= 4.6.0            ; python_version < '3.10.0' and python_version >= '3.7.0'   # Python 3.7-3.9
-pytest >= 4.6.0            ; python_version < '3.7.0'  and python_version >= '3.6.0'   # Python 3.6
-pytest >= 4.6.0, <= 6.1.2  ; python_version < '3.6.0'  and python_version >= '3.5.0'   # Python 3.5
-pytest >= 4.6.0, <= 4.6.11 ; python_version < '3.5.0'  and python_version >= '3.4.0'   # Python 3.4
-pytest >= 4.6.0, <= 4.6.11 ; python_version < '2.8.0'  and python_version >= '2.7.0'   # Python 2.7

 coverage>=5.2.1       ;                            python_version >= '3.6'    # Python 3.6+
 coverage>=4.4.0       ; python_version < '3.6' and python_version >= '2.7'    # Python 2.7

--- a/setup.py
+++ b/setup.py
@@ -211,6 +211,7 @@ if __name__ == "__main__":
        "tests": parse_requirements("requirements/tests.txt", versions="loose"),
        "optional": parse_requirements("requirements/optional.txt", versions="loose"),
        "docs": parse_requirements("requirements/docs.txt", versions="loose"),
+        "linting": parse_requirements("requirements/linting.txt", versions="loose"),
        "all-strict": parse_requirements("requirements.txt", versions="strict"),
        "runtime-strict": parse_requirements(
            "requirements/runtime.txt", versions="strict"
@@ -220,6 +221,9 @@ if __name__ == "__main__":
            "requirements/optional.txt", versions="strict"
        ),
        "docs-strict": parse_requirements("requirements/docs.txt", versions="strict"),
+        "linting-strict": parse_requirements(
+            "requirements/linting.txt", versions="strict"
+        ),
    }
    setupkw["name"] = NAME
    setupkw["version"] = VERSION
@@ -231,7 +235,7 @@ if __name__ == "__main__":
    setupkw["long_description_content_type"] = "text/x-rst"
    setupkw["license"] = "Apache 2"
    setupkw["packages"] = find_packages(".")
-    setupkw["python_requires"] = ">=3.6"
+    setupkw["python_requires"] = ">=3.8"
    setupkw["classifiers"] = [
        "Development Status :: 4 - Beta",
        "Intended Audience :: Developers",
@@ -241,8 +245,6 @@ if __name__ == "__main__":
        "Intended Audience :: Science/Research",
        "Topic :: Scientific/Engineering",
        "Topic :: Software Development",
-        "Programming Language :: Python :: 3.6",
-        "Programming Language :: Python :: 3.7",
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",

--- a/tests/test_arrayapi.py
+++ b/tests/test_arrayapi.py
@@ -120,6 +120,8 @@ def test_numpy_torch_compat():
            'clip',

            'array_equal',
+            'isclose',
+            'allclose',
        }

        if arrayapi._TORCH_LT_1_7_0:
@@ -152,6 +154,7 @@ def test_numpy_torch_compat():
                    flag = True
                    if isinstance(np_result1, tuple):
                        for a, b in ub.iter_window(results, 2):
+                            # flag &= ub.IndexableWalker(a, list_cls=(np.ndarray, torch.Tensor, tuple, list)).allclose(b)
                            flag &= indexable_allclose(a, b)
                    else:
                        results = [ArrayAPI.numpy(r) for r in results]
@@ -160,3 +163,11 @@ def test_numpy_torch_compat():

                    if not flag:
                        errors.append(row)
+
+
+if __name__ == '__main__':
+    """
+    CommandLine:
+        python ~/code/kwarray/tests/test_arrayapi.py
+    """
+    test_numpy_torch_compat()
--- a/tests/test_slider.py
+++ b/tests/test_slider.py
@@ -46,7 +46,7 @@ def test_stitcher_grid():
    }
    results = []
    gauss_weights = kwimage.gaussian_patch(window_dims)
-    gauss_weights = kwimage.normalize(gauss_weights)
+    gauss_weights = kwarray.normalize(gauss_weights)
    for params in ub.named_product(basis):
        if params['weighted'] == 'none':
            weights = None
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