Release 0.11.0

davehadley · Nov 5, 2022 · d34ef32 · d34ef32
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diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -2,53 +2,46 @@ name: ci
 
 on: 
   push:
-    branches: [master, dev]
+    branches: [dev]
   pull_request:
-    branches: [master, dev]
-  schedule:
-  # run once per week in case latest version of depedencies or compiler cause issues
-  - cron: '41 3 * * 0'
+    branches: [dev]
 
 jobs:
-  pre-commit:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v2
-      - name: Setup Python
-        uses: actions/setup-python@v2
-        with:
-          python-version: '3.8'
-      - name: Run pre-commit checks
-        run: |
-          curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
-          source $HOME/.poetry/env && \
-            poetry install && \
-            poetry run pre-commit install && \
-            poetry run pre-commit run --all-files
-      - name: Build docs
-        run: pip install . && pip install -r docs/requirements.txt && sphinx-build -W docs docs-build
+
   build-linux:
     runs-on: ubuntu-latest
-    needs: pre-commit
     strategy:
       matrix:
-        python-version: [ '3.6', '3.7', '3.8', '3.9' ]
+        python-version: [ '3.6', '3.7', '3.8', '3.9', '3.10', '3.11', ]
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
       - name: Setup Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v4
         with:
           python-version: '${{ matrix.python-version }}'
       - name: Setup Poetry
         run: |
-          curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
-          source $HOME/.poetry/env
+          curl -sSL https://install.python-poetry.org | python - --version 1.1.15
+      - name: Cache Poetry
+        uses: actions/cache@v3
+        env:
+          cache-name: cache-poetry
+        with:
+          path: ~/.cache/pypoetry/
+          key: ${{ runner.os }}-build-${{ env.cache-name }}-${{ matrix.python-version }}-${{ hashFiles('**/pyproject.toml') }}
       - name: Install Dependencies
-        run: source $HOME/.poetry/env && poetry install
+        run: export PATH=$HOME/.local/bin:${PATH} && poetry install
       - name: pytest
-        run: source $HOME/.poetry/env && poetry run pytest
+        run: export PATH=$HOME/.local/bin:${PATH} && poetry run pytest
       - name: Build
-        run: source $HOME/.poetry/env && poetry build
+        run: export PATH=$HOME/.local/bin:${PATH} && poetry build
       - name: Publish (dry-run)
-        run: source $HOME/.poetry/env && poetry publish --dry-run --username username --password password
+        run: export PATH=$HOME/.local/bin:${PATH} && poetry publish --dry-run --username username --password password
+      - name: Run pre-commit checks
+        run: |
+            export PATH=$HOME/.local/bin:${PATH} && \
+            poetry run pre-commit install && \
+            poetry run pre-commit run --all-files
+      - name: Build docs
+        run: pip install . && pip install -r docs/requirements.txt && sphinx-build -W docs docs-build
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -3,27 +3,29 @@ default_stages: [commit]
 repos:
 
 - repo: https://github.com/timothycrosley/isort
-  rev: 5.9.3
+  rev: 5.10.1
   hooks:
     - id: isort
       stages: [ commit ]
       args: ["--profile", "black"]
 
 - repo: https://github.com/ambv/black
-  rev: 21.10b0
+  rev: 22.3.0
   hooks:
   - id: black
     stages: [commit]
 
 
 - repo:  https://gitlab.com/pycqa/flake8
-  rev: 3.9.2
+  rev: 5.0.4
   hooks:
     - id: flake8
       stages: [commit]
 
 - repo: https://github.com/pre-commit/pre-commit-hooks
+  # don't update this beyond 4.0.1 otherwise it stops working on python3.6
   rev: v4.0.1
+
   hooks:
     - id: check-added-large-files
     - id: check-ast
@@ -37,7 +39,10 @@ repos:
   hooks:
     - id: mypy
       name: mypy
-      entry: poetry run mypy --install-types --strict --non-interactive src tests
+      # Don't mypy if the python version is 3.6 as numpy has no type-stubs
+      # Don't mypy if the python version is 3.7 as numpy types hints are missing 
+      # on some numpy methods
+      entry: bash -c "python -c \"import sys; sys.exit(sys.version_info[1]>7)\" || poetry run mypy --strict --non-interactive --install-types src tests"
       pass_filenames: false
       language: system
       types: [python]
@@ -56,6 +61,7 @@ repos:
           "-dno-else-return", # Disable no-else-return
           "-dinvalid-name", # Too many warnings, too difficult to fix
           "-dduplicate-code", # Too many false positives
+          "-dline-too-long", # Black should handle this
         ]
       exclude: |
         (?x)^(

diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,3 +1,12 @@
+# 0.11.0 (2022-11-04)
+
+  - Add `ignore_nan` option to some methods to use `numpy.nanmean`, 
+    `numpy.nanstd` and `numpy.nanpercentile` instead of `numpy.mean`, 
+    `numpy.std` and `numpy.percentile`.
+  - Add more flexibility to plotting functions to display percentiles or 
+    mean/standard deviation.
+  - Improved type hints.
+
 # 0.10.0 (2022-03-24)
 
   - Improved type hinting.

diff --git a/docs/pyplots/twodim2_example.py b/docs/pyplots/twodim2_example.py
@@ -57,8 +57,8 @@ def stddev_bootstrap_2d(nevents=100, numbins=1, numsamples=1000):
 def stddev_analytic(nevents=100, numbins=1):
     sigma = np.sqrt(nevents / numbins)
     correlation = 1.0 / numbins
-    cov = correlation * sigma ** 2
-    return np.sqrt(2.0 * sigma ** 2 + 2.0 * cov)
+    cov = correlation * sigma**2
+    return np.sqrt(2.0 * sigma**2 + 2.0 * cov)
 
 
 def example2d():

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "bootstraphistogram"
-version = "0.10.0"
+version = "0.11.0"
 description = "Poisson bootstrap histogram."
 license = "MIT"
 authors = ["David Hadley <[email protected]>"]
@@ -13,7 +13,16 @@ include = ["bootstraphistogram/py.typed"]
 
 [tool.poetry.dependencies]
 python = "^3.6.2"
-numpy = "^1.19.0"
+# The simplest numpy dependency spec fails to install with python 3.10 and 3.11
+# numpy = "^1.19.0"
+numpy = [
+    # Manually specifying the numpy-python compatibility seems to be necessary
+    # to ensure that poetry will install the latest supported numpy versions
+    # This should be simplified once python3.6 support is dropped
+    {version = ">=1.19.0,<1.20", python = "<3.7"},
+    {version = ">=1.19.0,<1.22.0", python = ">=3.7,<3.8"},
+    {version = "^1.19.0", python = ">=3.8"},
+]
 boost-histogram = ">=1.0.0"
 matplotlib = "^3.1"
 
@@ -22,8 +31,11 @@ pytest = "^6.0"
 pre-commit = "^2.15.0"
 tox = "^3.24.4"
 memory-profiler = "^0.58.0"
-pylint = "^2.12.1"
-mypy = "^0.941"
+pylint = "==2.13.9"
+mypy = [
+    # Fix for https://github.com/python/mypy/issues/13627
+    {version = "^0.982", python = ">=3.8" }
+]
 
 [tool.black]
 target_version = ['py36', 'py37', 'py38']
@@ -36,4 +48,7 @@ build-backend = "poetry.core.masonry.api"
 minversion = "6.0"
 addopts = " --doctest-modules "
 doctest_optionflags = " NORMALIZE_WHITESPACE IGNORE_EXCEPTION_DETAIL NUMBER ELLIPSIS"
-testpaths = ["tests", "src", "docs"]
+testpaths = ["tests", "src", "docs"]
+
+[tool.mypy]
+strict = true
diff --git a/src/bootstraphistogram/__init__.py b/src/bootstraphistogram/__init__.py
@@ -18,7 +18,7 @@
 from bootstraphistogram.bootstrapmoment import BootstrapMoment
 from bootstraphistogram.valuewithsamples import ValueWithSamples
 
-__version__ = "0.10.0"
+__version__ = "0.11.0"
 __license__ = "MIT"
 __author__ = "David Hadley"
 __url__ = "https://github.com/davehadley/bootstraphistogram"

diff --git a/src/bootstraphistogram/bootstrapefficiency.py b/src/bootstraphistogram/bootstrapefficiency.py
@@ -1,17 +1,18 @@
 """Implements :py:class:`BoostrapEfficiency`, a tool for calculating binned efficiencies."""
 
 from copy import copy, deepcopy
-from typing import Any, NamedTuple, Optional, Tuple, Union, cast
+from typing import TYPE_CHECKING, Any, NamedTuple, Optional, Tuple, Union, cast
 
 import boost_histogram as bh
-import numpy as np  # type: ignore
+import numpy as np
 
 from bootstraphistogram.bootstraphistogram import BootstrapHistogram
 
-try:
-    from numpy.typing import ArrayLike  # type: ignore
-except (ImportError, ModuleNotFoundError):
-    ArrayLike = np.ndarray
+if TYPE_CHECKING:
+    try:
+        from numpy.typing import ArrayLike, NDArray
+    except (ImportError, ModuleNotFoundError):
+        pass
 
 
 class BootstrapEfficiency:
@@ -51,9 +52,9 @@ class Array(NamedTuple):
         """A result type to store arrays returned by
         :py:class:`bootstraphistogram.BootstrapEfficiency`"""
 
-        numerator: np.ndarray
-        denominator: np.ndarray
-        efficiency: np.ndarray
+        numerator: "NDArray[Any]"
+        denominator: "NDArray[Any]"
+        efficiency: "NDArray[Any]"
 
     def __init__(
         self,
@@ -125,32 +126,64 @@ def samples(self) -> "BootstrapEfficiency.Histogram":
         """
         return self._hist_to_result(self._hist.samples, nanto=self._nanto)
 
-    def mean(self, flow: bool = False) -> "BootstrapEfficiency.Array":
-        """Binned mean of the bootstrap samples."""
+    def mean(
+        self, flow: bool = False, ignore_nan: bool = True
+    ) -> "BootstrapEfficiency.Array":
+        """Binned mean of the bootstrap samples.
+
+        Parameters
+        ----------
+        flow: bool
+            If True under and overflow bins are included.
+        ignore_nan : bool
+            If True :py:func:`numpy.nanmean` is used.
+
+        """
         samples = self.samples
+        mean = np.nanmean if ignore_nan else np.mean
         return BootstrapEfficiency.Array(
-            *[np.mean(hst.view(flow=flow), axis=-1) for hst in samples]
+            *[mean(hst.view(flow=flow), axis=-1) for hst in samples]
         )
 
-    def std(self, flow: bool = False) -> np.ndarray:
-        """Binned standard deviation of the boostrap samples."""
+    def std(
+        self, flow: bool = False, ignore_nan: bool = True
+    ) -> "BootstrapEfficiency.Array":
+        """Binned standard deviation of the boostrap samples.
+
+        Parameters
+        ----------
+        flow: bool
+            If True under and overflow bins are included.
+        ignore_nan : bool
+            If True :py:func:`numpy.nanstd` is used.
+
+        """
         samples = self.samples
+        std = np.nanstd if ignore_nan else np.std
         return BootstrapEfficiency.Array(
-            *[np.std(hst.view(flow=flow), axis=-1) for hst in samples]
+            *[std(hst.view(flow=flow), axis=-1) for hst in samples]
         )
 
     def percentile(
-        self, q: float, flow: bool = False, interpolation: str = "linear"
-    ) -> np.ndarray:
+        self,
+        q: float,
+        flow: bool = False,
+        interpolation: str = "linear",
+        ignore_nan: bool = True,
+    ) -> "BootstrapEfficiency.Array":
         """
         Binned q-th percentile of the bootstrap samples.
 
         Parameters
         ----------
         q : float
             The percentile, a number between 0 and 100 (inclusive).
+        flow: bool
+            If True under and overflow bins are included.
         interpolation : str
             As :py:func:`numpy.percentile`.
+        ignore_nan : bool
+            If True :py:func:`numpy.nanpercentile` is used.
 
         Returns
         -------
@@ -159,11 +192,10 @@ def percentile(
             bin in the histogram, .
         """
         samples = self.samples
+        percentile = np.nanpercentile if ignore_nan else np.percentile
         return BootstrapEfficiency.Array(
             *[
-                np.nanpercentile(
-                    hst.view(flow=flow), q, axis=-1, interpolation=interpolation
-                )
+                percentile(hst.view(flow=flow), q, axis=-1, interpolation=interpolation)  # type: ignore
                 for hst in samples
             ]
         )
@@ -184,10 +216,10 @@ def axes(self) -> Tuple[bh.axis.Axis, ...]:
 
     def fill(
         self,
-        selected: ArrayLike,
-        *args: ArrayLike,
-        weight: Optional[ArrayLike] = None,
-        seed: Optional[ArrayLike] = None,
+        selected: "ArrayLike",
+        *args: "ArrayLike",
+        weight: Optional["ArrayLike"] = None,
+        seed: Optional["ArrayLike"] = None,
         **kwargs: Any,
     ) -> "BootstrapEfficiency":
         """
@@ -196,14 +228,14 @@ def fill(
 
         Parameters
         ----------
-        selected: ArrayLike
+        selected: "ArrayLike"
             A 1D boolean array determining whether an event enters the numerator or
             denominator.
-        *args : ArrayLike
+        *args : "ArrayLike"
             An 1D array containing coordinates for each dimension of the histogram.
-        weight : Optional[ArrayLike]
+        weight : Optional["ArrayLike"]
             Entry weights used to fill the histogram.
-        seed: Optional[ArrayLike]
+        seed: Optional["ArrayLike"]
             Per-element seed. Overrides the Generator given in the constructor and
             uses a pseudo-random number generator seeded by the given value.
             This may be useful when filling multiple histograms with data that is not
@@ -218,16 +250,16 @@ def fill(
             Reference to this object. This is done to maintain consistency with
             `boost_histogram.Histogram`.
         """
-        args = tuple(np.asarray(a) for a in args)
-        selected = np.asarray(selected).astype(bool)
-        self._validate_fill_inputs(args, selected)
-        self._hist.fill(selected, *args, weight=weight, seed=seed, **kwargs)
+        arrays = tuple(np.asarray(a) for a in args)
+        selectedarray = np.asarray(selected).astype(bool)
+        self._validate_fill_inputs(arrays, selectedarray)
+        self._hist.fill(selectedarray, *arrays, weight=weight, seed=seed, **kwargs)
         return self
 
     @staticmethod
     def _validate_fill_inputs(
-        args: ArrayLike,
-        selected: ArrayLike,
+        args: "Tuple[NDArray[Any], ...]",
+        selected: "NDArray[Any]",
     ) -> None:
         if len(args) <= 0:
             raise ValueError("fill must be provided at least 1 array as input.")