refactor!: match API with Scikit-HEP (#22)

* refactor!: match API with Scikit-HEP

* refactor!: match API with Scikit-HEP

* tests + __getitem__

* docs

* Update README.md

* Update README.md

Author: Saransh-cpp

.pre-commit-config.yaml

@@ -7,6 +7,7 @@ repos:
     rev: "1.18.0"
     hooks:
       - id: blacken-docs
+        args: ["-E"]
         additional_dependencies: [black==24.*]
 
   - repo: https://github.com/pre-commit/pre-commit-hooks

README.md

@@ -13,12 +13,203 @@
 [![Conda latest release][conda-version]][conda-link]
 [![LICENSE][license-badge]][license-link] [![Scikit-HEP][sk-badge]][sk-link]
 
-`cuda-histogram` is a histogram filling package for GPUs. The package follows
-[UHI](https://uhi.readthedocs.io) and keeps its API similar to
+`cuda-histogram` is a histogram filling package for GPUs. The package tries to
+follow [UHI](https://uhi.readthedocs.io) and keeps its API similar to
 [boost-histogram](https://github.com/scikit-hep/boost-histogram) and
 [hist](https://github.com/scikit-hep/hist).
 
-The package is under active development at the moment.
+Main features of cuda-histogram:
+
+- Implements a subset of the features of boost-histogram using CuPy (see API
+  documentation for a complete list):
+  - Axes
+    - `Regular` and `Variable` axes
+      - `edges()`
+      - `centers()`
+      - `index(...)`
+      - ...
+  - Histogram
+    - `fill(..., weight=...)` (including `Nan` flow)
+    - simple indexing with slicing (see example below)
+    - `values(flow=...)`
+    - `variance(flow=...)`
+- Allows users to detach the generated GPU histogram to CPU -
+  - `to_boost()` - converts to `boost-histogram.Histogram`
+  - `to_hist()` - converts to `hist.Hist`
+
+Near future goals for the package -
+
+- Implement support for `Categorical` axes (exists internally but need
+  refactoring to match boost-histogram's API)
+- Improve indexing (`__getitem__`) to exactly match boost-histogram's API
+
+## Installation
+
+cuda-histogram is available on [PyPI](https://pypi.org/project/cuda-histogram/)
+as well as on [conda](https://anaconda.org/conda-forge/cuda-histogram). The
+library can be installed using `pip` -
+
+```
+pip install cuda-histogram
+```
+
+or using `conda` -
+
+```
+conda install -c conda-forge cuda-histogram
+```
+
+## Usage
+
+Ideally, a user would want to create a cuda-histogram, fill values on GPU, and
+convert the filled histogram to boost-histogram/Hist object to access all the
+UHI functionalities.
+
+### Creating a histogram
+
+```py
+import cuda_histogram; import cupy as cp
+
+ax1 = cuda_histogram.axis.Regular(10, 0, 1)
+ax2 = cuda_histogram.axis.Variable([0, 2, 3, 6])
+
+h = cuda_histogram.Hist(ax1, ax2)
+
+>>> ax1, ax2, h
+(Regular(10, 0, 1), Variable([0. 2. 3. 6.]), Hist(Regular(10, 0, 1), Variable([0. 2. 3. 6.])))
+```
+
+### Filling a histogram
+
+Differences in API (from boost-histogram) -
+
+- Has an additional `NaN` flow
+- Accepts only CuPy arrays
+
+```py
+h.fill(cp.random.normal(size=1_000_000), cp.random.normal(size=1_000_000))  # set weight=... for weighted fills
+
+>>> h.values(), type(h.values())  # set flow=True for flow bins (underflow, overflow, nanflow)
+(array([[28532.,  1238.,    64.],
+       [29603.,  1399.,    61.],
+       [30543.,  1341.,    78.],
+       [31478.,  1420.,    98.],
+       [32692.,  1477.,    92.],
+       [32874.,  1441.,    96.],
+       [33584.,  1515.,    88.],
+       [34304.,  1490.,   114.],
+       [34887.,  1598.,   116.],
+       [35341.,  1472.,   103.]]), <class 'cupy.ndarray'>)
+```
+
+### Indexing axes and histograms
+
+Differences in API (from boost-histogram) -
+
+- `underflow` is indexed as `0` and not `-1`
+- `ax[...]` will return a `cuda_histogram.Interval` object
+- No interpolation is performed
+- `Hist` indices should be in the range of bin edges, instead of integers
+
+```py
+>>> ax1.index(0.5)
+array([6])
+
+>>> ax1.index(-1)
+array([0])
+
+>>> ax1[0]
+<Interval ((-inf, 0.0)) instance at 0x1c905208790>
+
+>>> h[0, 0], type(h[0, 0])
+(Hist(Regular(1, 0.0, 0.1), Variable([0. 2.])), <class 'cuda_histogram.hist.Hist'>)
+
+>>> h[0, 0].values(), type(h[0, 0].values())
+(array([[28532.]]), <class 'cupy.ndarray'>)
+
+>>> h[0, :].values(), type(h[0, 0].values())
+(array([[28532.,  1238.,    64.]]), <class 'cupy.ndarray'>)
+
+>>> h[0.2, :].values(), type(h[0, 0].values()) # indices in range of bin edges
+(array([[30543.,  1341.,    78.]]), <class 'cupy.ndarray'>)
+
+>>> h[:, 1:2].values(), type(h[0, 0].values()) # no interpolation
+C:\Users\Saransh\Saransh_softwares\OpenSource\Python\cuda-histogram\src\cuda_histogram\axis\__init__.py:580: RuntimeWarning: Reducing along axis Variable([0. 2. 3. 6.]): requested start 1 between bin boundaries, no interpolation is performed
+  warnings.warn(
+(array([[28532.],
+       [29603.],
+       [30543.],
+       [31478.],
+       [32692.],
+       [32874.],
+       [33584.],
+       [34304.],
+       [34887.],
+       [35341.]]), <class 'cupy.ndarray'>)
+```
+
+### Converting to CPU
+
+All the existing functionalities of boost-histogram and Hist can be used on the
+converted histogram.
+
+```py
+h.to_boost()
+
+>>> h.to_boost().values(), type(h.to_boost().values())
+(array([[28532.,  1238.,    64.],
+       [29603.,  1399.,    61.],
+       [30543.,  1341.,    78.],
+       [31478.,  1420.,    98.],
+       [32692.,  1477.,    92.],
+       [32874.,  1441.,    96.],
+       [33584.,  1515.,    88.],
+       [34304.,  1490.,   114.],
+       [34887.,  1598.,   116.],
+       [35341.,  1472.,   103.]]), <class 'numpy.ndarray'>)
+
+h.to_hist()
+
+>>> h.to_hist().values(), type(h.to_hist().values())
+(array([[28532.,  1238.,    64.],
+       [29603.,  1399.,    61.],
+       [30543.,  1341.,    78.],
+       [31478.,  1420.,    98.],
+       [32692.,  1477.,    92.],
+       [32874.,  1441.,    96.],
+       [33584.,  1515.,    88.],
+       [34304.,  1490.,   114.],
+       [34887.,  1598.,   116.],
+       [35341.,  1472.,   103.]]), <class 'numpy.ndarray'>)
+```
+
+## Getting help
+
+- `cuda-histogram`'s code is hosted on
+  [GitHub](https://github.com/Saransh-cpp/cuda-histogram).
+- If something is not working the way it should, or if you want to request a new
+  feature, create a new
+  [issue](https://github.com/Saransh-cpp/cuda-histogram/issues) on GitHub.
+- To discuss something related to `cuda-histogram`, use the
+  [discussions](https://github.com/Saransh-cpp/cuda-histogram/discussions/) tab
+  on GitHub.
+
+## Contributing
+
+Contributions of any kind welcome! See
+[CONTRIBUTING.md](./.github/CONTRIBUTING.md) for information on setting up a
+development environment.
+
+## Acknowledgements
+
+This library was primarily developed by Lindsey Gray, Saransh Chopra, and Jim
+Pivarski.
+
+Support for this work was provided by the National Science Foundation
+cooperative agreement OAC-1836650 and PHY-2323298 (IRIS-HEP). Any opinions,
+findings, conclusions or recommendations expressed in this material are those of
+the authors and do not necessarily reflect the views of the National Science
+Foundation.
 
 <!-- prettier-ignore-start -->
 [actions-badge]:            https://github.com/Saransh-cpp/cuda-histogram/workflows/CI/badge.svg

docs/api/cuda_histogram.axis.rst

@@ -5,3 +5,4 @@ cuda_histogram.axis package
    :members:
    :undoc-members:
    :show-inheritance:
+   :private-members:

docs/index.md

@@ -10,26 +10,6 @@
 :start-after: <!-- SPHINX-START -->
 ```
 
-## Installation
-
-cuda-histogram is available on [PyPI](https://pypi.org/project/cuda-histogram/)
-as well as on [conda](https://anaconda.org/conda-forge/cuda-histogram). The
-library can be installed using `pip` -
-
-```{code-block}
-
-pip install cuda-histogram
-
-```
-
-or using `conda` -
-
-```{code-block}
-
-conda install -c conda-forge cuda-histogram
-
-```
-
 ## Changes in cuda-histogram's API
 
 The `changelog` file describes the changes in `cuda-histogram`'s API and usage
@@ -41,17 +21,6 @@ introduced in every new version.
 changelog
 ```
 
-## Getting help
-
-- `cuda-histogram`'s code is hosted on
-  [GitHub](https://github.com/Saransh-cpp/cuda-histogram).
-- If something is not working the way it should, or if you want to request a new
-  feature, create a new
-  [issue](https://github.com/Saransh-cpp/cuda-histogram/issues) on GitHub.
-- To discuss something related to `cuda-histogram`, use the
-  [discussions](https://github.com/Saransh-cpp/cuda-histogram/discussions/) tab
-  on GitHub.
-
 ## API reference
 
 ```{toctree}

pyproject.toml

@@ -9,21 +9,23 @@ maintainers = [
   { name = "The Scikit-HEP admins", email = "[email protected]" },
 ]
 authors = [
-  { name = "Lindsey Gray, Saransh Chopra", email = "[email protected]" },
+  { name = "Lindsey Gray", email = "[email protected]" },
+  { name = "Saransh Chopra", email = "[email protected]" },
 ]
 description = "Histogramming tools on CUDA."
 readme = "README.md"
 license.file = "LICENSE"
 requires-python = ">=3.8"
 classifiers = [
-  "Development Status :: 1 - Planning",
+  "Development Status :: 4 - Beta",
   "Intended Audience :: Science/Research",
   "Intended Audience :: Developers",
   "License :: OSI Approved :: BSD License",
   "Operating System :: OS Independent",
   "Programming Language :: Python",
   "Programming Language :: Python :: 3",
   "Programming Language :: Python :: 3 :: Only",
+  "Programming Language :: Python :: 3.8",
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",