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Author: samaid

demos/mcpi/LICENSE

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+BSD 2-Clause License
+
+Copyright (c) 2023, Sergey Maydanov
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

demos/mcpi/README.md

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+# MCPI - Monte Carlo estimation of Pi using numpy, numba, dpnp, numba-dpex
+
+This is a "Hello, World" application in Monte Carlo methods. It stresses random number generation 
+along with some other math required for implementation of the Acceptance-Rejection technique.
+
+For details please refer to [Wikipedia](https://en.wikipedia.org/wiki/Monte_Carlo_method)
+
+## How to run
+
+`python -m mcpi_demo [options]`
+
+Demo can be invoked in several ways:
+
+1. Cloning Github repo and running `python mcpi.py [options]`
+2. Cloning Github repo and running `python -m mcpi_demo [options]`
+3. Installing conda package and invoking executable
+   * `conda install -c pycoddiy/label/dev mcpi-demo`
+   * `mcpi [options]`
+
+### Options
+
+The following options are allowed:
+* `--variant [numpy, numba, dpnp, numba-dpex]` (default `numpy`): Implementation variant
+* `--batch-size`: Number of trial points in the batch
+* `--n-batches`:  Number of batches
+
+## Jupyter Notebook
+The Monte Carlo Pi demo is also supplemented with the [Juoyter Notebook](https://github.com/samaid/mcpi/blob/main/mcpi.ipynb),
+where step by step we illustrate the idea of the algorithm.

demos/mcpi/conda-recipe/conda_build_config.yaml

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+python:
+  - 3.8
+  - 3.9
+  - 3.10
+numpy:
+  - 1.23

demos/mcpi/conda-recipe/meta.yaml

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+package:
+  name: mcpi-demo
+  version: {{ GIT_DESCRIBE_TAG }}
+
+source:
+  path: ..
+
+build:
+  entry_points:
+    - mcpi = mcpi_demo.pi:main
+  number: {{ GIT_DESCRIBE_NUMBER }}
+  script: {{ PYTHON }} -m pip install . --no-deps --ignore-installed --no-cache-dir -vvv
+
+requirements:
+  host:
+    - python
+  run:
+    - python
+    - matplotlib >=3.7.1
+    - numpy >=1.21
+    - numba >=0.55
+    - dpnp
+    - numba-dpex
+
+test:
+  requires:
+    - pytest
+  commands:
+    - mcpi --help
+    - python -m mcpi_demo --variant numba
+    - mcpi --batch-size 10 --n-batches 1
+  imports:
+    - mcpi_demo
+    - mcpi_demo.impl.impl_versioner
+    - mcpi_demo.impl.arg_parser
+
+about:
+  home: https://github.com/samaid
+  license: BSD-2-Clause
+  license_family: BSD
+  license_file:
+    - LICENSE
+  summary: Monte Carlo method to compute Pi
+
+extra:
+  recipe-maintainers:
+    - samaid

demos/mcpi/mcpi.ipynb

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+from mcpi_demo.pi import main
+
+main()

demos/mcpi/mcpi.py

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+from mcpi_demo.pi import main
+
+main()