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توضیحات

Tools for simulation-based model checking and diagnostics.

ویژگی	مقدار
سیستم عامل	-
نام فایل	checkrs-0.2.0
نام	checkrs
نسخه کتابخانه	0.2.0
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Timothy Brathwaite
ایمیل نویسنده	timothyb0912@gmail.com
آدرس صفحه اصلی	https://github.com/timothyb0912/checkrs
آدرس اینترنتی	https://pypi.org/project/checkrs/
مجوز	-

# checkrs ![Tests](https://github.com/timothyb0912/checkrs/workflows/Tests/badge.svg) Tools for simulation-based model checking. ## Description The checkrs package contains functions for creating 7 model checking/diagnostic plots described in > Brathwaite, Timothy. "Check yourself before you wreck yourself: Assessing discrete choice models through predictive simulations" arXiv preprint arXiv:1806.02307 (2018). https://arxiv.org/abs/1806.02307. Beyond the plots described in this paper, checkrs enables the creation of reliability and marginal model plots that use continuous scatterplot smooths based on [Extremely Randomized Trees](https://scikit-learn.org/stable/modules/generated/sklearn.tree.ExtraTreeClassifier.html#sklearn.tree.ExtraTreeClassifier) as kernel estimators, as opposed to only allowing discrete smooths based on binning. As for the name, checkrs is a play on the word "checkers," i.e., those tools one uses to check, or one who checks. The name is also a play on the phrases "check the research of scientists" and "check research scientists." ## Installation `pip install checkrs` ## Usage Note that `example_project` is fictitious! This example is, literally, just an example. ``` from checkrs import ChartData, ViewSimCDF from example_project import load_data design, targets_observed, targets_simulated = load_data() chart_data = ChartData.from_raw( targets=targets_observed, # 1D Ndarray or Tensor targets_simulated=targets_simulated, # 2D Ndarray or Tensor design=design # DataFrame or None ) chart = ViewSimCDF.from_chart_data(chart_data) chart_plotnine = chart.draw(backend="plotnine") chart_altair = chart.draw(backend="altair") #### ## Save to a variety of formats #### # chart.save("temp_plot.png") # chart.save("temp_plot.pdf") # chart.save("temp_plot.json") # chart.save("temp_plot.html") ``` See docstrings for `ChartData.from_raw`, `ViewSimCDF.from_chart_data`, and `ViewSimCDF.save`. ## To-Do: - Add package to conda and conda-forge ## Development installation To work on and edit checkrs, the following setup process may be useful. 1. from the project root, create an environment `checkrs` with the help of [conda](https://docs.conda.io/en/latest/), ``` cd checkrs conda env create -n checkrs -f environment.yml ``` 2. activate the new environment with ``` conda activate checkrs ``` 3. install `checkrs` in an editable fashion using: ``` flit install --pth-file ``` Optional and needed only once after `git clone`: 4. install several [pre-commit] git hooks with: ``` pre-commit install ``` and checkout the configuration under `.pre-commit-config.yaml`. The `-n, --no-verify` flag of `git commit` can be used to deactivate pre-commit hooks temporarily. Then take a look into the `scripts` and `notebooks` folders. ## Dependency Management & Reproducibility 1. Always keep your abstract (unpinned) dependencies updated in `environment.yml`, `requirements.in`, and eventually in `pyproject.toml` if you want to ship and install the package via `pip` later on. - Use `environment.yml` for dependencies that cannot be installed via `pip`. - Use `requirements.in` for dependencies that can be installed via `pip`. - Use `pyproject.toml` for dependencies that are needed for `checkrs` to function at all, not just in development. 2. Create concrete dependencies as `requirements.txt` for the exact reproduction of your environment with: ``` pip-compile requirements.in ``` 3. Manually update any non-pip dependencies in `environment.yml`, being sure to pin any such dependencies to a specific version. 4. Update your current environment using: ``` conda env update -f environment.yml ``` Or ``` pip install -r requirements.txt ``` if you did not update any non-pip dependencies. ## Project Organization ``` ├── AUTHORS.rst <- List of developers and maintainers. ├── CHANGELOG.rst <- Changelog to keep track of new features and fixes. ├── LICENSE.txt <- License as chosen on the command-line. ├── README.md <- The top-level README for developers. ├── configs <- Directory for configurations of model & application. ├── data │ ├── external <- Data from third party sources. │ ├── interim <- Intermediate data that has been transformed. │ ├── processed <- The final, canonical data sets for modeling. │ └── raw <- The original, immutable data dump. ├── docs <- Directory for Sphinx documentation in rst or md. ├── environment.yaml <- The conda environment file for reproducibility. ├── models <- Trained and serialized models, model predictions, │ or model summaries. ├── notebooks <- Jupyter notebooks. Naming convention is a number (for │ ordering), the creator's initials and a description, │ e.g. `1.0-fw-initial-data-exploration`. ├── references <- Data dictionaries, manuals, and all other materials. ├── reports <- Generated analysis as HTML, PDF, LaTeX, etc. │ └── figures <- Generated plots and figures for reports. ├── scripts <- Analysis and production scripts which import the │ actual PYTHON_PKG, e.g. train_model. ├── setup.cfg <- Declarative configuration of your project. ├── setup.py <- Use `python setup.py develop` to install for development or | or create a distribution with `python setup.py bdist_wheel`. ├── src │ └── checkrs <- Actual Python package where the main functionality goes. ├── tests <- Unit tests which can be run with `py.test`. ├── .coveragerc <- Configuration for coverage reports of unit tests. ├── .isort.cfg <- Configuration for git hook that sorts imports. └── .pre-commit-config.yaml <- Configuration of pre-commit git hooks. ``` ## Note This project has been set up using PyScaffold 3.3a1 and the [dsproject extension] 0.4. For details and usage information on PyScaffold see https://pyscaffold.org/. [conda]: https://docs.conda.io/ [pre-commit]: https://pre-commit.com/ [Jupyter]: https://jupyter.org/ [nbstripout]: https://github.com/kynan/nbstripout [Google style]: http://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings [dsproject extension]: https://github.com/pyscaffold/pyscaffoldext-dsproject

نیازمندی

مقدار	نام
-	altair
-	altair-viewer
-	attrs
-	future
-	matplotlib
-	numpy
-	pandas
-	plotnine
-	scipy
-	seaborn
-	scikit-learn
-	scipy
-	seaborn
-	statsmodels
-	torch
-	typing_extensions
-	tqdm

زبان مورد نیاز

مقدار	نام
>=3.3	Python

نحوه نصب

نصب پکیج whl checkrs-0.2.0:

pip install checkrs-0.2.0.whl

نصب پکیج tar.gz checkrs-0.2.0:

pip install checkrs-0.2.0.tar.gz