semvec/pypi-packages huggingface dataset:
rdmulti 1.0.1
Analysis of RD Designs with multiple cutoffs or scores
Requires Python: >=3.6

# rdmulti: analysis of RD Designs with multiple cutoffs or scores

## Description

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The `rdmulti` package provides tools to analyze RD designs with multiple cutoffs or scores:

- `rdmc()` estimates pooled and cutoff-specific effects in multi-cutoff designs.
- `rdmcplot()` draws RD plots for multi-cutoff RD designs.
- `rdms()` estimates effects in cumulative cutoffs or multi-score designs.

For more details, visit [https://rdpackages.github.io/rdmulti](https://rdpackages.github.io/rdmulti).

## References

1. Calonico, S., M.D. Cattaneo, M. Farrell, and R. Titiunik. (2017). [`rdrobust`: Software for Regression Discontinuity Designs](https://rdpackages.github.io/references/Calonico-Cattaneo-Farrell-Titiunik_2017_Stata.pdf). *Stata Journal* 17(2): 372-404.
2. Calonico, S., M.D. Cattaneo, and R. Titiunik. (2014). [Robust Data-Driven Inference in the Regression-Discontinuity Design](https://rdpackages.github.io/references/Calonico-Cattaneo-Titiunik_2014_Stata.pdf). *Stata Journal* 14(4): 909-946.
3. Calonico, S., M.D. Cattaneo, and R. Titiunik. (2015). [`rdrobust`: An R Package for Robust Nonparametric Inference in Regression-Discontinuity Designs](https://rdpackages.github.io/references/Calonico-Cattaneo-Titiunik_2015_R.pdf). *R Journal* 7(1): 38-51.
4. Cattaneo, M.D., L. Keele, R. Titiunik, and G. Vazquez-Bare. (2016). [Interpreting Regression Discontinuity Designs with Multiple Cutoffs](https://rdpackages.github.io/references/Cattaneo-Keele-Titiunik-VazquezBare_2016_JOP.pdf). *Journal of Politics* 78(4): 1229-1248.
5. Cattaneo, M.D., L. Keele, R. Titiunik, and G. Vazquez-Bare. (2020). [Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs](https://rdpackages.github.io/references/Cattaneo-Keele-Titiunik-VazquezBare_2021_JASA.pdf). *Journal of the American Statistical Association* 116(536): 1941, 1952.
6. Cattaneo, M.D., R. Titiunik, and G. Vazquez-Bare. (2020). [Analysis of Regression Discontinuity Designs with Multiple Cutoffs or Multiple Scores](https://rdpackages.github.io/references/Cattaneo-Titiunik-VazquezBare_2020_Stata.pdf). *Stata Journal* 20(4): 866-891.
7. Keele, L., and R. Titiunik. (2015). [Geographic Boundaries as Regression Discontinuities](https://rdpackages.github.io/references/Keele-Titiunik_2015_PA.pdf). *Political Analysis* 23(1): 127-155

## Authors

- Matias Cattaneo, Princeton University. Email: cattaneo@princeton.edu
- Rocio Titiunik, Princeton University. Email: titiunik@princeton.edu
- Ricardo Masini, UC Davis. Email: rmasini@ucdavis.edu
- Gonzalo Vazquez-Bare, UC Santa Barbara. Email: gvazquez@econ.ucsb.edu
anchorpoint 0.8.2
Text substring selectors for anchoring annotations
Requires Python: >=3.8

Anchorpoint
===========

A Python library for anchoring annotations with text substring selectors.

.. image:: https://img.shields.io/badge/open-ethical-%234baaaa
    :target: https://ethicalsource.dev/licenses/
    :alt: An Ethical Open Source Project

.. image:: https://coveralls.io/repos/github/mscarey/anchorpoint/badge.svg?branch=master
    :target: https://coveralls.io/github/mscarey/anchorpoint?branch=master
    :alt: Test Coverage Percentage

.. image:: https://github.com/mscarey/anchorpoint/actions/workflows/python-package.yml/badge.svg
    :target: https://github.com/mscarey/anchorpoint/actions
    :alt: GitHub Actions Workflow

.. image:: https://readthedocs.org/projects/anchorpoint/badge/?version=latest
    :target: https://anchorpoint.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status

Anchorpoint supplies TextQuoteSelector and TextPositionSelector
classes based on the Web Annotation Data Model, which is
a `W3C Recommendation`_. Anchorpoint includes helper methods
for switching between selector types, and
a `pydantic`_ schema for serialization. Anchorpoint is used
by `Legislice`_ for referencing laws such as statutes, and
by `AuthoritySpoke`_ for referencing judicial opinions.

`API Documentation`_ is available on readthedocs.

Anchorpoint relies on `python-ranges`_ to perform set operations on spans of text.

Related Packages
~~~~~~~~~~~~~~~~

In Javascript, try the `Text Quote Anchor`_ and `Text Position Anchor`_ packages.

In Python try python-ranges_, which is the basis for much of the TextPositionSelector class's behavior.

.. _W3C Recommendation: https://www.w3.org/TR/annotation-model/
.. _pydantic: https://docs.pydantic.dev/latest/
.. _Legislice: https://github.com/mscarey/legislice
.. _AuthoritySpoke: https://authorityspoke.readthedocs.io
.. _API Documentation: https://anchorpoint.readthedocs.io/en/latest/
.. _python-ranges: https://github.com/Superbird11/ranges
.. _Text Quote Anchor: https://www.npmjs.com/package/dom-anchor-text-quote
.. _Text Position Anchor: https://www.npmjs.com/package/dom-anchor-text-position
Spectralanalysis 0.1.6
A package for spectral analysis
Requires Python: >=3.6

﻿# team22_2023

![Tests](https://code.harvard.edu/CS107/team22_2023/main/.github/workflows/test.yml/badge.svg)
![Code Coverage](https://code.harvard.edu/CS107/team22_2023/main/.github/workflows/code-coverage.yml/badge.svg)
cs107-team31-2023 0.0.1
An API for interfacing with the Sloan Digital Sky Survey
Requires Python: >=3.7

# Astronomy Research Library

The Astronomy Research Library is a Python library designed to facilitate astronomical research, particularly focusing on the classification of stars, galaxies, and quasars (QSOs). It interfaces with Sloan Digital Sky Survey (SDSS) services to access spectral data and related information.

## Modules Overview

### Core Functionalities
This module provides tools to query the SDSS database and APIs using ADQL (Astronomical Data Query Language).

- **Classes & Functions**:
  - `CoreFunctionalities`: Constructs ADQL query strings and Handles HTTP requests and responses to/from SDSS services.
  - `MetaDataExtractor`: Extracts metadata from queried objects
  - 'DataPreprocessor': Responsible for preparing raw spectral data for analysis, including normalization, outlier removal, and interpolation, and RedshiftCorrection
  - 'Wavelength Aligner' - handles spectral alignment to a common wavelength range
  - `get_ml_data`: Extracts wavelength and flux data from SDSS for use in later modules



### Visualization
Offers visualization tools for spectral data using Matplotlib, with capabilities for overlaying inferred continua.

- **Classes & Functions**:
  - `Vizualization`: Provides functionalities to plot and overlay spectral features.

### Data Augmentation
Enhances the dataset by calculating derivatives and fractional derivatives of spectral data.

- **Classes & Functions**:
  - `data_augmentation`: Computes and appends derivatives to each spectral data point.

### Machine Learning
Implements a machine learning model for classifying astronomical objects.

- **Classes & Functions**:
  - `knn_clasifier`: A model that distinguishes between stars, galaxies, and QSOs.

### Cross Matching
Enables cross matching between SDSS and Gaia.

- **Classes & Functions**:
  - `extract_gaia_cross_match`: Facilitates the selection and analysis of pure matches between SDSS and Gaia.

### Spectral Feature Extraction
Extracts spectral features defining emission and absorption lines as those with flux
levels exceeding 2 sigma from the continuum

### Interactive Visualization
- **Classes & Functions**:
  - `viz_tool_interactive`: interactive visualization tool


# Workflow Status

[![Python application test with coverage](https://code.harvard.edu/CS107/team31_2023/actions/workflows/code_coverage.yml/badge.svg?branch=dev)](https://code.harvard.edu/CS107/team31_2023/actions/workflows/code_coverage.yml)
[![Run Tests](https://code.harvard.edu/CS107/team31_2023/actions/workflows/tests.yml/badge.svg?branch=dev)](https://code.harvard.edu/CS107/team31_2023/actions/workflows/tests.yml)
vmjuggler 0.1.1
vmjuggler provides the simple high level API to VMWare’s SDK.
Keywords: vmware pyvmomi vm vcenter API devops sdk

What is vmjuggler
-----------------

**vmjuggler** provides the simple high level API to VMWare’s SDK.

It built around pyvmomi_ library with aim to simplify interaction to VMWare VCenter and it's managed objects
for DevOps crowd and those who don't want to plunge deeply to object's relations. At the same time ability
to perform actions on low level was preserved.

Installation
------------

``pip install vmjuggler``

Manual installation
-------------------
- Install following python package

    - pyvmomi_

- Download latest **vmjuuggler** from https://github.com/shurkam/vmjuggler
- Unpack and run ``python setup.py install``

Getting started
---------------

.. code-block:: python

    from vmjuggler import VCenter

    # Create instance of VCenter and connect to VCenter
    vc = VCenter('10.0.0.1', 'user', 'super_secret_password')
    vc.return_single(True)
    vc.connect()

    # Find VM and print out it's power state
    vm = vc.get_vm(name='My_Linux_VM')
    if vm:
        print(f'{vm.name} | {vm.state}')

    # Close connection to VCenter
    vc.disconnect()

Please check documentation_ for more examples.

.. _pyvmomi: https://github.com/vmware/pyvmomi
.. _documentation: https://vmjuggler.readthedocs.io/en/latest/
pgf-formatter 0.2.0
Embedding PDF images in Jupyter notebooks
Requires Python: >=3.8

# pgf-formatter

[![PyPI - Version](https://img.shields.io/pypi/v/pgf-formatter.svg)](https://pypi.org/project/pgf-formatter)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pgf-formatter.svg)](https://pypi.org/project/pgf-formatter)

-----

**Table of Contents**

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install pgf-formatter
```

## License

`pgf-formatter` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.