semvec/pypi-packages huggingface dataset:
pydistance 0.0.2
Package for plotting the closest point for a given set of coordinates
License: MIT
Requires Python: >=3.4.0


# Pydistance

> A library for visualizing the closest point to a set of points.

![Example Image](https://github.com/dang3r/pydistance/blob/master/example.png?raw=true)

## Getting started

Install the Python3 package

```shell
pip3 install pydistance
```

## Usage

```
$ pyd --help
Usage: pyd [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  distance  Dumb command to test the distance_matrix api
  enrich    Enrich the locations with lat, lng information
  plot      Plot all employee addresses and the best determined office...
```

To use, create a text file and run the plot command.

```bash
cat <<EOF
Toronto, Ontario, Canada
Palo Alto, California, USA
Mt. Everest, Nepal
Berlin, Germany
EOF > addrs.txt
pyd plot --adrs-file=addrs.txt
```


## License

MIT
isover10 0.1.4
Check whether two lines A (x1,x2) and B (x3,x4) on the x-axis whether they overlap or not
License: MIT
Keywords: Overlap,A over B


check whether two lines (x1,x2) and (x3,x4) on the x-axis do overlap or not 

It returns True if they DO overlap, otherwise False

As an example, (1,5) and (2,6) overlaps but not (1,5) and (6,8).

The solution was based on the following schema:

                 A0------------------A1
      B0------B1                          B0------B1

          if B1<A0 OR B0>A1 then
             Line B does NOT overlap Line A
          else
             Line B DOES ovelap Line A


Therefore, we need to make sure the A and B are ordered:

    def swap(X):
        '''
        this function does make sure the pair is 
        ordered (a,b) where a<b
        (10, -5) would become (-5, 10)
        '''
        if X[0]>X[1]:
            return (X[1],X[0])
        return X

    A, B = swap(A), swap(B)

 Proposed solution:

 def isbovera(A,B):

    # Return True if A Line overlaps B Line; False otherwise

    A, B = swap(A), swap(B)

    return not (B[1]<A[0] or B[0]>A[1])

In order to call this function, please take a look at the testOverlapV0.py

(venv) C:\work\vanhack\venv\Quiz\test_A>python testOverlapV0.py

This program that accepts two lines (x1,x2) and (x3,x4) on the x-axis and returns 
whether they overlap (True) or not overlap (False)

Enter total number of lines to check, default=1 pair to check

please add  1 lines to be checked - use comma

(1,2),(3,4) should be typed as 1,2,3,4

1,5,2,6

(1.0, 5.0) (2.0, 6.0) True

True means (1,2) and (5,6) do overlap

Let's check the following pair (1,5) and (6,8)

(1,5) and (6,8) should be entered as below:

1,5,6,8


(1.0, 5.0) (6.0, 8.0) False

False means (1,2) and (6,8) do NOT overlap

Note:
 We are using float although has no mention about it - set/intersection could also handle it but only for int figures

 in order to run it as a batch module, a text file should be created with n pairs (comma separeted) as follow:

 first line, number of pair to check
 second line next pair to check
 and so on

ex:

4

13 , -6 , -8 , 3

-15 , -6 , 4 , -11

-4 , -2 , 0 , -20

-18 , 9 , 10 , 12

** please check testsample.txt ** 

python testOverlapV0.py <testsample.txt

This program that accepts two lines (x1,x2) and (x3,x4) on the x-axis and returns whether they overlap
Enter total number of lines to check, default=1 pair to check
please add  100 lines to be checked - use comma
(1,2),(3,4) should be typed as 1,2,3,4

(13.0, -6.0) (-8.0, 3.0) True

(-15.0, -6.0) (4.0, -11.0) True

(-4.0, -2.0) (0.0, -20.0) True

(-18.0, 9.0) (10.0, 12.0) False
django-transtool 0.0.19
Make translating your django project easier.
License: MIT
Keywords: django,django-transtool,translation,localization,internationalization,i18n,l10n

django-transtool
===========

Make translating your django project easier.

|

Installation
------------

**Requirements:**

* django v1.8+
* django-rosetta

**\1\. Install** ``django-transtool``.

* Via pip::

  $ pip install django-transtool

* Via setuptools::

  $ easy_install django-transtool


 For install development version use ``git+https://github.com/liminspace/django-transtool.git@develop`` instead ``django-transtool``.

**\2\. Set up** ``settings.py`` **in your django project.** ::

  INSTALLED_APPS = (
    ...,
    'transtool',
  )
sparsereg 0.10.0
Modern sparse linear regression
License: MIT
Requires Python: >=3.6

sparsereg
=========

|travis| |pypi| |codecov| |zenodo|

**sparsereg** is a collection of modern sparse (regularized) regression
algorithms.

Installation
------------

``pip install sparsereg``

Citation
--------

If you use sparsereg please consider a citation:

::

    @misc{markus_quade_sparsereg,
      author       = {Markus Quade},
      title        = {sparsereg - collection of modern sparse regression algorithms},
      month        = feb,
      year         = 2018,
      doi          = {10.5281/zenodo.1173754},
      url          = {https://github.com/ohjeah/sparsereg}
    }

Implemented algorithms
----------------------

-  Mcconaghy, T. (2011). FFX: Fast, Scalable, Deterministic Symbolic
   Regression Technology. Genetic Programming Theory and Practice IX,
   235-260. `DOI:
   10.1007/978-1-4614-1770-5_13 <http://dx.doi.org/10.1007/978-1-4614-1770-5_13>`__
-  Brunton, Steven L., Joshua L. Proctor, and J. Nathan Kutz.
   “Discovering governing equations from data by sparse identification
   of nonlinear dynamical systems.” Proceedings of the National Academy
   of Sciences 113.15 (2016): 3932-3937. `DOI:
   10.1073/pnas.1517384113 <http://dx.doi.org/10.1073/pnas.1517384113>`__
-  Bouchard, Kristofer E. “Bootstrapped Adaptive Threshold Selection for
   Statistical Model Selection and Estimation.” arXiv preprint
   arXiv:1505.03511 (2015).
-  Ignacio Arnaldo, Una-May O’Reilly, and Kalyan Veeramachaneni.
   “Building Predictive Models via Feature Synthesis.” In Proceedings of
   the 2015 Annual Conference on Genetic and Evolutionary Computation
   (GECCO ’15), Sara Silva (Ed.). ACM, New York, NY, USA, 983-990. `DOI:
   10.1145/2739480.2754693 <http://dx.doi.org/10.1145/2739480.2754693>`__

.. |travis| image:: https://travis-ci.org/Ohjeah/sparsereg.svg?branch=master
   :target: https://travis-ci.org/Ohjeah/sparsereg
.. |pypi| image:: https://badge.fury.io/py/sparsereg.svg
   :target: https://badge.fury.io/py/sparsereg
.. |codecov| image:: https://codecov.io/gh/Ohjeah/sparsereg/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/Ohjeah/sparsereg
.. |zenodo| image:: https://zenodo.org/badge/80389199.svg
   :target: https://zenodo.org/badge/latestdoi/80389199