semvec/pypi-packages huggingface dataset:
slicer-package-manager-client 0.9.0
Python client for interacting with the Slicer package manager endpoint.
Requires Python: >=3.7

Slicer package manager Python Client
====================================

Python client for managing Slicer application and extension packages
organized on a server with the corresponding Girder plugin installed.

The documentation is accessible at https://slicer-package-manager.readthedocs.io/en/latest/commands_shell.html#slicer-package-manager-client.

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

Install with::

    $ pip install slicer-package-manager-client

or::

    $ git clone https://github.com/girder/slicer_package_manager.git
    $ cd slicer_package_manager/python_client
    $ pip install -e .

for development.

Resources
---------

To learn more about the Slicer package manager server and associated client, check out the following resources.

* https://slicer-package-manager.readthedocs.io/en/latest/commands_shell.html#slicer-package-manager-client
* https://slicer-package-manager.readthedocs.io

License
-------

This software is licensed under the terms of the `Apache Licence Version 2.0 <https://github.com/girder/slicer_package_manager/blob/main/LICENSE>`_.
slicer-package-manager 0.9.0
Manage Slicer application and extension packages.
Requires Python: >=3.8
Keywords: girder-plugin, slicer_package_manager

======================
Slicer Package Manager
======================

|CircleCI| |Documentation|

.. |CircleCI| image:: https://circleci.com/gh/girder/slicer_package_manager.svg?style=svg
    :target: https://circleci.com/gh/girder/slicer_package_manager
    :alt: Build Status

.. |Documentation| image:: https://readthedocs.org/projects/slicer-package-manager/badge/?version=latest
    :target: https://slicer-package-manager.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status

The ``Slicer Package Manager`` includes a REST API service and CLI built on `Girder`_ for downloading, uploading
and organizing application and extension packages for both `3D Slicer`_ and `3D Slicer-based`_ applications.

.. _Girder: https://github.com/girder/girder
.. _3D Slicer: https://slicer.org
.. _3D Slicer-based: https://github.com/KitwareMedical/SlicerCustomAppTemplate


Documentation is available at https://slicer-package-manager.readthedocs.io

This software is licensed under the terms of the `Apache Licence Version 2.0 <https://github.com/girder/slicer_package_manager/blob/main/LICENSE>`_.
cismat 0.0.0
HiZXtman  sdafaf safafa sfsdf



# Installation


To install requirements: `python -m pip install requirements.txt`

To save requirements: `python -m pip list --format=freeze --exclude-editable -f https://download.pytorch.org/whl/torch_stable.html > requirements.txt`

* Note we use Python 3.9.4 for our experiments

# Running the code 

For remaining experiments: 

Navigate to the corresponding directory, then execute: `python run.py -m` with the corresponding `config.yaml` file (which stores experiment configs).

# License

Consult License.md
numerical-pde-solver 0.1.4
A small package for solving PDEs using numerical methods
Requires Python: >=3.6

# Numerical PDE Solver

## Overview
This package provides numerical solutions to Partial Differential Equations (PDEs) using Euler and Milstein methods, tailored for use in financial mathematics and other fields requiring the numerical solution of stochastic differential equations.

## Installation
Install this package by running:
```bash
pip install numerical-pde-solver

##  Usage 

from numerical_pde_solver.euler import euler_method

# Define your drift and diffusion functions
def f(x, t):
    # Drift coefficient function
    return -x

def g(x, t):
    # Diffusion coefficient function
    return 0.1

# Initial condition, start time, end time, and step size
x0, t0, T, dt = 0, 0, 1, 0.01

# Solve the SDE
t, x = euler_method(f, g, x0, t0, T, dt)

# Now `t` holds the time points, and `x` holds the solution at those points
from numerical_pde_solver.milstein import milstein_method

# Define your drift and diffusion functions for the SDE
def f(x, t):
    # Drift coefficient function as a placeholder example
    return 0.05 * x

def g(x, t):
    # Diffusion coefficient function as a placeholder example
    return 0.2 * x

# Define the partial derivative of the diffusion function with respect to x
def dg(x, t):
    # For the diffusion term g(x, t) = 0.2 * x, the derivative with respect to x is 0.2
    return 0.2

# Initial condition, start time, end time, and step size
x0, t0, T, dt = 1, 0, 1, 0.01

# Solve the SDE using the Milstein method
t, x = milstein_method(f, g, dg, x0, t0, T, dt)

# t holds the array of time points, and x holds the array of solution values at those points