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codpy-0.1.8
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مشاهده بیشترتوضیحات
An RKHS based module for machine learning and data mining
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | codpy-0.1.8 |
| نام | codpy |
| نسخه کتابخانه | 0.1.8 |
| نگهدارنده | ['jean-marc mercier'] |
| ایمیل نگهدارنده | [] |
| نویسنده | jean-marc mercier |
| ایمیل نویسنده | jeanmarc.mercier@gmail.com |
| آدرس صفحه اصلی | https://github.com/johnlem/codpy_alpha |
| آدرس اینترنتی | https://pypi.org/project/codpy/ |
| مجوز | new BSD |
# Overview
Codpy is a kernel based, open source software library for high performance numerical computation, relying on the [RKHS](https://en.wikipedia.org/wiki/Reproducing_kernel_Hilbert_space) theory.
It contains a set of core tools that we use for machine Learning, statistics and numerical simulations. As a machine learning platform, it enjoys some interesting properties :
* It is a numerically efficient machine learning platform. We provide benchmark tools to compare codpy to other popular machine learning platforms.
* It is a white box method. Any learning machine has access to worst-error bounds computations. These allow to compute confidence levels of prediction on any test set. Moreover, reproducibility properties of kernel methods allow to fully understand and explain obtained results.
* Each learning machine has access to all classical differential operators. These properties allow us to use this library with any PDE (partial differential equations) approach.
* Each learning machine has access to optimal transport tools, much needed for statistics.
## Technical requirement
This version of the library is CPUs based, and is tested on
* windows / amd64 platforms
## Directory structure
Once installed (see below), navigate to ```<path\to\python39>\Lib\site-packages\codpy```. The directory structure should be
* ```codpy```
* ```docs```
* codpy-book.pdf is the codpy reference manual.
* *.ipynb are jupyter notebooks to reproduce the example of codpy book.
* ```com``` : low level tools and interface.
* ```pred``` : Wrappers to a number of prediction machines : kernels, neural networks, and more.
* ```data``` : Wrappers to data set handling
* ```proj``` : some examples of applications
* BTC_predictor.py : an example of time serie prediction.
* clustering.py : benchmarks of clustering methods.
* housing_prices.py : benchmarks for the venerable Boston house price data set.
* mnist_codpy.py : benchmarks for the MNIST data set.
* radon.py : an application for medical imagery.
* reordering.py : illustration of optimal transport tools.
* README.md : this document
* __init__.py : codpy loader
* include.py : called by __init__
# Installation
Note: this installation process has been tested on
* windows / amd64 platform
## prerequisite
### Minimum installation
* [python3.9.7](https://www.python.org/ftp/python/3.9.7/python-3.9.7-amd64.exe): a valid python python3.9.7 installation.
*NOTE* : Python installation differs from one machine to another. The python root folder is denoted "\<path/to/python39>" in the rest of this document. The software Everything (or another equivalent) can be of great help finding files.
### Dev installations
For information, we list the softwares that we are using for our dev configuration :
* [GitHub Desktop](https://desktop.github.com)
* [R](https://www.r-project.org): use any CRAN mirror for download
* [RStudio](https://rstudio.com): see the download link, then choose the free version
* [MiKTEX](https://miktex.org): see the download tab
* [Everything](https://www.voidtools.com/downloads/)
* [Visual Studio Code](https://code.visualstudio.com)
Those installations should be fine using the latest (64 bits) version and the default settings for each software .
*Note* Once R and RStudio are installed, open the latter.
In the console, enter "*install.packages("rmarkdown")*" to install [RMarkdown](https://rmarkdown.rstudio.com/index.html).
## Cloning repo
Download the codpy repo at [codpy alpha](https://github.com/JohnLeM/codpy_alpha) to your location <path/to/codpyrepo>
## Installation
### prerequisite
We suppose that there is a valid python installation on the host machine. The reader can
* either use its main python environment ```<path/to/python39>```
* or create a virtual python environment ```<path/to/venv>```, a good practice that we describe in the rest of this section.
First open a command shell ```cmd```, create a virtual environment and activate it.
```
python -m venv .\venv
.\venv\Scripts\activate
```
*NOTE* : In the rest of the installation procedure, we consider a virtual environment <path/to/venv>. One can replace with <path/to/python39> if a main environment installation is desired, for dev purposes for instance.
### pip install codpy
Open a command shell ```cmd```, and pip install codpy
```
pip install codpy
```
or from the local repository
```
pip install <path/to/codpyrepo>/dist/codpy-XXXX.whl
```
The installation procedure might take some minutes depending on your internet connection.
### Test codpy
open a python shell and import codpy
```
python
```
```
import codpy
```
# Testing with Visual Studio Code
You can your visual studio installation.
- With Visual Studio Code, open the ```<path/to/codpyrepo>``` folder and select for instance the file ```<path/to/codpyrepo>/proj/clustering.py```
- Select your python interpreter (Shift+P)
- Hit F5. If everything works, you should have some figures.
نیازمندی
| مقدار | نام |
|---|---|
| ==0.1.1 | codpydll |
| ==0.2.1 | SobolSequence |
| ==2.63.0 | google-api-python-client |
| ==4.1.3 | oauth2client |
| ==2.10.0 | pybind11 |
| ==1.5.0 | pandas |
| - | tk |
| - | numpy |
| ==3.6.0 | matplotlib |
| ==2022.2.0 | mkl |
| ==1.1.2 | scikit-learn |
| ==1.9.1 | scipy |
| ==2.10.0 | tensorflow |
| ==0.12.0 | seaborn |
| ==0.19.3 | scikit-image |
| ==4.6.0 | tensorflow-datasets |
| ==1.12.1 | torch |
| ==1.6.2 | xgboost |
| ==1.0.0 | jupyter |
| ==1.27 | quantlib |
| ==2.0.1 | xlrd |
| ==2.3.0 | pydicom |
| ==0.1.74 | yfinance |
| ==2022.9.0 | xarray |
| ==1.5.12 | kaggle |
| - | pandera |
| - | statsmodels |
نحوه نصب
نصب پکیج whl codpy-0.1.8:
pip install codpy-0.1.8.whl
نصب پکیج tar.gz codpy-0.1.8:
pip install codpy-0.1.8.tar.gz