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Python Installation old
ここでは Python と開発環境である PyCharm の導入方法を説明します.
ついでにおすすめの Python モジュールを紹介しておきます.
This repository explains how to install Python and development environment (PyCharm) in Windows PC.
This is for Sharing Knowledge in Shimamura Laboratory.
We introfuce installation by pip, it's not Anaconda.
Please follow the below procedure.
I strongly recommend to use pip instead of Anaconda !!
Firstly, install Python.
- Download
.exeof Python from official site. Recommended version is Python 3.6 ! If Windows 10, please clickWindows x86-64 executable installerin that page.
- Execute downloaded
.exefile.
When wondow is opened, Must turn on check box ofAdd Python 3.X to Path! And clickInstall Now.
Next, install PyCharm that is an strong development environment.
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Donload Community version of Pycharm from https://www.jetbrains.com/pycharm/download/#section=windows.
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Execute it and click
Next.
The following is almost the same as here.
To enable to release memory usage, show memory indicator.
From [File] > [Settings] > [Appearance & Behavior] > [Appearance] , turn on Show memory indicator.
@akiyoko blog : PyCharm のオレオレ最強設定
Then you can release memory by clicking memory indicator on the lower right corner like this.
@akiyoko blog : PyCharm のオレオレ最強設定
From [Help] > [Edit Custom VM Options],
you can open pycharm64 file.
From
# custom PyCharm VM options
-Xms128m
-Xmx750m
-XX:ReservedCodeCacheSize=240m
-XX:+UseCompressedOops
you can increase the upper-bound of memory usage by
# custom PyCharm VM options
-Xms2000m
-Xmx4000m
-XX:ReservedCodeCacheSize=240m
-XX:+UseCompressedOops
Of cause, memory limit is as you like, but must be set to match your PC environment!
The following modules are my recommendations to install. Basically, you can install & update them by command prompt. Please command
pip install (***module name***) --upgrade
Firstly, Please update pip in command prompt by the following command :
pip install pip --upgrade
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numpy
many usable calculation functions -
scipy
file loader, writer, signal processing tools -
scikit-learn
powerful machine learning tools -
matplotlib
graph tools -
numba
for @jit compile
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soundfile
wav IO tools -
pyaudio
real-time audio processor
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Pillow
image IO tools

