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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# General introduction\n", | ||
"\n", | ||
"## What can we do with Nilearn ?\n", | ||
"\n", | ||
"- Decoding and MultiVariate Pattern Analysis (MVPA)\n", | ||
"- Functional connectivity analysis\n", | ||
"- Extracting resting state networks (ICA, Dictionary Learning, ...)\n", | ||
"- Plotting brain images\n", | ||
"- Manipulating brain volumes\n", | ||
"- Downloading (open) datasets: atlases, cohorts ...\n", | ||
"\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# Installing Nilearn\n", | ||
"\n", | ||
"## 1. Install dependencies\n", | ||
"\n", | ||
"It is recommended to install a complete scientific Python distribution like [**64-bit Anaconda**](https://store.continuum.io/cshop/anaconda/)\n", | ||
"\n", | ||
"## 2. In a Terminal/Command prompt, install Nilearn\n", | ||
"\n", | ||
"- Open Terminal/Command prompt\n", | ||
"\n", | ||
"- **`pip install -U --user nilearn`**\n", | ||
"\n", | ||
"## 3. Open IPython\n", | ||
"\n", | ||
"- In Terminal/Command prompt:\n", | ||
"\n", | ||
"- **`ipython`**\n", | ||
"\n", | ||
"- in IPython:\n", | ||
"\n", | ||
"- *In [1]:* **`import nilearn`**" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# Setting the dataset folder\n", | ||
"\n", | ||
"**nilearn_data**: Where is the downloaded data stored?\n", | ||
"\n", | ||
"The fetching functions download the reference datasets to the disk. They save it **locally for future use**, in one of the following directories (in order of priority, if present):\n", | ||
"\n", | ||
"- the folder specified by **`data_dir` parameter** in the fetching function\n", | ||
"- the global environment variable **`NILEARN_SHARED_DATA`**\n", | ||
"- the user environment variable **`NILEARN_DATA`**\n", | ||
"- the **`nilearn_data`** folder in the **user home** folder\n", | ||
"\n", | ||
"The two different environment variables (NILEARN_SHARED_DATA and NILEARN_DATA) are provided for multi-user systems, to distinguish a global dataset repository that may be read-only at the user-level. \n", | ||
"\n", | ||
"You can copy that folder to another user’s computers to avoid the initial dataset download on the first fetching call.\n", | ||
"\n", | ||
"You can check in which directory nilearn will store the data with the function **`nilearn.datasets.get_data_dirs`**.\n" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 2", | ||
"language": "python", | ||
"name": "python2" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 2 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython2", | ||
"version": "2.7.11" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 0 | ||
} |
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