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import nipype.interfaces.io as nio
import nipype.pipeline.engine as pe
volsource = pe.Node(interface = nio.DataGrabber(outfields=["dw_imgs"]), name="volsource")
project_dir = "/mindhive/gablab/sad/PY_STUDY_DIR/Block"
volsource.inputs.base_directory = project_dir
volsource.inputs.template = "diffusion/preproc/SAD_*/%s_warp.nii.gz"
volsource.base_dir = '.'
volsource.inputs.template_args = dict(dw_imgs=[[["fa", "ra", "adc"]]])
res = volsource.run()

mwaskom

# vi: set ft=python sts=4 ts=4 sw=4 et:
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
"""
    Nipype interface script for the Fluid Intelligence project.
"""

import os
import sys
import argparse
from copy import deepcopy

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#! /usr/bin/env python
import os
from os.path import join as pjoin
import argparse

import nipype.interfaces.fsl as fsl
import nipype.interfaces.io as nio
import nipype.interfaces.utility as util
import nipype.pipeline.engine as pe
import nibabel as nib

mwaskom

import numpy as np
from scipy.stats import gamma

def gamma_params(peak, fwhm):
    """Return parameters to scipy.stats.gamma corresponding for an HRF shape.

    This was mostly copied from nipy.

    Parameters
    ----------

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mwaskom

{
 "metadata": {
  "name": "mrTutMR"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {

mwaskom

mwaskom

mwaskom

long pipe;

mwaskom

# from <module> import * is strongly discouraged
import numpy as np

# One way to make your array that shows off a few features
# Specifying it like you did is fine, but why bother?
a = np.arange(1, 7)
a[1::2] *= -1

# Again, just demonstrating some features
choice = np.array([np.ones(6),