<commit_before>#!/usr/bin/env python2

"""Produce parametric maps by fitting one or more diffusion models to imaging
data. Multiple input images can be provided in ASCII format. Single input image
can be provided as a group of DICOM files. Output is written in ASCII files
named by input and model."""

from __future__ import absolute_import, division, print_function
import os.path
import argparse

import numpy as np

import dwi.dwimage
import dwi.files
import dwi.mask
import dwi.models


def parse_args():
    """Parse command-line arguments."""
    p = argparse.ArgumentParser(description=__doc__)
    p.add_argument('-v', '--verbose', action='count',
                   help='increase verbosity')
    p.add_argument('-l', '--listmodels', action='store_true',
                   help='list available models')
    p.add_argument('-a', '--average', action='store_true',
                   help='average input voxels into one')
    p.add_argument('--mask',
                   help='mask file')
    p.add_argument('-s', '--subwindow', metavar='I', nargs=6, type=int,
                   help='use subwindow (specified by 6 one-based indices)')
    p.add_argument('-m', '--models', metavar='MODEL', nargs='+', default=[],
                   help='models to use')
    p.add_argument('-i', '--input', metavar='PATH', nargs='+', default=[],
                   help='input files (or DICOM directories)')
    p.add_argument('-o', '--output', metavar='PATH',
                   help='output file (for single model and input only)')
    return p.parse_args()


def fit(image, timepoints, model):
    """Fit model to image."""
    shape = image.shape[:-1]
    image = image.reshape(-1, len(timepoints))
    assert len(timepoints) == len(image[0]), len(image[0])
    # self.start_execution()
    pmap = model.fit(timepoints, image)
    # self.end_execution()<commit_msg>removed shortened versions of some arguments<commit_after>#!/usr/bin/env python2

"""Produce parametric maps by fitting one or more diffusion models to imaging
data. Multiple input images can be provided in ASCII format. Single input image
can be provided as a group of DICOM files. Output is written in ASCII files
named by input and model."""

from __future__ import absolute_import, division, print_function
import os.path
import argparse

import numpy as np

import dwi.dwimage
import dwi.files
import dwi.mask
import dwi.models


def parse_args():
    """Parse command-line arguments."""
    p = argparse.ArgumentParser(description=__doc__)
    p.add_argument('-v', '--verbose', action='count',
                   help='increase verbosity')
    p.add_argument('--listmodels', action='store_true',
                   help='list available models')
    p.add_argument('--average', action='store_true',
                   help='average input voxels into one')
    p.add_argument('--mask',
                   help='mask file')
    p.add_argument('--subwindow', metavar='I', nargs=6, type=int,
                   help='use subwindow (specified by 6 one-based indices)')
    p.add_argument('-m', '--models', metavar='MODEL', nargs='+', default=[],
                   help='models to use')
    p.add_argument('-i', '--input', metavar='PATH', nargs='+', default=[],
                   help='input files (or DICOM directories)')
    p.add_argument('-o', '--output', metavar='PATH',
                   help='output file (for single model and input only)')
    return p.parse_args()


def fit(image, timepoints, model):
    """Fit model to image."""
    shape = image.shape[:-1]
    image = image.reshape(-1, len(timepoints))
    assert len(timepoints) == len(image[0]), len(image[0])
    # self.start_execution()
    pmap = model.fit(timepoints, image)
    # self.end_execution()
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