%matplotlib inline
from __future__ import print_function
import numpy as np
import matplotlib.pyplot as plt
import nibabel as nib

def plot_slice(fname, z_idx=5):

    # Load the image and collect the data
    # and orientation information
    img = nib.load(fname)
    data = img.get_data()
    aff = img.get_affine()

    # Find the center of the brain matrix
    ctr = np.dot(np.linalg.inv(aff), [0, 0, 0, 1])[:3]

    # Plot the data
    vmin, vmax = (0, 1) if data.dtype == np.int16 else (30, 150)
    plt.imshow(np.rot90(data[:, :, ctr[2] + z_idx]), 
               cmap="gray", vmin=vmin, vmax=vmax)
    plt.gca().set_axis_off()

plot_slice("data/T1.nii.gz")

!bet data/T1.nii.gz data/T1_bet.nii.gz

plot_slice("data/T1_bet.nii.gz")

!bet

!bet data/T1 data/T1_bet -m
plot_slice("data/T1_bet_mask.nii.gz")

from nipype.interfaces.fsl import BET

print(BET.__doc__)

print(BET.help())

skullstrip = BET()
skullstrip.inputs.in_file = "data/T1.nii.gz"
skullstrip.inputs.out_file = "data/T1_bet_nipype.nii.gz"

skullstrip = BET(in_file="data/T1.nii.gz", out_file="data/T1_bet_nipype.nii.gz")

print(skullstrip.cmdline)

skullstrip.inputs.mask = True
print(skullstrip.cmdline)

skullstrip.run()

plot_slice("data/T1_bet_nipype.nii.gz")

skullstrip2 = BET()
skullstrip2.run()

skullstrip.inputs.mask = "mask_file.nii"

skullstrip.inputs.in_file = "data/oops_a_typo.nii"

skullstrip = BET(in_file="data/T1.nii.gz")
print(skullstrip.cmdline)

res = skullstrip.run()
print(res.outputs)

res2 = skullstrip.run(mask=True)
print(res2.outputs)

from nipype.interfaces.spm import Realign
print(Realign.help())

!gunzip -c data/timeseries.nii.gz > data/timeseries.nii  # SPM cannot read compressed files natively
realign = Realign(in_files="data/timeseries.nii")
realign.inputs.register_to_mean = False
realign.inputs.interp = 3
# realign.run()  # Uncomment if you have SPM installed and want it to run

def add_two(x):
    return x + 2

from nipype import Function
addtwo = Function(input_names=["x"],
                  output_names=["val"],
                  function=add_two)

print(addtwo.run(x=4).outputs.val)

!make clean