<jupyter_start><jupyter_text>Show overlay map in sliced glassbrain  1. Upload all statistical maps into the data folder The `data` folder can be found in the same folder as this notebook. Just drag and drop your NIfTI file into the data folder and press the **upload** button.  2. Specify relevant visualization parameters<jupyter_code># Template to use for background
mnipath = '../scripts/templates/MNI152_T1_1mm_brain.nii.gz'

# Direction to make the cuts, can be x, y, z, xy, xz, yz, xyz
ortho = 'xyz'

# How many rows should the cuts be distributed over
nRows = 2

# How many cuts should be included in the figure
nCuts = 6

# Should left / right annotation be shown
showLRannot = 1

# What should be shown: Brain, Numbers, Both
figLayout = 'Both'

# Positive threshold for overlay
threshpos = 3

# Negative threshold for overlay
threshneg = 3

# Should optimal cut spacing be estimated or not (not means equal spacing)
findOptimalCut = 1

# File extension to use for figure
imageType = 'png'<jupyter_output><empty_output><jupyter_text>3. Run the visualization script<jupyter_code>%run ../scripts/plot_glassbrain_slices.py \
    data \
    $mnipath \
    $ortho \
    $nRows \
    $nCuts \
    $showLRannot \
    $figLayout \
    $threshpos \
    $threshneg \
    $findOptimalCut \
    $imageType<jupyter_output>/home/mnotter/anaconda/lib/python2.7/site-packages/nilearn/plotting/displays.py:649: UserWarning: empty mask
  get_mask_bounds(new_img_like(img, not_mask, affine))
/home/mnotter/anaconda/lib/python2.7/site-packages/numpy/ma/core.py:4144: UserWarning: Warning: converting a masked element to nan.
  warnings.warn("Warning: converting a masked element to nan.")<jupyter_text>4. Look at your data<jupyter_code>from IPython.display import Image, display
outputs = sorted(gg('data/figures/*.%s' % imageType))
for o in outputs:
    a = Image(filename=o)
    display(a)<jupyter_output><empty_output>
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