示例#1
0
from nisl import datasets, utils
from pynax import Figure, Mark, create_axes
import pylab as pl
import numpy as np

nyu = datasets.fetch_nyu_rest(n_subjects=1)
func = nyu.func[0]
niimg = utils.check_niimg(func)
fig = Figure((2, 3))
data = niimg.get_data()[..., 0]
# Awesome example activation map : take whatever is > .6 max
data_act = np.ma.MaskedArray(data, mask=(data < .6 * np.max(data)))

display_options = {}
display_options['interpolation'] = 'nearest'
display_options['cmap'] = pl.cm.gray

x, y, z = create_axes(['x', 'y', 'z'])
mx = Mark(x, 20)
my = Mark(y, 20)
mz = Mark(z, 20)
vx = fig.add((1, 2), data, mx, z, y, display_options=display_options)
vx.add_mark(my)
vx.add_mark(mz)
vy = fig.add((0, 2), data, my, z, x, display_options=display_options)
vy.add_mark(mx)
vy.add_mark(mz)
vz = fig.add((0, 0),
             data,
             mz,
             y,
示例#2
0
if len(sys.argv) > 1:
    import nibabel as nb
    f = nb.load(sys.argv[1])
    data = f.get_data()
    data_act = None
else:
    nyu = datasets.fetch_nyu_rest(n_subjects=1)
    func = nyu.func[0]
    niimg = utils.check_niimg(func)
    data = niimg.get_data()[..., 0]

    # Awesome example activation map : take whatever is > .6 max
    data_act = np.ma.MaskedArray(data, mask=(data < .6 * np.max(data)))

fig = Figure((2, 3))
display_options = {}
display_options['interpolation'] = 'nearest'
display_options['cmap'] = pl.cm.gray
display_options['pynax_colorbar'] = True

x, y, z = create_axes(['x', 'y', 'z'])
mx = Mark(x, 20)
my = Mark(y, 20)
mz = Mark(z, 20)
vx = fig.add((1, 2), data, mx, z, y, display_options=display_options)
vx.add_mark(my)
vx.add_mark(mz)
vy = fig.add((0, 2), data, my, z, x, display_options=display_options)
vy.add_mark(mx)
vy.add_mark(mz)
示例#3
0
from nisl import datasets, utils
from pynax import Figure, Mark, create_axes
import pylab as pl
import numpy as np

nyu = datasets.fetch_nyu_rest(n_subjects=1)
func = nyu.func[0]
niimg = utils.check_niimg(func)
fig = Figure((2, 7))
data = niimg.get_data()[..., 0]
# Awesome example activation map : take whatever is > .6 max
data_act = np.ma.MaskedArray(data, mask=(data < .6 * np.max(data)))

display_options = {}
display_options['interpolation'] = 'nearest'
display_options['cmap'] = pl.cm.gray

x, y, z = create_axes(['x', 'y', 'z'])
mx = Mark(x, 20)

marks = []
slices = []
for i in range(10):
    mz = Mark(z, i * 3 + 3)
    marks.append(mz)
    slices.append(fig.add((i / 5, i % 5), data, mz, x, y,
                          display_options=display_options))

    vx = fig.add((0, 5), data, mx, y, z, shape=(2, 2),
             display_options=display_options)
for m in marks:
示例#4
0
from nisl import datasets, utils
from pynax import Figure, Mark, create_axes
import pylab as pl
import numpy as np

nyu = datasets.fetch_nyu_rest(n_subjects=1)
func = nyu.func[0]
niimg = utils.check_niimg(func)
fig = Figure((2, 7))
data = niimg.get_data()[..., 0]
# Awesome example activation map : take whatever is > .6 max
data_act = np.ma.MaskedArray(data, mask=(data < .6 * np.max(data)))

display_options = {}
display_options['interpolation'] = 'nearest'
display_options['cmap'] = pl.cm.gray

x, y, z = create_axes(['x', 'y', 'z'])
mx = Mark(x, 20)

marks = []
slices = []
for i in range(10):
    mz = Mark(z, i * 3 + 3)
    marks.append(mz)
    slices.append(
        fig.add((i / 5, i % 5),
                data,
                mz,
                x,
                y,