"""
Resample the volume with user-defined slices.
"""
self.dataset.slices = (slice(*self.xslice),
slice(*self.yslice),
slice(*self.zslice))
self.plot()
def _preloaded_changed(self):
self.dataset.preloaded = not self.dataset.preloaded
if self.dataset.preloaded:
_tmp_list = self.preload_range[:]
_tmp_list[1] += 1
self.dataset.load_data(slice(*_tmp_list))
if not self.dataset.preloaded:
del self.dataset.data
if __name__ == '__main__':
from glob import glob
if glob('data/data*.npy') == []:
print "generating some synthetic data..."
from generate_data import generate_big_data
generate_big_data(l=60, t=15)
tv = TimeVisualizer('data/data*.npy')
tv.configure_traits()
tv.plot()
import numpy as np
from time_series_visualizer import TimeVisualizer
from generate_data import generate_big_data
from glob import glob
# Data in format 'h5'
print("Visualizing data stored in hdf5 format")
generate_big_data(l=60, t=10, mode='h5')
tv_h5 = TimeVisualizer('data/data*.h5', mode='h5', name='image')
tv_h5.configure_traits()
tv_h5.plot()
# Data in format 'npy'
print("Visualizing data stored in npy format")
generate_big_data(l=60, t=10, mode='npy')
tv_npy = TimeVisualizer('data/data*.npy', mode='npy')
tv_npy.configure_traits()
tv_npy.plot()
# Data in format 'raw'
print("Visualizing data stored in raw format")
generate_big_data(l=60, t=10, mode='raw')
tv_raw = TimeVisualizer('data/data*.raw', mode='raw', dtype=np.float,
shape=(60, 60, 60))
tv_raw.configure_traits()
tv_raw.plot()
