""" 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()