def test_track_greedy():
nx, ny = 512, 512
sigma = None
tslice_to_regions = extract_regions(h5fname, sigma=sigma)
tracks = tracking.track_regions_greedy(tslice_to_regions, nx, ny)
tracks = tracking.chop_tracks(tracks, area_frac=0.1)
slice_regions = get_slice_regions(tracks)
track_regions_image(slice_regions, h5fname, sigma=sigma)
def track_regions_image(slice_regions, h5fname, sigma):
tslice_to_regions = extract_regions(h5fname, sigma=sigma)
dta = tables.openFile(h5fname, "r")
pl.ioff()
for idx, psi_arr in enumerate(dta.walkNodes("/psi", "Array")):
print idx
psi_arr = psi_arr.read()
psi_arr_mask = psi_arr.copy()
for (reg, num) in slice_regions[idx]:
psi_arr_mask[zip(*reg.region)] = 2 * psi_arr.max()
pl.figure()
pl.imshow(psi_arr_mask, interpolation="nearest", cmap="hot")
for (reg, num) in slice_regions[idx]:
loc = reg.loc
pl.text(loc[1], loc[0], str(num))
xs = [reg.loc[0] for reg in tslice_to_regions[idx][1]]
ys = [reg.loc[1] for reg in tslice_to_regions[idx][1]]
pl.scatter(ys, xs, c="r", marker="s")
pl.savefig("psi_%03d.pdf" % idx)
pl.close("all")
dta.close()
def fractional_energy(h5fname, sigma):
tslice_to_regions = extract_regions(h5fname, sigma=sigma)
dta = tables.openFile(h5fname, 'r')
efrac = []
rfrac = []
# efrac_by_regfrac = []
# dual = []
bx_arrs = dta.walkNodes('/bx', 'Array')
by_arrs = dta.walkNodes('/by', 'Array')
for idx, (bx_arr, by_arr) in enumerate(zip(bx_arrs, by_arrs)):
bx_arr = bx_arr.read()
by_arr = by_arr.read()
bmag_arr = bx_arr**2 + by_arr**2
bmag_arr_regions = np.zeros(bx_arr.shape, dtype=np.bool)
for reg in tslice_to_regions[idx][1]:
bmag_arr_regions[zip(*reg.region)] = True
reg_frac = float(np.sum(bmag_arr_regions)) / bmag_arr_regions.size
eng_frac = np.sum(bmag_arr[bmag_arr_regions]) / np.sum(bmag_arr)
efrac.append(eng_frac)
rfrac.append(reg_frac)
dta.close()
return np.array(efrac), np.array(rfrac)
