def filter(self, delta):
feature = delta.get_feature()
prj = feature.get_coordinate_system().get_projection(self.prj_settings)
v = [k.to(self.unit).value for k in delta.get_angular_velocity_vector(prj)]
x_dir = self.x_dir
if x_dir == 'position_angle':
x_dir = prj.p2s(p2i(feature.get_coord()))
vx, vy = nputils.vector_projection(v, x_dir)
dy, dx = delta.get_delta()
vn = np.linalg.norm([vx, vy])
dn = np.linalg.norm([dx, dy])
res = True
for v_range, value, v_pix in zip([self.vxrange, self.vyrange, self.normrange], [vx, vy, vn], [dx, dy, dn]):
if np.abs(v_pix) < self.pix_limit:
continue
if v_range is not None and not nputils.in_range(value, v_range):
res = False
break
logger.debug("DeltaRangeFilter: delta=%s, v=%s, vp=%s, res=%s" % (delta.get_delta(), v, [vx, vy], res))
return res
def filter(self, delta):
feature = delta.get_feature()
prj = feature.get_coordinate_system().get_projection(self.prj_settings)
v = [k.to(self.unit).value for k in delta.get_angular_velocity_vector(prj)]
x_dir = self.x_dir
if x_dir == 'position_angle':
x_dir = prj.p2s(p2i(feature.get_coord()))
vx, vy = nputils.vector_projection(v, x_dir)
dy, dx = delta.get_delta()
vn = np.linalg.norm([vx, vy])
dn = np.linalg.norm([dx, dy])
res = True
for v_range, value, v_pix in zip([self.vxrange, self.vyrange, self.normrange], [vx, vy, vn], [dx, dy, dn]):
if np.abs(v_pix) < self.pix_limit:
continue
if v_range is not None and not nputils.in_range(value, v_range):
res = False
break
logger.debug("DeltaRangeFilter: delta=%s, v=%s, vp=%s, res=%s" % (delta.get_delta(), v, [vx, vy], res))
return res
def stack_cross_correlation(ctx, config, debug=0, nwise=2, stack=None):
"""Perform a Stack Cross Correlation analysis
Parameters
----------
ctx : :class:`wise.project.AnalysisContext`
config : :class:`wise.scc.SCCConfiguration`
debug : int, optional
nwise : int, optional
stack : :class:`libwise.plotutils.FigureStack`, optional
Returns
-------
:class:`wise.scc.StackCrossCorrelation` : a StackCrossCorrelation containing the results of the analysis
.. _tags: task_scc
"""
scc_result = scc.StackCrossCorrelation(config, debug=debug, stack=stack)
all_files = nputils.nwise(ctx.files, nwise)
for pair in all_files:
img1 = ctx.open_file(pair[0])
img2 = ctx.open_file(pair[-1])
prj = ctx.get_projection(img1)
delta_t, velocity_pix, tol_pix = scc_result.get_velocity_resolution(prj, img1, img2)
if not nputils.in_range(tol_pix, config.get("tol_pix_range")):
print "-> Skip: Not in the allowed range of pixel velocity resolution:", tol_pix
continue
res1 = ctx.detection(img1, filter=config.get("filter1"))
print "-> Numbers of detected SSP: %s" % ", ".join([str(k.size()) for k in res1])
res2 = ctx.detection(img2, filter=config.get("filter2"))
scc_result.process(prj, res1, res2)
return scc_result
def bootstrap_scc(ctx, config, output_dir, n, nwise = 2, append=False,
verbose=False, seperate_scales=False):
"""Perform Stack Cross Correlation analysis n time and store results in output_dir
Parameters
----------
ctx : :class:`wise.project.AnalysisContext`
config : :class:`wise.scc.SCCConfiguration`
output_dir : str
n : int
append : bool, optional
Append results
seperate_scales : bool, optional
.. _tags: task_scc
"""
random_shift = config.get("img_rnd_shift")
if config.get("shuffle") == config.get("rnd_pos_shift"):
print "Configuration Error: either 'shuffle' or 'rnd_pos_shift' need to be set"
return
all_files = list(ctx.files)
prj = ctx.get_projection(ctx.open_file(all_files[0]))
all_res1 = dict()
all_res2 = dict()
all_epochs = []
for file1 in ctx.files:
img1 = ctx.open_file(file1)
img1.data = nputils.shift2d(img1.data, np.random.uniform(-random_shift, random_shift, 2))
img2 = ctx.open_file(file1)
img2.data = nputils.shift2d(img2.data, np.random.uniform(-random_shift, random_shift, 2))
res1 = ctx.detection(img1, filter=config.get("filter1"))
print "-> Numbers of detected SSP: %s" % ", ".join([str(k.size()) for k in res1])
res2 = ctx.detection(img2, filter=config.get("filter2"))
print "-> Numbers of detected SSP: %s" % ", ".join([str(k.size()) for k in res2])
all_res1[file1] = res1
all_res2[file1] = res2
all_epochs.append(img1.get_epoch())
t = time.time()
# all_segments2_img = dict()
# for file, segments2 in all_res2.items():
# all_segments2_img[file] = [k.get_img().data.copy() for k in segments2]
if not os.path.exists(output_dir):
os.mkdir(output_dir)
files = os.listdir(output_dir)
if append and len(files) > 0:
if seperate_scales and os.path.isdir(os.path.join(output_dir, files[0])):
files = os.listdir(os.path.join(output_dir, files[0]))
all_i = sorted([int(os.path.splitext(file)[0].split('_')[-1]) for file in files])
if len(all_i) == 0:
start = 0
else:
start = all_i[-1] + 1
else:
start = 0
for i in range(n):
eta = ""
if i > 0:
remaining = (np.round((time.time() - t) / float(i) * (n - i)))
eta = " (ETA: %s)" % time.strftime("%H:%M:%S", time.localtime(time.time() + remaining))
print "Run %s / %s%s" % (i + 1, n, eta)
if config.get("shuffle"):
# np.random.shuffle(all_files)
shuffled = nputils.permutation_no_succesive(all_files)
files_pair = nputils.nwise(shuffled, nwise)
else:
files_pair = nputils.nwise(all_files, nwise)
epochs_pair = nputils.nwise(all_epochs, nwise)
scc_result = scc.StackCrossCorrelation(config, verbose=verbose)
for shuffled_pair, epoch_pair in zip(files_pair, epochs_pair):
res1 = all_res1[shuffled_pair[0]]
res2 = all_res2[shuffled_pair[-1]]
# for segments2, segments2_img in zip(res2, all_segments2_img[shuffled_pair[-1]]):
# segments2.get_img().data = nputils.shift2d(segments2_img,
# np.random.uniform(-random_shift, random_shift, 2))
res1.epoch = epoch_pair[0]
res2.epoch = epoch_pair[-1]
delta_t, velocity_pix, tol_pix = scc_result.get_velocity_resolution(prj, res1, res2)
if not nputils.in_range(tol_pix, config.get("tol_pix_range")):
print "-> Skip: Not in the allowed range of pixel velocity resolution:", tol_pix
continue
scc_result.process(prj, res1, res2)
if seperate_scales:
for scale, gncc_map in scc_result.get_mean_ncc_scales(smooth_len=1).items():
save_dir = os.path.join(output_dir, "scale_%s" % scale)
if not os.path.exists(save_dir):
os.mkdir(save_dir)
imgutils.Image(gncc_map).save_to_fits(os.path.join(save_dir, "gncc_map_%s.fits" % (start + i)))
else:
gncc_map = scc_result.get_global_ncc(smooth_len=1)
imgutils.Image(gncc_map).save_to_fits(os.path.join(output_dir, "gncc_map_%s.fits" % (start + i)))
print "Done"