def _test_rcc_1():
"""
Test RCC drift correction.
"""
# Calculate drift correction.
param_name = storm_analysis.getData("test/data/test_drift.xml")
parameters = params.ParametersCommon().initFromFile(param_name)
data_name = storm_analysis.getData("test/data/test_drift.hdf5")
h5_name = storm_analysis.getPathOutputTest("test_rcc_hdf5.hdf5")
# Make a copy of the original as it will get modified and then
# git will pick this up.
shutil.copyfile(data_name, h5_name)
drift_output = storm_analysis.getPathOutputTest("test_drift_drift.txt")
[min_z, max_z] = parameters.getZRange()
rccDriftCorrection.rccDriftCorrection(h5_name, drift_output,
parameters.getAttr("frame_step"),
parameters.getAttr("d_scale"), min_z,
max_z, True)
# Verify results.
diffs = veri.verifyDriftCorrection(
storm_analysis.getData("test/data/test_drift.txt"), drift_output)
if (diffs[0] > 0.1):
raise Exception("Frame numbers do not match.")
# These thresholds are somewhat arbitrary.
if (diffs[1] > 0.1) or (diffs[2] > 0.1):
raise Exception("XY drift correction error.")
if (diffs[3] > 0.03):
raise Exception("Z drift correction error.")
def trackDriftCorrect(h5_name, params_file):
parameters = params.ParametersCommon().initFromFile(params_file)
std_analysis.trackDriftCorrect(h5_name, parameters)
"The name of the output movie (with background subtracted). This will be in .dax format."
)
parser.add_argument('--xml',
dest='settings',
type=str,
required=True,
help="The name of the settings xml file.")
args = parser.parse_args()
# Load movies and parameters.
input_movie = datareader.inferReader(args.in_movie)
[w, h, l] = input_movie.filmSize()
output_movie = daxwriter.DaxWriter(args.out_movie, h, w)
parameters = params.ParametersCommon().initFromFile(args.settings)
n_frames = parameters.getAttr("max_frame")
if (n_frames > l) or (n_frames == -1):
n_frames = l
# Default to a sample size if the settings file does not specify this.
sample_size = 100
if (parameters.getAttr("static_background_estimate", 0) > 0):
sample_size = parameters.getAttr("static_background_estimate")
else:
print(
"Did not find parameter 'static_background_estimate' in parameters file, defaulting to",
sample_size)
sbge = StaticBGEstimator(input_movie,