def setUp(self) -> None:
self.h5_sample_path = pathlib.Path(path.global_example_data,
"basic.h5")
self.repo = H5RepositoryWithCheckpoint(repo_path=self.h5_sample_path)
self.img = Image3dWithSpots(repository=self.repo,
image_path="mrna/arhgdia/2h/1")
self.nucleus_mask = self.img.get_nucleus_mask()
cell_mask = self.img.get_cell_mask()
self.cytoplasm_mask = (cell_mask == 1) & (self.nucleus_mask == 0)
def open_repo():
dataset_root_fp = pathlib.Path(
constants.analysis_config['DATASET_CONFIG_PATH'].format(
root_dir=global_root_dir)).parent
primary_fp = pathlib.Path(dataset_root_fp,
constants.dataset_config['PRIMARY_FILE_NAME'])
secondary_fp = pathlib.Path(
dataset_root_fp, constants.dataset_config['SECONDARY_FILE_NAME'])
repo = H5RepositoryWithCheckpoint(repo_path=primary_fp,
secondary_repo_path=secondary_fp)
return repo
def setUp(self) -> None:
self.h5_sample_path = pathlib.Path(path.global_example_data,
"basic.h5")
self.repo = H5RepositoryWithCheckpoint(repo_path=self.h5_sample_path)
self.img = ImageWithMTOC(repository=self.repo,
image_path="mrna/arhgdia/2h/1")
self.img1 = ImageWithMTOC(repository=self.repo,
image_path="mrna/arhgdia/2h/1")
self.img10 = ImageWithMTOC(repository=self.repo,
image_path="mrna/arhgdia/2h/10")
self.img11 = ImageWithMTOC(repository=self.repo,
image_path="mrna/arhgdia/2h/11")
self.img12 = ImageWithMTOC(repository=self.repo,
image_path="mrna/arhgdia/2h/12")
self.img13 = ImageWithMTOC(repository=self.repo,
image_path="mrna/arhgdia/2h/13")
mads.append(mse)
total_mads.append(mads)
return total_mads
# Figure 2.D Mean Absolute Deviation of Arhgdia mRNA distribution for peripheral fraction descriptors of a randomly selected cell
# from a pooled average of up to ~40 cells for cultured and micropatterned cells.
constants.init_config(analysis_config_js_path=pathlib.Path(
global_root_dir, "src/analysis/stability/config_original.json"))
dataset_root_fp = pathlib.Path(
constants.analysis_config['DATASET_CONFIG_PATH'].format(
root_dir=global_root_dir)).parent
primary_fp = pathlib.Path(dataset_root_fp,
constants.dataset_config['PRIMARY_FILE_NAME'])
secondary_fp = pathlib.Path(dataset_root_fp,
constants.dataset_config['SECONDARY_FILE_NAME'])
analysis_repo = H5RepositoryWithCheckpoint(repo_path=primary_fp,
secondary_repo_path=secondary_fp)
total_mads = []
for gene in constants.analysis_config['MRNA_GENES']:
total_mads.append(compute_stability(gene, bootstrap=500))
tgt_image_name = constants.analysis_config['FIGURE_NAME_FORMAT']
tgt_fp = pathlib.Path(
constants.analysis_config['FIGURE_OUTPUT_PATH'].format(
root_dir=global_root_dir), tgt_image_name)
plot.plot_figure(total_mads[0], total_mads[1], tgt_fp)
logger.info("Generated image at {}", str(tgt_fp).split("analysis/")[1])
def setUp(self) -> None:
self.h5_sample_path = pathlib.Path(path.global_example_data,
"basic.h5")
self.repo = H5RepositoryWithCheckpoint(repo_path=self.h5_sample_path)
self.img = Image3dWithSpots(repository=self.repo,
image_path="mrna/arhgdia/2h/1")
def setUp(self) -> None:
self.h5_sample_path = pathlib.Path(path.global_example_data, "basic.h5")
self.repo = H5RepositoryWithCheckpoint(repo_path=self.h5_sample_path)
def setUp(self) -> None:
self.h5_sample_path = pathlib.Path(path.global_example_data,
"basic.h5")
self.repo = H5RepositoryWithCheckpoint(repo_path=self.h5_sample_path)
self.img = Image3dWithIntensitiesAndMTOC(
repository=self.repo, image_path="protein/arhgdia/2h/1")
def setUp(self) -> None:
self.h5_sample_path = pathlib.Path(path.global_example_data,
"basic.h5")
self.repo = H5RepositoryWithCheckpoint(repo_path=self.h5_sample_path)
self.img = imageWithSpotsAndZlines(repository=self.repo,
image_path="mrna/actn2/immature/02")
