Utilities module

Utilities module#

class napari_stress.utils.TimelapseConverter#

This class allows converting napari 4D layer data between different formats.

data_to_list_of_data(data, layertype: type) → list#

Convert 4D data into a list of 3D data frames

Parameters:

Raises:

TypeError – Error to indicate that the converter does not support the passed layertype

Returns:

list

Return type:

List of 3D objects of input layertype

list_of_data_to_data(data, layertype: type)#

Function to convert a list of 3D frames into 4D data.

Parameters:

Raises:

TypeError – Error to indicate that the converter does not support the passed layertype

Return type:

4D data of type layertype

napari_stress.utils.compile_data_from_layers(results_stress_analysis: list, n_frames: int, time_step: float) → list#

Compile data from the results of the stress analysis into a list of dataframes.

Parameters:

results_stress_analysis (list) – List of tuples containing the results of the stress analysis
n_frames (int) – Number of frames in the data
time_step (float) – Time step between frames

Returns:

df_over_time (pd.DataFrame) – Dataframe containing the singular values results, e.g. results from the stress analysis that refer to a single value per frame. Columns:

timefloat
Time of the frame

etc.
df_nearest_pairs (pd.DataFrame) – Dataframe containing the nearest pair extrema results. Columns:

timefloat
Time of the frame

nearest_pair_distancefloat
Distance between the nearest pairs of extrema

nearest_pair_anisotropyfloat
Stress Anisotropy of the nearest pair
df_all_pairs (pd.DataFrame) – Dataframe containing the all pair extrema results. Columns:

timefloat
Time of the frame

all_pair_distancefloat
Distance between all pairs of extrema

all_pair_anisotropyfloat
Stress Anisotropy of all pairs
df_autocorrelations (pd.DataFrame) – Dataframe containing the spatial autocorrelation results. Columns:

timefloat
Time of the frame

distancesfloat
Distances at which the autocorrelation was calculated

autocorrelation_totalfloat
Autocorrelation of the total stress

autocorrelation_cellfloat
Autocorrelation of the cell stress

autocorrelation_tissuefloat
Autocorrelation of the tissue stress

napari_stress.utils.export_settings(settings: dict, parent=None, file_name: str | None = None) → None#

Export settings to yaml file.

Parameters:

napari_stress.utils.frame_by_frame(function: callable, progress_bar: bool = False)#

Decorator to apply a function frame by frame to 4D data.

Parameters:

function (callable) –
Function to be wrapped. If the optional argument use_dask is passed to the function, the function will be parallelized using dask:
```
>>> @frame_by_frame(some_function)(argument1, argument2, use_dask=True)
```
Note: For this to work, the arguments (e.g., the input data) must not be passed as keyword argument. I.e., this works:
```
>>> @frame_by_frame(some_function)(argument1, argument2, some_keyword='abc', use_dask=True)
```
This does not work:
```
>>> @frame_by_frame(some_function)(image1=argument1, image2=argument2, some_keyword='abc', use_dask=True)
```
progress_bar (bool, optional) – Show progress bar, by default False. Has no effect if use_dask=True is passed as an argument to the input function function.

Returns:

Wrapped function

Return type:

callable

napari_stress.utils.import_settings(parent=None, file_name: str | None = None) → dict#

Import settings from yaml file.

Parameters:: parent (QWidget, optional) – Parent widget for dialog, by default None
Returns:: Dictionary of settings
Return type:: dict