mrbles.data module

Data Classes and Functions

This file stores the data classes and functions for the MRBLEs Analysis module.

class mrbles.data.ImageDataFrame(data=None)[source]

Bases: future.types.newobject.newobject

Xarray based dataframe object for images.

Variables:
  • data (Xarray DataArray) – Returns (cropped, if crop_x and/or crop_y is set) Xarray DataArray.
  • xdata (Xarray DataArray) – Returns uncropped Xarray DataArray.
  • sets (list) – Returns a list of all set names, if ‘set’ column is present.
  • crop_x (slice) – Crop X slice. Set with slice().
  • crop_y (slice) – Crop Y slice. Set with slice().
combine(images)[source]

Combine iamges with dataframe.

Parameters:images (Xarray DataArray, dict of Xarray DataArrays)
crop_x

Crop X slice. Set with slice().

crop_y

Crop Y slice. Set with slice().

data

Return cropped Xarray dataframe.

static get_dim_names(data_set, set_dim='c')[source]

Return list of dimension names.

static get_set_names(data_set)[source]

Return list of sets.

sets

Return list of sets.

shift_channel(channel, x_shift, y_shift)[source]

Shift images of channel by x and y pixels.

WARNING: This will shift the images permanently and sets inbound pixels to 0. Reload images to reset.

Parameters:
  • channel (str) – Channel name to shift.
  • x_shift (int) – Pixels to shift in X dimension.
  • y_shift (int) – Pixels to shift in Y dimension.
xdata

Return uncropped Xarray dataframe.

class mrbles.data.ImageSetRead(file_path, series=0, output='xr')[source]

Bases: mrbles.data.ImageDataFrame

Image set data object that loads image set from file(s).

Parameters:
  • file_path (string/list [string, string, …]) – File path as string, e.g. ‘C:/folder/file.tif’, or as list of file paths, e.g. [‘C:/folder/file.tif’, ‘C:/folder/file.tif’].
  • series (int, optional) – Sets the series number if file has multiple series. To Loads all series set to series=’all’. Defaults to 0.
  • output (str, optional) – Sets default output method. Options: ‘nd’ for NumPy ndarray or ‘xd’ for xarray. Defaults to ‘ndarray’.
Variables:

function descriptions. (See) –

Returns:

  • _dataframe (xarray dataframe) – Returned when calling the instance.
  • _dataframe[idx] (NumPy ndarray) – Returns the index value or slice values: [start:stop:stride]. Warning: when using column names stop values are included.

Examples

>>> image_data_object = ImageSetRead('C:/folder/file.tif')
>>> image_files = ['C:/folder/file.tif', 'C:/folder/file.tif']
>>> image_data_object = ImageSetRead(image_files, output='xd')
>>> image_data_object['BF', 100:400, 100:400]
    (301L, 301L)
axes

Return data order.

Returns:data_order – Returns order as string with: P for position; F for file; T for timepoint, C for channel; Y for Y-axis; X for X-axis.
Return type:string

Examples

>>> image_data_object = ImageSetRead('C:/folder/file.tif')
>>> image_data_object.axes
'TCYX'
c_index(name)[source]

Return channel number.

c_names

Return channel names.

c_size

Return channel count.

f_names

Return file names.

f_size

Return file count.

is_multi_file

Return if from multiple files.

classmethod load(file_path, series=0)[source]

Load image files into data structures.

Class method. Can be used without instantiating.

Parameters:
  • file_path (string/list [string, string, …]) – File path as string, e.g. ‘C:/folder/file.tif’, or as list of file paths, e.g. [‘C:/folder/file.tif’, ‘C:/folder/file.tif’].
  • series (int, optional) – Sets the series number if file has multiple series (or positions). Use series=’all’ for loading all series. Defaults to 0.

Examples

>>> ImageSetRead.load('C:/folder/file.tif')
>>> image_files = ['C:/folder/file.tif', 'C:/folder/file.tif']
>>> ImageSetRead.load(image_files)
p_size

Return position count.

s_size

Return series count.

static scan_path(path, pattern='.*.tif')[source]

Scan folder recursively for files matching the pattern.

Parameters:
  • path (string) – Folder path as string, e.g. r’C:/folder/file.tif’.
  • pattern (string) – General file pattern as search string, e.g. ‘20160728_MOL_*’, using regular expressions (regex). Defaults to ‘.*.tif’.
classmethod scan_paths(paths, pattern='.*.tif')[source]

Scan folders recursively for files matching the pattern.

Parameters:
  • paths (list) – Folder paths as list, e.g. [‘C:/folder/file.tif’, …].
  • pattern (string) – General file pattern as search string, e.g. ‘20160728_MOL_*’, using regular expressions (regex).
t_deltas

Return time deltas between each image acquisition.

Default in milliseconds (ms), check object.t_unit for time unit.

t_interval

Return set time interval.

Default in milliseconds (ms), check object.t_unit for time unit.

t_size

Return time-point count.

t_unit

Return time unit.

z_size

Return Z-slice count.

class mrbles.data.TableDataFrame(data=None, flag_filt=True, **kwargs)[source]

Bases: future.types.newobject.newobject

Pandas based dataframe object for table data.

Variables:
  • data (Pandas DataFrame) – Returns (filtered, if ‘filter’ column is present) Pandas DataFrame.
  • pdata (Pandas DataFrame) – Returns unfiltered Pandas DataFrame
  • sets (list) – Returns a list of all set names, if ‘set’ column is present.
combine(data)[source]

Combine data with dataframe.

Parameters:data (Pandas DataFrame)
data

Return Pandas dataframe object.

static get_set_names(data_set, set_dim='set')[source]

Return list of sets.

pdata

Return unflagged Pandas dataframe.

sets

Return list of sets.