utils package

Module contents

This is a collection of helper code for various python utilities.

Submodules

utils.display module

Functions for the purposing displaying data. Most of this work is based on matplotlib, but provides more convenient wrappers.

utils.display.get_color(name, tuple_type=True)

Returns the RGBa values in array for plot colors using the solarized pallette.

Parameters

  • name (str) – Color name

  • tuple_type (bool) – Whether or not to return a tuple or array

Returns

color_rgb – Color RGBa value in array form

Return type

array_like

utils.display.gif(data, file_name, dpi=80, interval=100)

This function will take an array with a temporal dimension (y, x, t) and save an animated gif.

Parameters

  • data (array_like) – The input data array (y, x, t)

  • file_name (str) – The input file name

  • dpi (int) – The saved image DPI

  • interval (int) – The frame rate interval

utils.display.im_movie(data, duration=0.05, cm='gray')

Takes a 3D array (y, x, t) and displays the data as movie.

Note: this still needs to call the plt.show() command after running this command to get the stuff to display.

Parameters

  • data (array_like) – 3D array to be displayed (y, x, t)

  • duration (float) – Duration of pause between frames

  • cm (str) – Colormap type

utils.display.render(X, colormap='gray', vmax=None, vmin=None)

This function takes a 3D array X and creates a tiled montage image.

Parameters

  • X (array_like) – 3D array (y, x, z)

  • colormap (str) – Colormap to be used

  • vmax (float) – Maximum value in display

  • vmin (float) – Minimum value in display

utils.display.save_image(data, cm, fn)

This function tries to save the image without borders for publication purposes. (Not sure if it works.)

Parameters

  • data (array_like) – The image to be displayed

  • cm (str) – The colormap to be used

  • fn (str) – The saved image filename

utils.display.set_plot()

This function will generate figures with properly thick lines and large fonts.

utils.matutils module

utils.matutils.matreader(filename, keyName=None, memberName=None, verbose=False, save=False)

Reader for matlab .mat files.

Parameters

  • filename (str) – Name of mat file being read

  • keyName (str, optional) – Name of the key that you are reading in

  • memberName (str, optional) – Name of the member if the underlining object is a Matlab struct

  • verbose (bool, optional) – Whether or not you want verbose output

  • save (bool, optional) – Option to save the file to a numpy file

Returns

data – The data from the mat file in some form of numpy array

Return type

array_like

utils.mkdir module

utils.mkdir.create_tree(pathName)

This function will take a folder saved in a different location and create an identical tree at a different location. These are controlled by the names variable, which is a dictionary that is hardcoded at the moment.

Parameters

pathName (str) – The path to the folder that you want to relocate

Returns

pathName – The new folder full path

Return type

str

utils.mkdir.get_patient_number(path)

Takes the path name form the DiBella pathname convention.

Parameters

path (str) – The path to be analyzed

Returns

patientNumber – The patient number

Return type

str

utils.readhdf5 module

utils.readhdf5.read_hdf5(fileName, varName)

Read HDF5 file with some variable name as a dictionary key.

Parameters

  • fileName (str) – The hdf5 file name

  • varName (str) – The hdf5 dictionary key name

Returns

data – The data returned in a numpy array

Return type

array_like

utils.roiselector module

Classes and functions that provide the ability to select some arbitrary region of interest (ROI) and return some statistics over that region.

class utils.roiselector.PolygonSelect(data, zMiddle=None)

Bases: object

This class reads in an image an allows the user to graphically select and ROI to generate statistics based on the underlying pixel values.

To do the selection: 1. Select points in the figure by enclosing them within a polygon. 2. Press the ‘esc’ key to start a new polygon. 3. Try holding the ‘shift’ key to move all of the vertices. 4. Try holding the ‘ctrl’ key to move a single vertex.

Parameters

  • data (array_like) – Image data to be analyzed. Can be 2D (y,x) or 3D (y,x,t). The ROI is selected from a single frame and is applied to all time images subsequently

  • zMiddle (int) – The time frame to be used if the image is 3D

display_roi(saveName=None)

Displays the ROI overlayed on top of the image used for the selection. Not displayed until plt.show() is called.

Parameters

saveName (str) – The filename of the figure being saved

generate_mask()

Generates a 2D (x,y) mask from the selected ROI.

Returns

mask – Mask (y,x) of the selected ROI in 1’s (selection) and 0’s (not-selected)

Return type

array_like

polygon_mean()

Generate the mean values based on the selected ROI. Will calculated the mean on a per frame basis. If the input image is 2D, then a scalar is given. If it is 3D, then the means will be calculated over the ROI at each time frame and a 1D array will be given.

Returns

meanValues – Mean values calculated over the ROI for each time frame

Return type

str or array_like

utils.roiselector.polygon_mean(data, mask)

Given some input image and the mask of the ROI desired (1’s are pixels of interest and 0’s are not), find the mean value.

This function assumes a 2D image can calculates the mean as a scalar, but a temporal dimension can also be added. In that case, the same ROI is used at each time frame, and the output is given as a 1D array.

Parameters

  • data (array_like) – 2D (y,x) or 3D (y,x,t) data array

  • mask (array_like) – 2D (y,x) array of 1’s and 0’s, pixels of 1’s are the pixels that are ultimately counted in the mean

Returns

meanValues – Array of mean values if the input is 3D (temporal), a float is given it is strictly 2D

Return type

array_like (or float)

utils.roiselector.rectangle_mean(image, zMiddle=None)

Based on some input image, calculate the mean over some selected rectangular ROI.

While this function does allow 3D images, the ROI is selected over one image and used for all images in the third dimension.

Parameters

  • image (array_like) – Image used. Can be 2D (y,x) or 3D (y,x,z)

  • zMiddle (int) – The image used in the selection of the rectangle

Returns

meanValue – The mean value for the ROI

Return type

float or array_like

utils.roiselector.rectangle_select(image)

Do a mouseclick somewhere, move the mouse to some destination, release the button. This class gives click- and release-events and also draws a line or a box from the click-point to the actual mouseposition (within the same axes) until the button is released. Within the method ‘self.ignore()’ it is checked whether the button from eventpress and eventrelease are the same.

Parameters

image (array_like) – 2D (y,x) or 3D (y,x,t) image to be analyzed. The ROI is drawn on only one frame, however

Returns

coordinates – The vertices of the selection (x1, x2, y1, y2)

Return type

tuple