figureflow.figure_panel.FigurePanel.show_images

figureflow.figure_panel.FigurePanel.show_images = <function FigurePanel.show_images>

Display images of current panel. Always use function that annotate within the image after functions that annotate outside of the image. Ranges seemingly can only be extracted from ImageJ images if the LUT is set to gray.

Parameters:

  • images – List of images (integers) which should be displayed each image corresponds to one image file for the panel

  • channel – List of channels (integers) which should be displayed composite/composite images can be by adding a string with all channel numbers separated by “-“, e.g. channels=[0,1,2,”0-1-2”]. dimension is extracted from ImageJ Hyperstack information

  • slices – List of slices (integers) which should be displayed dimension is extracted from ImageJ Hyperstack information

  • frames – List of frames (integers) which should be displayed dimension is extracted from ImageJ Hyperstack information

  • order_of_categories – List of strings with order of the image dimensions (“images”, “channels”, “slices”, “frames”), determines how images will be put into a grid. Images of different dimensions values for a dimension earlier in the list will be closer together (e.g. for [“frames”, “channels”] first all frames from one channel will be shown then all frames from the other channel)

  • focus – String of dimensions (“images”, “channels”, “slices”, “frames”) that will be alone on one axis of the image grid (e.g. for “frames” all different frames will be along one axis (e.g. columns) while the different images and channels will be along the other axis (e.g. rows).

  • show_focus_in – “row” or “column” - allows to fix in which dimension the focus will be shown

  • interpolate_images – Type of interpolation for the matplotlib function ax.imshow

  • dimension_equal – Determines in which dimension (“height” or “width”) images should be similar e.g. for “height”, images in same row will be adjusted to have the same height for “width images in same column will be adjusted to have the same width

  • scale_images – Boolean. Whether images should be scaled to fit into an even grid. dimension_equal will only be considered if scale_images == True scaling is necessary to show zoomed regions actually enlarged however, it might be a problem if it is important for the data to be equally scaled in the entire panel

  • flip_images – On which axis the images should be flipped (allowed avalues: “x” or “y”). If None, images will not be flipped.

  • auto_image_sub_param – String. Substring in panel file names that defines how images should be grouped into image_sub automatically (without defining images manually as a nested list) image file names must have this substring together with an identifier for the specific image sub group separated by “_” on each site from the rest of the file name auto_image_sub_param must only be ONCE in each file name! e.g. if you want to group various images for a panel by the cell from which they originate and each image file name somewhere contains “_cellXXXX_” where each X is some digit then auto_image_sub_param should be “cell” to catch the right group

  • make_image_size_equal – List. Allows for adding px to images in one dimension (“height” or “width”) to make the size of images in that dimension equal. list must have at least two values. The first value must be “height” or “width” the second value defines at which site pxs are added “right” or “left” for “width” OR “bottom” or “top” for “height” The third value in the list is optional and defines which values will be added The default value to be added is 0

  • auto_enlarge – Boolean; Whether images should be enlarged automatically to fill up grid into rectangle “focus”, “show_focus_in”, the first element in “order_of_categories” and “enlarged_image_site” can determine how the enlarged images will be shown (where they will be displayed and how much they will consequently be enlarged to fill up the image grid)

  • enlarged_image_site – Site at which the enlarged image should be shown (“left”, “right”, “top” or “bottom” possible)

  • simple_remapping – Whether only the image with the identity should be increased in size

  • channels_to_show_first_nonzoomed_timeframe – If a zoom is defined, should the first frame of each channel be always shown (as overview)

  • show_only_zoom – Potentially apart from overview image, dont show any non zoom pictures

  • force_show_non_zoom_channels – Force to show channels that were not zoomed independent of other settings

  • show_non_zoom_channels – show channels that were not zoomed independent of other settings

  • show_zoom_mark_on_all_channels – Whether rectangle with number of zoom should be shown on top of all channels otherwise they will only be shown on overview

  • position_zoom_nb – position at which the zoom number shouldbe shown in the zoomed image

  • show_single_zoom_numbers – Show zoom number in image and at zoom rectangle in overview image, even if there is just one zoomed area

  • show_zoom_number_in_image – Add zoom number to edge of zoomed image

  • zoom_nb_rows – List of rows in image grid in which zoom numbers will be added

  • zoom_nb_columns – List of columns in image grid in which zoom numbers will be added

  • line_width_zoom_rectangle – Line width in pt of zoom rectangle added to overview iamge

  • zoom_nb_font_size_overview – font size of zoom number in overview image

  • zoom_nb_color – Color of zoom number text on images

  • zoom_nb_padding – Padding of zoom number text to edges of image

  • zoom_nb_font_size – font size of zoom number in zoom image

  • zoom_nb_frames – List with ints or int, Index of frames where zoom nb should be shown in zoom For each int will use the Xth frame (e.g. if frame 5,10,20 will be shown and zoom_nb_frames is [0,1] then the zoom_nb will be shown in the first and second frame (5, 10)

  • repositioning_map – join specific images together with another dimension (by remapping the identity) e.g. join one image from a channel with the images of another channel supply a dict where the key is a tuple corresponding to the images that should be remapped (e.g. (“channel”,1,”zoom”,0)) the value should be a tuple that identifies the group that the images should be joined to uniquely the value tuple should correspond to images that only differ in one category (e.g. frame) the images will be joined in this category differing (like being added as additional frame points in this example) if “image” is not part of the value tuple then the images will be remapped on the same image

  • additional_padding – Multiply padding by factor to separate elements within one category dict where key is the category and value is the factor

  • show_axis_grid – Show axis grid on top of image (major ticks for x and y axis)

  • use_same_LUTs – Should the ranges from the first image in each chanel be applied to all images

  • replace_nan_with – float, Replace nan in images with value

  • cmaps – string or list of strings corresponding to matplotlib colormaps; each entry in list corresponds to one channel in same order

  • composite_cmaps –

    list of strings corresponding to matplotlib colors for composite channel (only if composite is defined in ‘channels’). Order of cmaps corresponds to order of channels in ImageJ, changes in order in the ‘channels’ parameter do not change the order of composite_cmaps.

    Will create cmap for each channel from black/white (depending on ‘black_composite_background’ parameter to color.)

  • black_composite_background – Whether the background (image below image range) of the composite should be black, if False, background is white

  • replace_nan_with – With what values to replace nan values with

  • sub_padding_factor – Multiple of figure_panel padding that is used for padding in image grid