show_camera

lstchain.visualization.bokeh.show_camera(content, camgeom, pad_width, label, titles=None, showlog=True, display_range=None, content_lowlim=None, content_upplim=None)

Parameters:

content: pixel-wise quantity to be plotted, ndarray with shape (N,

number_of_pixels) where N is the number of different sets of pixel

values, for example N different data runs or whatever. The shape can also

be just (number_of_pixels), in case a single camera display is to be shown

geom: camera geometry

pad_width: width in pixels of each of the 3 pads in the plot

pad_height: height in pixels of each of the 3 pads in the plot

label: string to label the quantity which is displayed, the same for the N

sets of pixels inside “content”

titles: list of N strings, with the title specific to each of the sets

of pixel values to be displayed: for example, indicating run numbers

content_lowlim: scalar or ndarray of shape(N, number_of_pixels),

same as content: lowest value of “content” which is considered healthy,

below which a message will be written out

content_upplim: highest value considered healthy, same as above

display_range: range of “content” to be displayed

Returns:

[slider, p1, range_slider, p2, p3]: three bokeh figures, intended for

showing them on the same row, and two sliders, one for the run numbers (

or whatever “sets” of data we are displaying) and the other for the

z-range of the plots.

p1 is the camera display (with “content” in linear & logarithmic scale)

p2: content vs. pixel

p3: histogram of content (with one entry per pixel)