This is a plotting method used to examine the distribution of signal within an image.
plantcv.visualize.histogram(gray_img, mask=None, bins=256, color='red', title=None)
returns hist_header, hist_data, fig_hist
- gray_img - Grayscale image data, the original image for analysis.
- mask - Optional binary mask made from selected contours (default mask=None)
- bins - Number of class to divide spectrum into (default bins=256)
- color - The color of the line plot in the histogram (default color='red'). Users can input and color that is accepted by plotnine ggplot.
- title - The title for the histogram (default title=None)
Context: - Examine the distribution of the signal, this can help select a value for binary thresholding.
- Example use:
from plantcv import plantcv as pcv # Examine signal distribution within an image # prints out an image histogram of signal within image header, hist_data, hist_figure = pcv.visualize.histogram(gray_img, mask=mask, bins=256, color='red', title=None)
Histogram of signal intensity