- static grdhisteq.compute_bins(grid, *, output_type='pandas', outfile=None, divisions=None, quadratic=None, verbose=None, region=None, header=None)
Perform histogram equalization for a grid.
Histogram equalization provides a way to highlight data that has most values clustered in a small portion of the dynamic range, such as a grid of flat topography with a mountain in the middle. Ordinary gray shading of this grid (using
pygmt.Figure.grdview) with a linear mapping from topography to graytone will result in most of the image being very dark gray, with the mountain being almost white.
pygmt.grdhisteq.compute_binscan provide a list of data values that divide the data range into divisions which have an equal area in the image [Default is 16 if
divisionsis not set]. The
pandas.DataFrameor ASCII file output can be used to make a colormap with
pygmt.makecptand an image with
pygmt.Figure.grdimagethat has all levels of gray occurring equally.
Full option list at https://docs.generic-mapping-tools.org/latest/grdhisteq.html
output_type (str) –
Determine the format the xyz data will be returned in [Default is
divisions (int) – Set the number of divisions of the data range.
quadratic (bool) – Perform quadratic equalization [Default is linear].
Select verbosity level [Default is w], which modulates the messages written to stderr. Choose among 7 levels of verbosity:
q - Quiet, not even fatal error messages are produced
e - Error messages only
w - Warnings [Default]
t - Timings (report runtimes for time-intensive algorithms)
i - Informational messages (same as
c - Compatibility warnings
d - Debugging messages
header (str) –
[i|o][n][+c][+d][+msegheader][+rremark][+ttitle]. Specify that input and/or output file(s) have n header records [Default is 0]. Prepend i if only the primary input should have header records. Prepend o to control the writing of header records, with the following modifiers supported:
+d to remove existing header records.
+c to add a header comment with column names to the output [Default is no column names].
+m to add a segment header segheader to the output after the header block [Default is no segment header].
+r to add a remark comment to the output [Default is no comment]. The remark string may contain \n to indicate line-breaks.
+t to add a title comment to the output [Default is no title]. The title string may contain \n to indicate line-breaks.
Blank lines and lines starting with # are always skipped.
ret (pandas.DataFrame or numpy.ndarray or None) – Return type depends on
>>> import pygmt >>> # Load a grid of @earth_relief_30m data, with a longitude range of >>> # 10°E to 30°E, and a latitude range of 15°N to 25°N >>> grid = pygmt.datasets.load_earth_relief( ... resolution="30m", region=[10, 30, 15, 25] ... ) >>> # Find elevation intervals that split the data range into 5 >>> # divisions, each of which have an equal area in the original grid. >>> bins = pygmt.grdhisteq.compute_bins(grid=grid, divisions=5) >>> print(bins) start stop bin_id 0 170.0 389.0 1 389.0 470.5 2 470.5 571.0 3 571.0 705.0 4 705.0 2275.5
This method does a weighted histogram equalization for geographic grids to account for node area varying with latitude.