"""
grd2cpt - Create a CPT from a grid file.
"""
from pygmt.clib import Session
from pygmt.exceptions import GMTInvalidInput
from pygmt.helpers import build_arg_list, fmt_docstring, kwargs_to_strings, use_alias
__doctest_skip__ = ["grd2cpt"]
[docs]
@fmt_docstring
@use_alias(
A="transparency",
C="cmap",
D="background",
F="color_model",
E="nlevels",
G="truncate",
H="output",
I="reverse",
L="limit",
M="overrule_bg",
N="no_bg",
Q="log",
R="region",
T="series",
V="verbose",
W="categorical",
Ww="cyclic",
Z="continuous",
)
@kwargs_to_strings(G="sequence", L="sequence", R="sequence", T="sequence")
def grd2cpt(grid, **kwargs):
r"""
Make GMT color palette tables from a grid file.
This function will help you to make static color palette tables (CPTs).
By default, the CPT will be saved as the current CPT of the session,
figure, subplot, panel, or inset depending on which level
:func:`pygmt.grd2cpt` is called (for details on how GMT modern mode
maintains different levels of colormaps please see
:gmt-docs:`reference/features.html#gmt-modern-mode-hierarchical-levels`).
You can use ``output`` to save the CPT to a file. The CPT is based on an
existing dynamic master CPT of your choice, and the mapping from data value
to colors is through the data's cumulative distribution function (CDF), so
that the colors are histogram equalized. Thus if the grid(s) and the
resulting CPT are used in :meth:`pygmt.Figure.grdimage` with a linear
projection, the colors will be uniformly distributed in area on the plot.
Let z be the data values in the grid. Define CDF(Z) = (# of z < Z) / (# of
z in grid). (NaNs are ignored). These z-values are then normalized to the
master CPT and colors are sampled at the desired intervals.
The CPT includes three additional colors beyond the range of z-values.
These are the background color (B) assigned to values lower than the lowest
*z*-value, the foreground color (F) assigned to values higher than the
highest *z*-value, and the NaN color (N) painted wherever values are
undefined. For color tables beyond the standard GMT offerings, visit
`cpt-city <http://soliton.vm.bytemark.co.uk/pub/cpt-city/>`_ and
`Scientific Colour-Maps <http://www.fabiocrameri.ch/colourmaps.php>`_.
If the master CPT includes B, F, and N entries, these will be copied into
the new master file. If not, the parameters :gmt-term:`COLOR_BACKGROUND`,
:gmt-term:`COLOR_FOREGROUND`, and :gmt-term:`COLOR_NAN` from the
:gmt-docs:`gmt.conf <gmt.conf>` file will be used. This default behavior
can be overruled using the parameters ``background``, ``overrule_bg``
or ``no_bg``.
The color model (RGB, HSV or CMYK) of the palette created by
:func:`pygmt.grd2cpt` will be the same as specified in the header of the
master CPT. When there is no :gmt-term:`COLOR_MODEL` entry in the master
CPT, the :gmt-term:`COLOR_MODEL` specified in the
:gmt-docs:`gmt.conf <gmt.conf>` file or the ``color_model`` parameter
will be used.
Full option list at :gmt-docs:`grd2cpt.html`
{aliases}
Parameters
----------
{grid}
transparency : int or float or str
Set a constant level of transparency (0-100) for all color slices.
Append **+a** to also affect the foreground, background, and NaN
colors [Default is no transparency, i.e., ``0`` (opaque)].
cmap : str
Select the master color palette table (CPT) to use in the
interpolation. Full list of built-in color palette tables can be found
at :gmt-docs:`reference/cpts.html#built-in-color-palette-tables-cpt`.
background : bool or str
Select the back- and foreground colors to match the colors for lowest
and highest *z*-values in the output CPT [Default (``background=True``
or ``background="o"``) uses the colors specified in the master file, or
those defined by the parameters :gmt-term:`COLOR_BACKGROUND`,
:gmt-term:`COLOR_FOREGROUND`, and :gmt-term:`COLOR_NAN`]. Use
``background="i"`` to match the colors for the lowest and highest
values in the input (instead of the output) CPT.
color_model : str
[**R**\|\ **r**\|\ **h**\|\ **c**]\
[**+c**\ [*label*\|\ *start*\ [**-**]]].
Force output CPT to be written with r/g/b codes, gray-scale values or
color name (**R**, default) or r/g/b codes only (**r**), or h-s-v codes
(**h**), or c/m/y/k codes (**c**). Optionally or alternatively, append
**+c** to write discrete palettes in categorical format. If *label* is
appended then we create labels for each category to be used when the
CPT is plotted. The *label* may be a comma-separated list of category
names (you can skip a category by not giving a name), or give
*start*, where we automatically build monotonically increasing
labels from *start* (a single letter or an integer). Additionally
append **-** to build ranges *start*-*start+1* as labels instead.
nlevels : bool, int, or str
Set to ``True`` to create a linear color table by using the grid
z-range as the new limits in the CPT. Alternatively, set *nlevels*
to resample the color table into *nlevels* equidistant slices.
series : list or str
[*min/max/inc*\ [**+b**\|\ **l**\|\ **n**\]|\ *file*\|\ *list*\].
Define the range of the new CPT by giving the lowest and highest
z-value (and optionally an interval). If this is not given, the
existing range in the master CPT will be used intact. The values
produced defines the color slice boundaries. If **+n** is used it
refers to the number of such boundaries and not the number of slices.
For details on array creation, see
:gmt-docs:`makecpt.html#generate-1d-array`.
truncate : list or str
*zlow/zhigh*.
Truncate the incoming CPT so that the lowest and highest z-levels are
to *zlow* and *zhigh*. If one of these equal NaN then we leave that
end of the CPT alone. The truncation takes place before any resampling.
See also :gmt-docs:`reference/features.html#manipulating-cpts`.
output : str
Optional. The file name with extension .cpt to store the generated CPT
file. If not given or ``False`` [Default], saves the CPT as the current
CPT of the session, figure, subplot, panel, or inset depending on which
level :func:`pygmt.grd2cpt` is called.
reverse : str
Set this to ``True`` or **c** [Default] to reverse the sense of color
progression in the master CPT. Set this to **z** to reverse the sign
of z-values in the color table. Note that this change of z-direction
happens before ``truncate`` and ``series`` values are used so the
latter must be compatible with the changed z-range. See also
:gmt-docs:`reference/features.html#manipulating-cpts`.
overrule_bg : str
Overrule background, foreground, and NaN colors specified in the master
CPT with the values of the parameters :gmt-term:`COLOR_BACKGROUND`,
:gmt-term:`COLOR_FOREGROUND`, and :gmt-term:`COLOR_NAN` specified in
the :gmt-docs:`gmt.conf <gmt.conf>` file. When combined with
``background``, only :gmt-term:`COLOR_NAN` is considered.
no_bg : bool
Do not write out the background, foreground, and NaN-color fields
[Default will write them, i.e. ``no_bg=False``].
log : bool
For logarithmic interpolation scheme with input given as logarithms.
Expects input z-values provided via ``series`` to be log10(*z*),
assigns colors, and writes out *z*.
continuous : bool
Force a continuous CPT when building from a list of colors and a list
of z-values [Default is None, i.e. discrete values].
categorical : bool
Do not interpolate the input color table but pick the output colors
starting at the beginning of the color table, until colors for all
intervals are assigned. This is particularly useful in combination with
a categorical color table, like ``cmap="categorical"``.
cyclic : bool
Produce a wrapped (cyclic) color table that endlessly repeats its
range. Note that ``cyclic=True`` cannot be set together with
``categorical=True``.
{verbose}
Example
-------
>>> import pygmt
>>> # load the 30 arc-minutes grid with "gridline" registration
>>> grid = pygmt.datasets.load_earth_relief("30m", registration="gridline")
>>> # create a plot
>>> fig = pygmt.Figure()
>>> # create a CPT from the grid object with grd2cpt
>>> pygmt.grd2cpt(grid=grid)
>>> # plot the grid object, the CPT will be automatically used
>>> fig.grdimage(grid=grid)
>>> # show the plot
>>> fig.show()
"""
if kwargs.get("W") is not None and kwargs.get("Ww") is not None:
raise GMTInvalidInput("Set only categorical or cyclic to True, not both.")
with Session() as lib:
with lib.virtualfile_in(check_kind="raster", data=grid) as vingrd:
if kwargs.get("H") is None: # if no output is set
arg_str = build_arg_list(kwargs, infile=vingrd)
else: # if output is set
outfile, kwargs["H"] = kwargs["H"], True
if not outfile or not isinstance(outfile, str):
raise GMTInvalidInput("'output' should be a proper file name.")
arg_str = build_arg_list(kwargs, infile=vingrd, outfile=outfile)
lib.call_module(module="grd2cpt", args=arg_str)