"""
Histogram - Create a histogram
"""
from pygmt.clib import Session
from pygmt.helpers import build_arg_string, fmt_docstring, kwargs_to_strings, use_alias
@fmt_docstring
@use_alias(
A="horizontal",
B="frame",
C="cmap",
D="annotate",
E="barwidth",
F="center",
G="fill",
J="projection",
L="extreme",
N="distribution",
Q="cumulative",
R="region",
S="stairs",
T="series",
V="verbose",
W="pen",
Z="histtype",
b="binary",
c="panel",
d="nodata",
e="find",
h="header",
i="incols",
l="label",
p="perspective",
t="transparency",
w="wrap",
)
@kwargs_to_strings(
R="sequence", T="sequence", c="sequence_comma", i="sequence_comma", p="sequence"
)
def histogram(self, data, **kwargs):
r"""
Plot Cartesian histograms.
Full option list at :gmt-docs:`histogram.html`
{aliases}
Parameters
----------
data : str, list, {table-like}
Pass in either a file name to an ASCII data table, a Python list, a 2-D
{table-classes}.
{projection}
{region}
{frame}
{cmap}
fill : str
Set color or pattern for filling bars [Default is no fill].
{pen}
{panel}
annotate : bool or str
[**+b**][**+f**\ *font*][**+o**\ *off*][**+r**].
Annotate each bar with the count it represents. Append any of the
following modifiers: Use **+b** to place the labels beneath the bars
instead of above; use **+f** to change to another font than the default
annotation font; use **+o** to change the offset between bar and
label [Default is ``"6p"``]; use **+r** to rotate the labels from
horizontal to vertical.
barwidth : float or str
*width*\ [**+o**\ *offset*].
Use an alternative histogram bar width than the default set via
``series``, and optionally shift all bars by an *offset*. Here
*width* is either an alternative width in data units, or the user may
append a valid plot dimension unit (**c**\|\ **i**\|\ **p**) for a
fixed dimension instead. Optionally, all bins may be shifted along the
axis by *offset*. As for *width*, it may be given in data units of
plot dimension units by appending the relevant unit.
center : bool
Center bin on each value. [Default is left edge].
distribution : bool, float, or str
[*mode*][**+p**\ *pen*].
Draw the equivalent normal distribution; append desired
*pen* [Default is ``"0.25p,black,solid"``].
The *mode* selects which central location and scale to use:
* 0 = mean and standard deviation [Default];
* 1 = median and L1 scale (1.4826 \* median absolute deviation; MAD);
* 2 = LMS (least median of squares) mode and scale.
cumulative : bool or str
[**r**].
Draw a cumulative histogram by passing ``True``. Use **r** to display
a reverse cumulative histogram.
extreme : str
**l**\|\ **h**\|\ **b**.
The modifiers specify the handling of extreme values that fall outside
the range set by ``series``. By default, these values are ignored.
Append **b** to let these values be included in the first or last
bins. To only include extreme values below first bin into the first
bin, use **l**, and to only include extreme values above the last bin
into that last bin, use **h**.
stairs : bool
Draw a stairs-step diagram which does not include the internal bars
of the default histogram.
horizontal : bool
Plot the histogram using horizontal bars instead of the
default vertical bars.
series : int, str, or list
[*min*\ /*max*\ /]\ *inc*\ [**+n**\ ].
Set the interval for the width of each bar in the histogram.
histtype : int or str
[*type*][**+w**].
Choose between 6 types of histograms:
* 0 = counts [Default]
* 1 = frequency_percent
* 2 = log (1.0 + count)
* 3 = log (1.0 + frequency_percent)
* 4 = log10 (1.0 + count)
* 5 = log10 (1.0 + frequency_percent).
To use weights provided as a second data column instead of pure counts,
append **+w**.
{verbose}
{binary}
{nodata}
{find}
{header}
{incols}
{label}
{perspective}
{transparency}
{wrap}
"""
kwargs = self._preprocess(**kwargs)
with Session() as lib:
file_context = lib.virtualfile_from_data(check_kind="vector", data=data)
with file_context as infile:
lib.call_module(
module="histogram", args=build_arg_string(kwargs, infile=infile)
)