""" Plotting routine for AscendingGrid """
import numpy
import matplotlib
import pyarts3 as pyarts
import numpy as np
from .common import default_fig_ax, select_flat_ax
__all__ = [
'plot',
]
[docs]
def plot(data: pyarts.arts.AscendingGrid,
*,
fig: matplotlib.figure.Figure | None = None,
ax: matplotlib.axes.Axes | list[matplotlib.axes.Axes] | numpy.ndarray[matplotlib.axes.Axes] | None = None,
**kwargs) -> tuple[matplotlib.figure.Figure, matplotlib.axes.Axes | list[matplotlib.axes.Axes] | numpy.ndarray[matplotlib.axes.Axes]]:
"""Plot an AscendingGrid as a scatter/line plot.
.. rubric:: Example
.. plot::
:include-source:
import pyarts3 as pyarts
import numpy as np
# Create a frequency grid
freqs = pyarts.arts.AscendingGrid(np.logspace(9, 12, 20))
pyarts.plots.AscendingGrid.plot(freqs)
Parameters
----------
data : ~pyarts3.arts.AscendingGrid
A sorted ascending grid of values
fig : ~matplotlib.figure.Figure, optional
The matplotlib figure to draw on. Defaults to None for new figure.
ax : ~matplotlib.axes.Axes | list[~matplotlib.axes.Axes] | ~numpy.ndarray[~matplotlib.axes.Axes] | None, optional
The matplotlib axes to draw on. Defaults to None for new axes.
**kwargs : keyword arguments
Additional keyword arguments to pass to the plotting functions.
Returns
-------
fig :
As input if input. Otherwise the created Figure.
ax :
As input if input. Otherwise the created Axes.
"""
fig, ax = default_fig_ax(fig, ax, 1, 1, fig_kwargs={
'figsize': (10, 6), 'constrained_layout': True})
indices = np.arange(len(data))
select_flat_ax(ax, 0).plot(indices, data, **kwargs)
return fig, ax