nenupy.io.tf_utils.plot_dynamic_spectrum

nenupy.io.tf_utils.plot_dynamic_spectrum(data, time, frequency, fig=None, ax=None, figsize=(10, 5), dpi=200, xlabel=None, ylabel=None, clabel=None, title=None, cmap='YlGnBu_r', norm='linear', vmin=None, vmax=None)[source]

Plot a dynamic spectrum. This function uses pcolormesh() in the background.

Parameters:

  • data (ndarray) – Two-dimensional array, shaped like (time, frequency).

  • time (Time) – One-dimensional time array.

  • frequency (Quantity) – One-dimensional frequency array, if ylabel is None, the unit is automatically used to describe the axis.

  • fig (Figure, optional) – Matplotlib figure if already existing, by default None

  • ax (Axes, optional) – Matplotlib ax if already existing, by default None

  • figsize (Tuple[int, int], optional) – Size of the figure in inches, by default (10, 5)

  • dpi (int, optional) – Dots per inch (best quality is around 300), by default 200

  • xlabel (str, optional) – Label of the x-axis (time), by default None (i.e., generic label)

  • ylabel (str, optional) – Label of the y-axis (time), by default None (i.e., generic label)

  • clabel (str, optional) – Label of the colorbar, by default None (i.e., empty)

  • title (str, optional) – Title of the graph, by default None (i.e., empty)

  • cmap (str, optional) – Colormap (see matplotlib colormaps), by default “YlGnBu_r”

  • norm (str, optional) – Normalization of the colorbar (‘linear’ or ‘log’), by default “linear”

  • vmin (float, optional) – Minimal data value to plot, by default None

  • vmax (float, optional) – Maximal data value to plot, by default None

Returns:

The figure and ax objects

Return type:

Tuple[Figure, Axes]

Raises:

ValueError – Raised if norm does not match supported value.

Examples

>>> from nenupy.io.tf_utils import plot_dynamic_spectrum
>>> from astropy.time import Time, TimeDelta
>>> import astropy.units as u
>>> import matplotlib.pyplot as plt
>>> import numpy as np

>>> n_times = 20
>>> dt = TimeDelta(1800, format="sec")
>>> n_freqs = 10
>>> df = 1 * u.MHz
>>> fig, ax = plot_dynamic_spectrum(
        data=np.arange(n_times * n_freqs).reshape((n_times, n_freqs)),
        time=Time("2024-01-01 00:00:00") + np.arange(n_times) * dt,
        frequency=50 * u.MHz + np.arange(n_freqs) * df,
        clabel="my color bar",
        norm="linear",
    )
../_images/plot_dynamic_spectrum.png

Warning

Do not forget to release the matplotlib cache (using close()), either after calling several times this method, and/or once you are done with your desired plot. Otherwise you may suffer from significant performance issues as the plots stacks in the memory…

>>> plt.close(fig)

or

>>> plt.close("all")