nenupy.io.tf_utils.ReducedSpectraSlice

class nenupy.io.tf_utils.ReducedSpectraSlice(time, frequency, polarization, data)[source]

Bases: object

__init__(time, frequency, polarization, data)[source]

Methods

`__init__`(time, frequency, polarization, data)
`multi_plot`(nrows, ncols[, fig, figsize])	_summary_
`plot`([polarization])	_summary_

Attributes

shape

_summary_

multi_plot(nrows, ncols, fig=None, figsize=None, **kwargs)[source]

_summary_

Parameters:

nrows (int) – _description_
ncols (int) – _description_
fig (mpl.figure.Figure, optional) – _description_, by default None
figsize (Tuple[int, int], optional) – _description_, by default None

Example

>>> import numpy as np
>>> from astropy.time import Time, TimeDelta
>>> import astropy.units as u
>>> from nenupy.io.tf_utils import ReducedSpectraSlice

>>> pols = np.array(["I", "Q", "U", "V/I"])
>>> nt, nf, no = (10, 5, pols.size)
>>> data = (np.arange(1, nt + 1)[:, None] * np.arange(1, nf + 1)[None, :])[:, :, None] * 2**np.arange(no)[None, None, :]
>>> dd = ReducedSpectraSlice(
        time=Time.now() + np.arange(nt) * TimeDelta(1800, format="sec"),
        frequency=np.arange(nf) * u.MHz,
        polarization=pols,
        data=data
    )

>>> f, axes = dd[2:5, ...].multi_plot(2, 2, figsize=(15, 7), norm="linear", vmin=0, vmax=200)

plot(polarization=None, **kwargs)[source]

_summary_

Parameters:: polarization (str, optional) – _description_, by default None
Returns:: _description_
Return type:: _type_