Visualization

DASPy uses the Section class method/function plot to plot images.

Call Class Method

Plot and show image：

>>> from daspy import read
>>> sec = read()
>>> sec.plot()

Adding savefig to save figure as specified filename, and dpi to set the resolution of the figure in dots-per-inch:

>>> sec.plot(savefig='waveform.png', dpi=400)

When drawing frequency domain graphs, you can set the kwargs_pro parameter to specify how the spectrum is plotted:

>>> sec.plot(obj='fk', kwargs_pro=dict(taper=(0.02, 0.05), nfft=(1024, 8192))) # set the coefficient of 2D cosine taper to (0.02,0.05), output points of 2DFFT to (1024, 8192)

Plot in Matplotlib.axes.Axes:

>>> import matplotlib.pyplot as plt
>>> fig, ax = plt.subplots(2, 1, figsize=(6,6))
>>> sec.plot(ax=ax[0], obj='waveform', xmode='channel', tmode='origin', xlabel=False, transpose=True, vmax=0.05) # set the spatial axis to the channel number, the time axis to the time after the event occurred, do not draw the x-axis label, invert the default x/y axis, and set the data range to -0.05~0.05
>>> sec.plot(ax=ax[1], obj='spectrogram', tmode='origin', kwargs_pro=dict(noverlap=156)) # overlap between two windows is 156 points
>>> plt.tight_layout()
>>> plt.show()

Call the function

First calculate the spectrum, perform other calculations on the output, and then use the daspy.basic_tools.visualization.plot function to plot:

>>> import numpy as np
>>> from daspy.basic_tools.visualization import plot
>>> spec, f = sec.spectrum()
>>> spec = 10 * np.log10(abs(spec) ** 2) # convert the spectrum to units of decibels (dB), using 1 as the reference value
>>> plot(spec, obj='spectrum', f=f, xmode='channel') # set the spatial axis to the channel number, the time axis to the time after the event occurred, and invert the default x/y axis