Statistical Power Plots

This function will calculate and plot a statistic of the lag-0 power of each record as a function of time.

This function applies the statistical function (ex. numpy.mean) to the pwr0 vector (lag-0 power for each range) for each record before plotting the results from all records chronologically.

This code can be used to study background interference in rawacf data when the radar has been operating in a receive-only mode such as "politescan" (cpid -3380), or during periods without any obvious coherent scatter returns from any range.

Basic code to plot lag 0, will plot the mean of pwr0 for all frequencies at beam 0, from a RAWACF file would look like:

import matplotlib.pyplot as plt
import pydarn

file = "20180101.0000.01.rkn.rawacf"
sdarn_read = pydarn.SuperDARNRead(file)
rawacf_data = sdarn_read.read_rawacf()

pydarn.Power.plot_pwr0_statistic(rawacf_data)
plt.show()

You also have access to numerous plotting options:

Parameter	Action
beam_num=0	beam number to plot
min_frequency	minimum Frequency (inclusive) to plot
max_frequency	maximum Frequency (inclusive) to plot
split_frequency	specific frequency to look for or split between
statistical_method=np.mean	the statistical calculation to apply to the pwr0 array

If you want display only one frequency set min_frequency = max_frequency:

import pydarn
import matplotlib.pyplot as plt 

rawacf_file = '20201001.0200.00.sas.0.rawacf.hdf5'
rawacf_data = pydarn.SuperDARNRead().read_borealis(rawacf_file)
pydarn.Power.plot_pwr0_statistic(rawacf_data, beam_num=3, min_frequency=10500, max_frequency=10500)
plt.show()

To compare data above and below a specific frequency, you can compare by using the split_frequency option:

import pydarn
import matplotlib.pyplot as plt 

rawacf_file = 'data/20180404.0601.00.lyr.rawacf'
rawacf_data = pydarn.SuperDARNRead(rawacf_file).read_rawacf()
pydarn.Power.plot_pwr0_statistic(rawacf_data, beam_num=15, split_frequency=11000, max_frequency=12000)
plt.show()