# pylint: disable-all
import os, sys, inspect
CURRENT_DIR = os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe())))
PARENT_DIR = os.path.dirname(CURRENT_DIR)
sys.path.insert(0, PARENT_DIR)
import matplotlib.animation as animation
from filterbank.header import read_header
from filterbank.filterbank import Filterbank
from plot import waterfall
import pylab as pyl
from plot.plot import next_power_of_2
fb = Filterbank(filename='./pspm32.fil')
wf = waterfall.Waterfall(fb=fb, fig=pyl.figure(), mode="stream")
fig, update, frames, repeat = wf.animated_plotter()
ani = animation.FuncAnimation(fig, update, frames=frames, repeat=repeat)
pyl.show()
"""
Example of clipping RFI from filterbank data
"""
# pylint: disable-all
import os,sys,inspect
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(currentdir)
sys.path.insert(0,parentdir)
import matplotlib.pyplot as plt
from timeseries.timeseries import Timeseries
from filterbank.filterbank import Filterbank
from plot.static_waterfall import waterfall_plot
from clipping.clipping import clipping
# init filterbank object
fil = Filterbank(filename='./pspm32.fil', read_all=True)
# retrieve channels and samples from filterbank
freqs, samples = fil.select_data()
print(freqs.shape, samples.shape)
# visualize data before clipping
time_series = Timeseries()
time_series.from_filterbank(fil)
plt.subplot(2,1,1)
plt.plot(time_series.timeseries)
# perform clipping on the filterbank data
# pylint: disable-all
import os, sys, inspect
CURRENT_DIR = os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe())))
PARENT_DIR = os.path.dirname(CURRENT_DIR)
sys.path.insert(0, PARENT_DIR)
import matplotlib.animation as animation
from filterbank.header import read_header
from filterbank.filterbank import Filterbank
from plot import waterfall
import pylab as pyl
from plot.plot import next_power_of_2
fb = Filterbank(filename='./pspm32.fil', read_all=True)
wf = waterfall.Waterfall(filter_bank=fb, fig=pyl.figure(), mode="discrete")
img = wf.get_image()
pyl.show(img)
import os
import sys
import inspect
# Volkswagened this example as it is just an example for educational purposes, no production code.
# pylint: disable-all
CURRENT_DIR = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
PARENT_DIR = os.path.dirname(CURRENT_DIR)
sys.path.insert(0, PARENT_DIR)
from timeseries.timeseries import Timeseries
from filterbank.filterbank import Filterbank
import matplotlib.pyplot as plt
# Initialize filterbank based on the pspm32.fil file. This filterbank object can then be used for other actions.
fb = Filterbank("./pspm32.fil")
fb.read_filterbank()
# Creating timeseries object from filterbank file which is initialized above.
time_series = Timeseries().from_filterbank(fb)
# Using the downsample method from the timeseries object.
decimated_tv = time_series.downsample(3)
# Plotting the downsampled result.
plt.plot(decimated_tv)
plt.show()
import sys
import inspect
import numpy as np
import matplotlib.pyplot as plt
CURRENT_DIR = os.path.dirname(
os.path.abspath(inspect.getfile(inspect.currentframe())))
PARENT_DIR = os.path.dirname(CURRENT_DIR)
sys.path.insert(0, PARENT_DIR)
from plot import opsd
from filterbank.header import read_header
from filterbank.filterbank import Filterbank
# Instatiate the filterbank reader and point to the filterbank file
fb = Filterbank(filename='./pspm32.fil', read_all=True)
# read the data in the filterbank file
f, samples = fb.select_data()
# Assign the center frequency with the data in the header
center_freq = fb.header[b'center_freq']
print(samples.shape)
# Get the powerlevels and the frequencies
print(samples[0])
power_levels, freqs, _ = opsd(samples[0],
nfft=128,
sample_rate=80,
sides='twosided')
from filterbank.generate import generate_file
header = {
b'source_name': b'P: 80.0000 ms, DM: 200.000',
b'machine_id': 10,
b'telescope_id': 4,
b'data_type': 1,
b'fch1': 400,
b'foff': -0.062,
b'nchans': 128,
b'tstart': 6000.0,
b'tsamp': 8e-05,
b'nifs': 1,
b'nbits': 8
}
filename = './examples/pspm.fil'
# generate a fake filterbank file
generate_file(filename, header)
# read fake filterbank file
fil = Filterbank(filename, read_all=True)
# select data from fitlerbank
_, data = fil.select_data()
# plot one sample
plt.plot(data[0])
plt.show()
from filterbank.filterbank import Filterbank
fil = Filterbank('data/voyager_f1032192_t300_v2.fil')