basic_dsp 0.7.0

Digital signal processing based on real or complex vectors in time or frequency domain. Vectors come with basic arithmetic, convolution, Fourier transformation and interpolation operations. The vectors are optimized for sizes of a couple of thousand elements or more. The same operations are provdided for matrices. For complete matrix algebra this lib is intended to be used in combination with other matrix libs. Please refer to the documentation for more information about this.
Documentation 
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from __future__ import unicode_literals
import matplotlib.pyplot as plt
import fileinput
import sys

#
# Displays one ore more CSV files in a graph. Intended to be used
# with the `bench_tables.rs` example.
#
# Accepts data from STDIN and additional files can be passed in as
# command line arguments. A use case would be to display the current
# benchmark results in STDIN and a reference benchmark as a file.
#

def process_file(ax, filename, fileinput):
	first_line = True
	if filename == "STDIN":
		linestyle = "-"
	else:
		linestyle = "--"

	x_axis = [0, 1]
	for line in fileinput:
		cells = line.strip().split(",") # Assume CSV string in English locale
		title = filename + " " + cells[0].strip()
		end = len(cells)
		# Ignore last cell if it's empty. That allows a trailing "," in
		# the CSV string
		if not cells[-1].strip():
			end = end - 1
		values = map(int, cells[1:end])
		if first_line:
			x_axis = values
			first_line = False
		else:
			line, = ax.plot(x_axis, values, linestyle, label=title)

fig, ax = plt.subplots()
process_file(ax, "STDIN", fileinput.input("-", openhook=fileinput.hook_encoded("utf16")))
for filename in sys.argv[1:]:
	with open(filename, "r") as filehandle:
		process_file(ax, filename, fileinput.input(filename, openhook=fileinput.hook_encoded("utf16")))

ax.legend(loc='lower right')
plt.show()