In [1]:
import numpy as np
import matplotlib.pyplot as plt
import sys
#Add a new path with needed .py files
sys.path.insert(0, 'C:\Users\Dominik\Documents\GitRep\kt-2015-DSPHandsOn\MedianFilter\Python')
import functions
import gitInformation
In [2]:
gitInformation.printInformation()
In [3]:
% matplotlib inline
Testing with more samples ( now 1024, before 128)
In [5]:
fig = plt.figure()
for i in range (0, 40):
functions.ErrorPlotWave(i, 127,1024)
With more samples the error rate at wave number 16 and 32 is no longer lower then expected.
In [7]:
fig = plt.figure(1, figsize=(15, 3))
functions.medianSinPlot(15, 127)
plt.title('Wave number 15')
fig = plt.figure(2, figsize=(15, 3))
functions.medianSinPlot(16, 127)
plt.title('Wave number 16')
fig = plt.figure(3, figsize=(15, 3))
functions.medianSinPlot(17, 127)
plt.title('Wave number 17')
Out[7]:
In [7]:
fig = plt.figure(1, figsize=(15, 3))
functions.medianSinPlot(31, 127,1024)
plt.title('Wave number 31')
fig = plt.figure(2, figsize=(15, 3))
functions.medianSinPlot(32, 127,1024)
plt.title('Wave number 32')
fig = plt.figure(3, figsize=(15, 3))
functions.medianSinPlot(33, 127,1024)
plt.title('Wave number 33')
Out[7]: