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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Test
Step1:  Testing with more samples ( now 1024, before 128)
Plots
Step2:  With more samples the error rate at wave number 16 and 32 is no longer lower then expected.
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Python Code:
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
gitInformation.printInformation()
 % matplotlib inline
Explanation: Test: Error of the median filter with different wave number, with higher sample rate (2015.10.14. DW)
End of explanation
fig = plt.figure()
for i in range (0, 40):
    functions.ErrorPlotWave1024(i, 128)
Explanation: Testing with more samples ( now 1024, before 128)
Plots
End of explanation
fig = plt.figure(1, figsize=(15, 3))
functions.medianSinPlot1024(15, 128)
plt.title('Wave number 15')
fig = plt.figure(2, figsize=(15, 3)) 
functions.medianSinPlot1024(16, 128)
plt.title('Wave number 16')
fig = plt.figure(3, figsize=(15, 3)) 
functions.medianSinPlot1024(17, 128)
plt.title('Wave number 17')
fig = plt.figure(1, figsize=(15, 3))
functions.medianSinPlot1024(31, 128)
plt.title('Wave number 31')
fig = plt.figure(2, figsize=(15, 3)) 
functions.medianSinPlot1024(32, 128)
plt.title('Wave number 32')
fig = plt.figure(3, figsize=(15, 3)) 
functions.medianSinPlot1024(33, 128)
plt.title('Wave number 33')
Explanation: With more samples the error rate at wave number 16 and 32 is no longer lower then expected.
End of explanation
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