OS X (Apple)

# DWT.py
#
# Basic Python 1D Haar DWT, Discrete Wavelet Transform, using internal default Python floating point maths only.
# Works on Python Versions 1.4.0 to 2.0.1 and 2.4.6, (for the AMIGA A1200), to 3.8.0rc1
# on other platforms without modification.
# Developed on OSX 10.12.x to 10.14.6, using Python Versions 2.6.x, 2.7.x, 3.5.2 and 3.8.0.
# Issued as CC0, Public Domain, B.walker, G0LCU, to https://www.unix.com first 12_03_2020.
#
# URL to check results against:
# https://www.unf.edu/~ddreibel/camp/wave8.html

# Integer values as floats used here for default DEMO 8 sample size.
# The 8 test samples; sample size must be a power of 2.
#
# DEMO 1:
# START:
# 56.0, 40.0, 8.0, 24.0, 48.0, 48.0, 40.0, 16.0
#
# STEPS IN BETWEEN:
# 48.0, 16.0, 48.0, 28.0, 8.0, -8.0, 0.0, 12.0
# 32.0, 38.0, 16.0, 10.0, 8.0, -8.0, 0.0, 12.0
#
# FINAL RESULT:
# 35.0, -3.0, 16.0, 10.0, 8.0, -8.0, 0.0, 12.0
# Works from Python 1.4.0 to Python 3.5.2.
#
# Learning reference here:
# https://www.math.aau.dk/digitalAssets/120/120646_r-2003-24.pdf
#
# LISTING=[56.0, 40.0, 8.0, 24.0, 48.0, 48.0, 40.0, 16.0]

# Transform creates genuine floating point values.
# DEMO 2:
# START:
# 6, 12, 15, 15, 14, 12, 120, 116
#
# FINAL RESULT:
# 38.75, -26.75, -3.0, -52.5, -3.0, 0.0, 1.0, 2.0
#
# LISTING=[6, 12, 15, 15, 14, 12, 120, 116]

# Basic transform.
# DEMO 3:
# START:
# 1, 2, 3, 4, 5, 6, 7, 8
#
# FINAL RESULT:
# 4.5, -2.0, -1.0, -1.0, -0.5, -0.5, -0.5, -0.5
#
# LISTING=[1, 2, 3, 4, 5, 6, 7, 8]

# Using padding of 0.0 for last three places.
# DEMO 4:
# START:
# 17.0, 3.0, 31.0, 213.0, 99.0, 0.0, 0.0, 0.0
#
# FINAL RESULT:
# 45.375, 20.625, -56.0, 24.75, 7.0, -91.0, 49.5, 0.0
#
LISTING=[17.0, 3.0, 31.0, 213.0, 99.0, 0.0, 0.0, 0.0]

print("Eight input values:")
print(LISTING)

# Haar 1D DWT function.
def DiscreteHaarWaveletTransform(DATA=[]):

    LENGTH=len(DATA)
    RESULT=[]
    while 1:
        TEMP=[0]*LENGTH

        for INDEX in range(0,LENGTH,2):
            MEAN_PAIR=(DATA[INDEX]+DATA[INDEX+1])/2.0
            DIFFERENCE=DATA[INDEX]-MEAN_PAIR
            TEMP[int(INDEX/2)]=MEAN_PAIR
            TEMP[int(LENGTH/2)+int(INDEX/2)]=DIFFERENCE

        DATA=TEMP
        RESULT=TEMP[int(LENGTH/2):]+RESULT
        LENGTH=int(LENGTH/2)

        if LENGTH==1:
            RESULT=TEMP[0:1]+RESULT
            return RESULT

# Obtain the results.
DWTDATA=DiscreteHaarWaveletTransform(LISTING)

print("DWT results:")
print(DWTDATA)