def generateFingerprint(molecule, numInts=32, pathLength=7):
"""(molecule, numInts=32)->Fingerprint
given a molecule and the number of integers to use to generate
the fingerprint, return the fingerprint of the molecule)"""
paths = LinearPaths.generatePaths(molecule, maxdepth=pathLength)
fp = Fingerprint.Fingerprint(numIntegers=numInts)
for path in paths:
fp.addPath(path)
return fp
def add_chords(self):
for chord in Chord.all():
#if fingerprint exists, get current fingerprint to modify
if self.fingerprint(chord.id):
fingerprint = self.fingerprints[chord.id]
fingerprint.add_chord(chord)
#else create new fingerprint
else:
self.fingerprints[chord.id] = Fingerprint(chord.stamp)
self.fingerprints[chord.id].add_chord(chord)
def add_scales(self):
for scale in Scale.all():
#if fingerprint exists, get current fingerprint to modify
#print(scale.stamp)
if self.fingerprint(scale.id):
fingerprint = self.fingerprints[scale.id]
fingerprint.add_scale(scale)
#else create new fingerprint
else:
self.fingerprints[scale.id] = Fingerprint(scale.stamp)
self.fingerprints[scale.id].add_scale(scale)
# RunTests.py
# Run the Fingerprint program on the test cases.
import os
import csv
import Fingerprint
# Instantiate the Fingerprint class.
f = Fingerprint.Fingerprint()
# Loop over all the test cases in the test directory.
test_directory = '../tests'
for test_file in os.listdir(test_directory):
if (test_file.endswith('.dat')):
#print (test_file)
# Evaluate the full path to the file.
test_file_path = test_directory + '/' + test_file
#print(test_file_path)
# Open the test file
with open(test_file_path, 'r') as tf:
reader = csv.reader(tf)
fp_data = list(reader)
# Process the input and identify the grouping.
#print(fp_data[0])
#print(fp_data[1])
# Get the expected result.
exp_result = [int(x) for x in fp_data[1]]
