p = "data/Letter-low"
ds = "Letter-low"
z = read_tud(p, ds, False)
import Visualization as v
G1 = z[0]["1"][0]
pos1 = t.get_pos(G1)
G2 = z[0]["9"][0]
pos2 = t.get_pos(G2)
v.cool_GIF(G1, pos1, G2, pos2, frames=720)
######################## Binary ShapeMatcher Models ###########################
matrices = [None, None, None, None] # For you to reference later
alienDict = read_sm("data/Shape-Matcher-models/ALIEN.xml")
t.rename_key(alienDict, oldKey="models/ALIEN/ALIEN", newKey="alien")
camelDict = read_sm("data/Shape-Matcher-models/camel.xml")
t.rename_key(camelDict, oldKey="models/camel/camel", newKey="camel")
eagleDict = read_sm("data/Shape-Matcher-models/eagle.xml")
t.rename_key(eagleDict, oldKey="models/eagle/eagle", newKey="eagle")
kangaDict = read_sm("data/Shape-Matcher-models/KANGAROO.xml")
t.rename_key(kangaDict, oldKey="models/KANGAROO/KANGAROO", newKey="kangaroo")
# see data/DataCleaning.py for how we picked outliers
biasedAliens = [
'alien67', 'alien0', 'alien1', 'alien2', 'alien4', 'alien5', 'alien6',
'alien9', 'alien16', 'alien18', 'alien19', 'alien27', 'alien28', 'alien30',
'alien31', 'alien32', 'alien33', 'alien34', 'alien36', 'alien37',
def read_ppm(DBname, ppmDir, ppmList=None, SMD=None):
if SMD == None:
SMD = '../images/ShapeMatcher'
print("Converting", ppmDir, "...")
with cd(SMD): # Directory finagling begins
with cd(ppmDir): # finagling x 2
OS = p.system()
if OS == 'Windows':
contents = cmd('dir')
elif OS in ['Darwin', 'Linux']:
contents = cmd('ls')
else:
s = sorry.format("Unknown Operating System")
print(s)
return None
if contents.returncode != 0:
s = sorry.format("Couldn't read the directory.")
print(s)
return None
# There is a built in ShapeMatcher commands that reads everything in a folder
# But I found it to be buggy at times
string = str(contents)
string = string[string.find(ppmDir) + 1:]
fileList = string.split(".ppm")
fileList = fileList[:-1]
# Need to work backwards from the end of the file name
# This is why file names can't have spaces
for i in range(len(fileList)):
file = None
j = -1
while j >= (-1 * len(fileList[i])):
if fileList[i][j] == " ":
break
j -= 1
j += 1
file = fileList[i][j + len(fileList[i]):]
file += ".ppm"
fileList[i] = file
# Now we have a list of all the files in the folder
# So we can make a database consisting of all of these files
# Start building the sm command for creating a database file
createDB = 'sm -doExtSimp 0 -c ' + DBname + '.db'
# Now add each of the files
for file in fileList:
createDB += " " + ppmDir + '/' + file
# Make a database of the graphs
cmd(createDB)
# Convert database to XML file
toXML = "sm -toXML " + DBname + ".xml " + DBname + ".db"
cmd(toXML)
print("----------")
g = read_sm(DBname + ".xml")
print("\t----------")
t.rename_key(g, list(g.keys())[0], DBname)
print("\t----------")
print("\nConversion complete. Returning NetworkX graph object.")
print("\nYour", DBname, "database and XML file should be in ", SMD)
return g
"""
Created on Tue Jul 7 19:36:23 2020
@author: Candace Todd
"""
# Script recording our data cleaning methodology
# Note: this is an interactive program
import DataReader as dr
import networkx as nx
import lib.Tools as t
import matplotlib.pyplot as plt
################## Code for picking out outlier binary images ########################
alienDict = dr.read_sm("data/Shape-Matcher-models/ALIEN.xml")
t.rename_key(alienDict, oldKey="models/ALIEN/ALIEN", newKey="alien")
childDict = dr.read_sm("data/Shape-Matcher-models/m_chld.xml")
t.rename_key(childDict, oldKey="models/m_chld/m_chld", newKey="child")
camelDict = dr.read_sm("data/Shape-Matcher-models/camel.xml")
t.rename_key(camelDict, oldKey="models/camel/camel", newKey="camel")
# 17 is a good camel model
horseDict = dr.read_sm("data/Shape-Matcher-models/HORSE.xml")
t.rename_key(horseDict, oldKey="models/HORSE/HORSE", newKey="horse")
# 52 isa good horse model
eagleDict = dr.read_sm("data/Shape-Matcher-models/eagle.xml")
t.rename_key(eagleDict, oldKey="models/eagle/eagle", newKey="eagle")
# 35 is a good eagle model
