def findRadius(self):
filename = StepData.get_filename(self)
with open('./instance/uploads/'+filename) as openfileobject:
for l, line in enumerate(openfileobject,1):
if "=ADVANCED_FACE(" in line:
adfs = re.search(r'\((.*?)\((.*?)\)(.*?)\)',line).group(2).split(",")
if len(adfs) == 2:
advancedFace = adfs[1]
for m, linet in enumerate(openfileobject,l+1):
if advancedFace in linet:
facebound = re.search(r'\((.*?)\)',linet).group(1).split(",")[1]
break
for n, linett in enumerate(openfileobject, m+1):
if facebound in linett:
edgeloop = re.search(r'\((.*?)\((.*?)\)(.*?)\)',linett).group(2).split(",")[0]
break
for o, linettt in enumerate(openfileobject, n+1):
if edgeloop in linettt:
orientededge = re.search(r'\((.*?)\)',linettt).group(1).split(",")[3]
break
for p, linetttt in enumerate(openfileobject,o+1):
if orientededge in linetttt:
edgecurve = re.search(r'\((.*?)\)',linetttt).group(1).split(",")[3]
break
for q, linettttt in enumerate(openfileobject, p+1):
if edgecurve in linettttt:
circle = re.search(r'\((.*?)\)',linettttt).group(1).split(",")
radius = round(float(circle[2]),2)
break
StepData.set_radius(self, radius)
def updateCSVFile(self):
fileDescription = StepData.get_fileDescription(self)
filename = StepData.get_filename(self)
manifoldSolidBrepCount = StepData.get_manifoldSolidBrepCount(self)
totalPlaneSurfaces = StepData.get_totalPlaneSurfaces(self)
radius = StepData.get_radius(self)
category = StepData.get_category(self)
gdriveFileId = StepData.get_gdriveFileId(self)
serialNumber = 1
StepData.set_serialNumber(self, serialNumber)
try:
with open('PartDetails.csv', 'r') as readFile:
reader = csv.reader(readFile)
serialNumber= len(list(reader))
StepData.set_serialNumber(self, serialNumber)
with open('PartDetails.csv', 'a', newline='') as csvFile:
fieldnames = ["SERIAL_NUMBER","FILE_DESCRIPTION", "FILENAME","MANIFOLD_SOLID_BREP","PLANE","RADIUS","CATEGORY","GDRIVE_FILE_ID"]
writer = csv.DictWriter(csvFile, fieldnames=fieldnames)
writer.writerow({'SERIAL_NUMBER': serialNumber,"FILE_DESCRIPTION": fileDescription, "FILENAME": filename,
"MANIFOLD_SOLID_BREP": manifoldSolidBrepCount, "PLANE": totalPlaneSurfaces, "RADIUS":radius,"CATEGORY":category,
"GDRIVE_FILE_ID": gdriveFileId})
except FileNotFoundError:
with open('PartDetails.csv', 'w', newline='') as csvFile:
fieldnames = ["SERIAL_NUMBER","FILE_DESCRIPTION", "FILENAME","MANIFOLD_SOLID_BREP","PLANE","RADIUS","CATEGORY","GDRIVE_FILE_ID"]
writer = csv.DictWriter(csvFile, fieldnames=fieldnames)
writer.writeheader()
writer.writerow({'SERIAL_NUMBER': serialNumber,"FILE_DESCRIPTION": fileDescription, "FILENAME": filename,
"MANIFOLD_SOLID_BREP": manifoldSolidBrepCount, "PLANE": totalPlaneSurfaces, "RADIUS":radius,"CATEGORY":category,
"GDRIVE_FILE_ID": gdriveFileId})
def stepFileHeaders(self):
filename = filename = StepData.get_filename(self)
manifoldSolidBrepCount = 0
totalPlaneSurfaces = -2
with open('./instance/uploads/'+filename) as openfileobject:
for line in openfileobject:
if "FILE_DESCRIPTION" in line:
fileDescription = re.search(r'\(\((.*?)\)(.*?)\)',line).group(1).split(",")[0]
StepData.set_fileDescription(self, fileDescription)
elif "MANIFOLD_SOLID_BREP" in line:
manifoldSolidBrepCount = manifoldSolidBrepCount + 1
StepData.set_manifoldSolidBrepCount(self, manifoldSolidBrepCount)
elif "=PLANE(" in line:
totalPlaneSurfaces = totalPlaneSurfaces + 1
StepData.set_totalPlaneSurfaces(self, totalPlaneSurfaces)
if manifoldSolidBrepCount > 1:
return False
else:
return True
def googleDriveFileUpload(self, file):
filename = StepData.get_filename(self)
mimetype = file.mimetype
service = Create_Service(CLIENT_SECRET_FILE, API_NAME, API_VERSION, SCOPES)
for filename,mimetype in zip([filename], [mimetype]):
file_metadata = {
'name': filename,
'parents': [GOOGLE_DRIVE_FOLDER_ID]
}
# Upload file to GDrive from local storage at /instance/uploads/filename
media = MediaFileUpload('./instance/uploads/{0}'.format(filename), mimetype=mimetype)
file = service.files().create(
body=file_metadata,
media_body=media,
fields='id'
).execute()
fileId = file.get('id')
StepData.set_gdriveFileId(self, fileId)
def aiTrainer(self, isCompare):
fileDescription = StepData.get_fileDescription(self)
filename = StepData.get_filename(self)
manifoldSolidBrepCount = StepData.get_manifoldSolidBrepCount(self)
totalPlaneSurfaces = StepData.get_totalPlaneSurfaces(self)
radius = StepData.get_radius(self)
category = StepData.get_category(self)
gdriveFileId = StepData.get_gdriveFileId(self)
serialNumber = StepData.get_serialNumber(self)
#NEO4J DATA, data of the form [radius,id,class]
partClass = 1
resultTrainSet = dbConnection.getradius(serialNumber, partClass, radius)
# TODO : Megha
testInstance = []
if isCompare:
# Compare
arrayOutside = []
for i in range(len(resultTrainSet)):
arrayInside = []
list1 = itemgetter(i)(resultTrainSet)
listprep1 = (list1['n.radius'])
arrayInside.append(listprep1)
listprep11 = (list1['n.id'])
arrayInside.append(listprep11)
listprep12 = (list1['n.partClass'])
arrayInside.append(listprep12)
arrayOutside.append(arrayInside)
trainSet = arrayOutside
else:
# Import
trainSet = [[4,11,'1'], [1,12,'1'],[2,13,'1'],[3,14,'1'],[5,16,'2'],[7,10,'2'],[10,19,'3']]
#getting radius from step file algorithm
testInstance.append(radius)
# checking if id already exists , generate non repeating random number
for i in range(len(trainSet)):
list1 = itemgetter(i)(trainSet)
list1_element1 = itemgetter(1)(list1)
step_data_id = random.randint(20,200)
if not step_data_id == list1_element1:
testInstance.append(step_data_id)
a = testInstance[0:1]
#extracting first element of list to find class
a = itemgetter(0)(testInstance)
# 1-4 is class 1, 5-8 is class 2 , 9-12 is class 3
if a > 1 and a <= 4 :
partClass = '1'
elif a > 4 and a <= 8:
partClass = '2'
elif a > 8 and a <= 12:
partClass = '3'
else :
partClass = '4'
importResult = dbConnection.savePartDetails(serialNumber, fileDescription, filename, manifoldSolidBrepCount, totalPlaneSurfaces, radius, category, partClass, gdriveFileId)
importData = []
for item in importResult:
importData.append(item['n'])
# if compare:
if isCompare:
# TODO : change the value of kNearestNeighbours for more accuracy
kNearestNeighbours = 3
neighbors = GetNeighbors.getNeighors(self, trainSet , testInstance , kNearestNeighbours)
#getting predicted class of data
response = GetResponse.getResponse(self, neighbors)
predictions= []
predictions.append(response)
#getting accuracy based on true class and predicted class
# TODO : return to UI
accuracy = GetAccuracy.getAccuracy(self, predictions,partClass)
getClassResult = dbConnection.getclass(partClass)
testInstance.append(partClass)
trainSet.append(testInstance)
# to Neo4j
compareResult = dbConnection.getclass(partClass)
compareData = []
for item in compareResult:
compareData.append(item['n'])
originalPart = []
similarParts = []
for item in compareData:
if item['reference'] == StepData.get_filename(self):
originalPart.append(item)
else:
similarParts.append(item)
return originalPart, similarParts, accuracy
return importData