OBJ.parse() - Code Metrics - explosiveduck/ed2d - Measure and Improve Code Quality continuously with Scrutinizer

OBJ.parse() F
last analyzed 2016-05-20 05:45 UTC

↳ Parent: OBJ

Complexity

Conditions

Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Importance

Changes	2
Bugs	0	Features	0

Metric	Value
cc	18
dl	0
loc	67
rs	2.6879
c	2
b	0
f	0

How to fix Long Method Complexity

from ed2d.assets.mtlloader import MTL
from ed2d import files

class OBJ(object):
    def __init__(self, fileName):
        ''' Wavefront .obj file parser.'''
        objPath = files.resolve_path('data', 'models', fileName + '.obj')

        self.fmvnig = {}

        # Shared temporary storage of data
        self.tempVertices = []
        self.tempNormals = []
        self.tempUVs = []

        # Load the obj file
        with open(objPath, 'r') as objfile:
            self.lines = objfile.readlines()

        self.parse()


    def parse(self):
        ''' Perform the parsing of the obj format  '''

        matname = None
        valueType = None

        for line in self.lines:
            valueType, value = line.strip().split(' ', 1)

            # Don't bother unless the following key words exist in the line
            if valueType not in ['o', 'g', 'f', 'v', 'vt', 'vn', 'usemtl', 'mtllib']:
                continue

            value = value.split(' ')

            # Check first and continue on early because of string splitting
            if valueType == "usemtl":
                matname = value[0]
                continue

            if valueType in ['g', 'o']:
                # These objects reset state basically
                matname = None
                continue

            if valueType == 'mtllib':
                mtlpath = files.resolve_path('data', 'models', value[0])

                # Load the mtl file
                self.mtlfile = MTL(mtlpath)
                for material in self.mtlfile.data.keys():
                    self.fmvnig[material] = [ [], [], [] ]

                continue

            if valueType == "f":
                face = [item.split("/") for item in value]
                for typeGroup in face:
                    for typeIndex in range(len(typeGroup)):
                        if typeIndex == 0: # Vertex
                            typeSource = self.tempVertices
                        elif typeIndex == 1: # UV
                            typeSource = self.tempUVs
                        elif typeIndex == 2: # Normal
                            typeSource = self.tempNormals

                        index = typeGroup[typeIndex]

                        # Make sure data exists
                        if index != '':
                            index = int(index)
                            typeData = typeSource[index - 1]

                            self.fmvnig[matname][typeIndex].append(typeData)
                continue

            # Map the values after the keyword to floats
            value = list(map(float, value))

            if valueType == "v":
                self.tempVertices.append(value)

            elif valueType == "vt":
                self.tempUVs.append(value * 2)

            elif valueType == "vn":
                self.tempNormals.append(value)


1			from ed2d.assets.mtlloader import MTL
2			from ed2d import files
3
4			class OBJ(object):
5			def __init__(self, fileName):
6			''' Wavefront .obj file parser.'''
7			objPath = files.resolve_path('data', 'models', fileName + '.obj')
8
9			self.fmvnig = {}
10
11			# Shared temporary storage of data
12			self.tempVertices = []
13			self.tempNormals = []
14			self.tempUVs = []
15
16			# Load the obj file
17			with open(objPath, 'r') as objfile:
18			self.lines = objfile.readlines()
19
20			self.parse()
21
22
23			def parse(self):
24			''' Perform the parsing of the obj format '''
25
26			matname = None
27			valueType = None
28
29			for line in self.lines:
30			valueType, value = line.strip().split(' ', 1)
31
32			# Don't bother unless the following key words exist in the line
33			if valueType not in ['o', 'g', 'f', 'v', 'vt', 'vn', 'usemtl', 'mtllib']:
34			continue
35
36			value = value.split(' ')
37
38			# Check first and continue on early because of string splitting
39			if valueType == "usemtl":
40			matname = value[0]
41			continue
42
43			if valueType in ['g', 'o']:
44			# These objects reset state basically
45			matname = None
46			continue
47
48			if valueType == 'mtllib':
49			mtlpath = files.resolve_path('data', 'models', value[0])
50
51			# Load the mtl file
52			self.mtlfile = MTL(mtlpath)
53			for material in self.mtlfile.data.keys():
54			self.fmvnig[material] = [ [], [], [] ]
55
56			continue
57
58			if valueType == "f":
59			face = [item.split("/") for item in value]
60			for typeGroup in face:
61			for typeIndex in range(len(typeGroup)):
62			if typeIndex == 0: # Vertex
63			typeSource = self.tempVertices
64			elif typeIndex == 1: # UV
65			typeSource = self.tempUVs
66			elif typeIndex == 2: # Normal
67			typeSource = self.tempNormals
68
69			index = typeGroup[typeIndex]
70
71			# Make sure data exists
72			if index != '':
73			index = int(index)
74			typeData = typeSource[index - 1]
75
76			self.fmvnig[matname][typeIndex].append(typeData)
77			continue
78
79			# Map the values after the keyword to floats
80			value = list(map(float, value))
81
82			if valueType == "v":
83			self.tempVertices.append(value)
84
85			elif valueType == "vt":
86			self.tempUVs.append(value * 2)
87
88			elif valueType == "vn":
89			self.tempNormals.append(value)
90

explosiveduck / ed2d

OBJ.parse() F last analyzed 2016-05-20 05:45 UTC

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OBJ.parse() F
last analyzed 2016-05-20 05:45 UTC