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- from .node_container_common import *
- from .base_definitions import MantisNode, NodeSocket
- def TellClasses():
- return [
- MathStaticInt,
- MathStaticFloat,
- MathStaticVector,
- ]
- #*#-------------------------------#++#-------------------------------#*#
- # M A T H N O D E S
- #*#-------------------------------#++#-------------------------------#*#
- class MathStaticInt(MantisNode):
- '''A node representing an armature object'''
- def __init__(self, signature, base_tree):
- super().__init__(signature, base_tree)
- inputs = [
- "Operation",
- "Int A",
- "Int B",
- ]
- outputs = [
- "Result Int",
- ]
- additional_parameters = {}
- self.inputs.init_sockets(inputs)
- self.outputs.init_sockets(outputs)
- self.init_parameters(additional_parameters=additional_parameters)
- self.node_type = "UTILITY"
- def bPrepare(self, bContext = None,):
- a = self.evaluate_input("Int A"); b = self.evaluate_input("Int B")
- result = float("NaN")
- if self.evaluate_input("Operation") == "ADD":
- result = int(a+b)
- if self.evaluate_input("Operation") == "SUBTRACT":
- result = int(a-b)
- if self.evaluate_input("Operation") == "MULTIPLY":
- result = int(a*b)
- if self.evaluate_input("Operation") == "FLOOR_DIVIDE":
- result = a//b
- if self.evaluate_input("Operation") == "MODULUS":
- result = int(a%b)
- if self.evaluate_input("Operation") == "POWER":
- result = int(a**b)
- if self.evaluate_input("Operation") == "ABSOLUTE":
- result = int(abs(a))
- if self.evaluate_input("Operation") == "MAXIMUM":
- result = int(a if a <= b else b)
- if self.evaluate_input("Operation") == "MINIMUM":
- result = int(a if a >= b else b)
- if self.evaluate_input("Operation") == "GREATER THAN":
- result = int(a > b)
- if self.evaluate_input("Operation") == "LESS THAN":
- result = int(a < b)
- self.parameters["Result Int"] = result
- self.prepared = True
- self.executed = True
- class MathStaticFloat(MantisNode):
- '''A node representing an armature object'''
- def __init__(self, signature, base_tree):
- super().__init__(signature, base_tree)
- inputs = [
- "Operation",
- "Float A",
- "Float B",
- ]
- outputs = [
- "Result Float",
- ]
- additional_parameters = {}
- self.inputs.init_sockets(inputs)
- self.outputs.init_sockets(outputs)
- self.init_parameters(additional_parameters=additional_parameters)
- self.node_type = "UTILITY"
- def bPrepare(self, bContext = None,):
- a = self.evaluate_input("Float A"); b = self.evaluate_input("Float B")
- result = float("NaN")
- if self.evaluate_input("Operation") == "ADD":
- result = a+b
- if self.evaluate_input("Operation") == "SUBTRACT":
- result = a-b
- if self.evaluate_input("Operation") == "MULTIPLY":
- result = a*b
- if self.evaluate_input("Operation") == "DIVIDE":
- result = a/b
- if self.evaluate_input("Operation") == "FLOOR_DIVIDE":
- result = a//b
- if self.evaluate_input("Operation") == "MODULUS":
- result = a%b
- if self.evaluate_input("Operation") == "POWER":
- result = a**b
- if self.evaluate_input("Operation") == "ABSOLUTE":
- result = abs(a)
- if self.evaluate_input("Operation") == "MAXIMUM":
- result = a if a <= b else b
- if self.evaluate_input("Operation") == "MINIMUM":
- result = a if a >= b else b
- if self.evaluate_input("Operation") == "GREATER THAN":
- result = float(a > b)
- if self.evaluate_input("Operation") == "LESS THAN":
- result = float(a < b)
- if self.evaluate_input("Operation") == "ARCTAN2":
- from math import atan2
- result = atan2(a,b)
- self.parameters["Result Float"] = result
- self.prepared = True
- self.executed = True
- class MathStaticVector(MantisNode):
- '''A node representing an armature object'''
- def __init__(self, signature, base_tree):
- super().__init__(signature, base_tree)
- inputs = [
- "Operation",
- "Vector A",
- "Vector B",
- "Scalar A",
- ]
- outputs = [
- "Result Vector",
- "Result Float",
- ]
- additional_parameters = {}
- self.inputs.init_sockets(inputs)
- self.outputs.init_sockets(outputs)
- self.init_parameters(additional_parameters=additional_parameters)
- self.node_type = "UTILITY"
- def bPrepare(self, bContext = None,):
- from mathutils import Vector
- a = Vector(self.evaluate_input("Vector A")).copy()
- b = Vector(self.evaluate_input("Vector B")).copy()
- s = self.evaluate_input("Scalar A")
- if hasattr(s, '__iter__'):
- average = lambda iterable : sum(iterable)/len(iterable)
- s = average(s)
- f_result = float("NaN")
- v_result = None
- if self.evaluate_input("Operation") == "ADD":
- v_result = a+b
- if self.evaluate_input("Operation") == "SUBTRACT":
- v_result = a-b
- if self.evaluate_input("Operation") == "MULTIPLY":
- v_result = a*b
- if self.evaluate_input("Operation") == "DIVIDE":
- v_result = a/b
- if self.evaluate_input("Operation") == "POWER":
- v_result = a**b
- # since these are unary, we need to make a copy lest we create spooky effects elsewhere.
- a = a.copy()
- if self.evaluate_input("Operation") == "SCALE":
- v_result = a.normalized() * s
- if self.evaluate_input("Operation") == "LENGTH":
- f_result = a.magnitude
- if self.evaluate_input("Operation") == "CROSS":
- v_result = a.cross(b)
- if self.evaluate_input("Operation") == "DOT":
- f_result = a.dot(b)
- if self.evaluate_input("Operation") == "NORMALIZE":
- v_result = a.normalized()
- if self.evaluate_input("Operation") == "LINEAR_INTERP":
- v_result = a.lerp(b, s).copy()
- self.parameters["Result Float"] = f_result
- # if v_result:
- self.parameters["Result Vector"] = v_result
- self.prepared = True
- self.executed = True
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