Source code for pyleecan.Classes.ImportGenVectSin

# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Import/ImportGenVectSin.csv
# WARNING! All changes made in this file will be lost!
"""Method code available at https://github.com/Eomys/pyleecan/tree/master/pyleecan/Methods/Import/ImportGenVectSin
"""

from os import linesep
from sys import getsizeof
from logging import getLogger
from ._check import check_var, raise_
from ..Functions.get_logger import get_logger
from ..Functions.save import save
from ..Functions.load import load_init_dict
from ..Functions.Load.import_class import import_class
from copy import deepcopy
from .ImportMatrix import ImportMatrix

# Import all class method
# Try/catch to remove unnecessary dependencies in unused method
try:
    from ..Methods.Import.ImportGenVectSin.get_data import get_data
except ImportError as error:
    get_data = error


from numpy import isnan
from ._check import InitUnKnowClassError


[docs]class ImportGenVectSin(ImportMatrix): """To generate a Sinus vector""" VERSION = 1 # cf Methods.Import.ImportGenVectSin.get_data if isinstance(get_data, ImportError): get_data = property( fget=lambda x: raise_( ImportError( "Can't use ImportGenVectSin method get_data: " + str(get_data) ) ) ) else: get_data = get_data # generic save method is available in all object save = save # get_logger method is available in all object get_logger = get_logger def __init__( self, f=100, A=1, Phi=0, N=1024, Tf=1, is_transpose=False, init_dict=None, init_str=None, ): """Constructor of the class. Can be use in three ways : - __init__ (arg1 = 1, arg3 = 5) every parameters have name and default values for pyleecan type, -1 will call the default constructor - __init__ (init_dict = d) d must be a dictionary with property names as keys - __init__ (init_str = s) s must be a string s is the file path to load ndarray or list can be given for Vector and Matrix object or dict can be given for pyleecan Object""" if init_str is not None: # Load from a file init_dict = load_init_dict(init_str)[1] if init_dict is not None: # Initialisation by dict assert type(init_dict) is dict # Overwrite default value with init_dict content if "f" in list(init_dict.keys()): f = init_dict["f"] if "A" in list(init_dict.keys()): A = init_dict["A"] if "Phi" in list(init_dict.keys()): Phi = init_dict["Phi"] if "N" in list(init_dict.keys()): N = init_dict["N"] if "Tf" in list(init_dict.keys()): Tf = init_dict["Tf"] if "is_transpose" in list(init_dict.keys()): is_transpose = init_dict["is_transpose"] # Set the properties (value check and convertion are done in setter) self.f = f self.A = A self.Phi = Phi self.N = N self.Tf = Tf # Call ImportMatrix init super(ImportGenVectSin, self).__init__(is_transpose=is_transpose) # The class is frozen (in ImportMatrix init), for now it's impossible to # add new properties def __str__(self): """Convert this object in a readeable string (for print)""" ImportGenVectSin_str = "" # Get the properties inherited from ImportMatrix ImportGenVectSin_str += super(ImportGenVectSin, self).__str__() ImportGenVectSin_str += "f = " + str(self.f) + linesep ImportGenVectSin_str += "A = " + str(self.A) + linesep ImportGenVectSin_str += "Phi = " + str(self.Phi) + linesep ImportGenVectSin_str += "N = " + str(self.N) + linesep ImportGenVectSin_str += "Tf = " + str(self.Tf) + linesep return ImportGenVectSin_str def __eq__(self, other): """Compare two objects (skip parent)""" if type(other) != type(self): return False # Check the properties inherited from ImportMatrix if not super(ImportGenVectSin, self).__eq__(other): return False if other.f != self.f: return False if other.A != self.A: return False if other.Phi != self.Phi: return False if other.N != self.N: return False if other.Tf != self.Tf: return False return True
[docs] def compare(self, other, name="self", ignore_list=None, is_add_value=False): """Compare two objects and return list of differences""" if ignore_list is None: ignore_list = list() if type(other) != type(self): return ["type(" + name + ")"] diff_list = list() # Check the properties inherited from ImportMatrix diff_list.extend( super(ImportGenVectSin, self).compare( other, name=name, ignore_list=ignore_list, is_add_value=is_add_value ) ) if ( other._f is not None and self._f is not None and isnan(other._f) and isnan(self._f) ): pass elif other._f != self._f: if is_add_value: val_str = " (self=" + str(self._f) + ", other=" + str(other._f) + ")" diff_list.append(name + ".f" + val_str) else: diff_list.append(name + ".f") if ( other._A is not None and self._A is not None and isnan(other._A) and isnan(self._A) ): pass elif other._A != self._A: if is_add_value: val_str = " (self=" + str(self._A) + ", other=" + str(other._A) + ")" diff_list.append(name + ".A" + val_str) else: diff_list.append(name + ".A") if ( other._Phi is not None and self._Phi is not None and isnan(other._Phi) and isnan(self._Phi) ): pass elif other._Phi != self._Phi: if is_add_value: val_str = ( " (self=" + str(self._Phi) + ", other=" + str(other._Phi) + ")" ) diff_list.append(name + ".Phi" + val_str) else: diff_list.append(name + ".Phi") if other._N != self._N: if is_add_value: val_str = " (self=" + str(self._N) + ", other=" + str(other._N) + ")" diff_list.append(name + ".N" + val_str) else: diff_list.append(name + ".N") if ( other._Tf is not None and self._Tf is not None and isnan(other._Tf) and isnan(self._Tf) ): pass elif other._Tf != self._Tf: if is_add_value: val_str = " (self=" + str(self._Tf) + ", other=" + str(other._Tf) + ")" diff_list.append(name + ".Tf" + val_str) else: diff_list.append(name + ".Tf") # Filter ignore differences diff_list = list(filter(lambda x: x not in ignore_list, diff_list)) return diff_list
def __sizeof__(self): """Return the size in memory of the object (including all subobject)""" S = 0 # Full size of the object # Get size of the properties inherited from ImportMatrix S += super(ImportGenVectSin, self).__sizeof__() S += getsizeof(self.f) S += getsizeof(self.A) S += getsizeof(self.Phi) S += getsizeof(self.N) S += getsizeof(self.Tf) return S
[docs] def as_dict(self, type_handle_ndarray=0, keep_function=False, **kwargs): """ Convert this object in a json serializable dict (can be use in __init__). type_handle_ndarray: int How to handle ndarray (0: tolist, 1: copy, 2: nothing) keep_function : bool True to keep the function object, else return str Optional keyword input parameter is for internal use only and may prevent json serializability. """ # Get the properties inherited from ImportMatrix ImportGenVectSin_dict = super(ImportGenVectSin, self).as_dict( type_handle_ndarray=type_handle_ndarray, keep_function=keep_function, **kwargs ) ImportGenVectSin_dict["f"] = self.f ImportGenVectSin_dict["A"] = self.A ImportGenVectSin_dict["Phi"] = self.Phi ImportGenVectSin_dict["N"] = self.N ImportGenVectSin_dict["Tf"] = self.Tf # The class name is added to the dict for deserialisation purpose # Overwrite the mother class name ImportGenVectSin_dict["__class__"] = "ImportGenVectSin" return ImportGenVectSin_dict
[docs] def copy(self): """Creates a deepcopy of the object""" # Handle deepcopy of all the properties f_val = self.f A_val = self.A Phi_val = self.Phi N_val = self.N Tf_val = self.Tf is_transpose_val = self.is_transpose # Creates new object of the same type with the copied properties obj_copy = type(self)( f=f_val, A=A_val, Phi=Phi_val, N=N_val, Tf=Tf_val, is_transpose=is_transpose_val, ) return obj_copy
def _set_None(self): """Set all the properties to None (except pyleecan object)""" self.f = None self.A = None self.Phi = None self.N = None self.Tf = None # Set to None the properties inherited from ImportMatrix super(ImportGenVectSin, self)._set_None() def _get_f(self): """getter of f""" return self._f def _set_f(self, value): """setter of f""" check_var("f", value, "float", Vmin=0) self._f = value f = property( fget=_get_f, fset=_set_f, doc=u"""Frequency of the sinus to generate :Type: float :min: 0 """, ) def _get_A(self): """getter of A""" return self._A def _set_A(self, value): """setter of A""" check_var("A", value, "float") self._A = value A = property( fget=_get_A, fset=_set_A, doc=u"""Amplitude of the sinus to generate :Type: float """, ) def _get_Phi(self): """getter of Phi""" return self._Phi def _set_Phi(self, value): """setter of Phi""" check_var("Phi", value, "float", Vmin=-6.29, Vmax=6.29) self._Phi = value Phi = property( fget=_get_Phi, fset=_set_Phi, doc=u"""Phase of the sinus to generate :Type: float :min: -6.29 :max: 6.29 """, ) def _get_N(self): """getter of N""" return self._N def _set_N(self, value): """setter of N""" check_var("N", value, "int", Vmin=0) self._N = value N = property( fget=_get_N, fset=_set_N, doc=u"""Length of the vector to generate :Type: int :min: 0 """, ) def _get_Tf(self): """getter of Tf""" return self._Tf def _set_Tf(self, value): """setter of Tf""" check_var("Tf", value, "float", Vmin=0) self._Tf = value Tf = property( fget=_get_Tf, fset=_set_Tf, doc=u"""End time of the sinus generation :Type: float :min: 0 """, )