# -*- 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
""",
)
