Source code for pyleecan.Classes.SolutionData

# -*- coding: utf-8 -*-
# File generated according to Generator/ClassesRef/Mesh/SolutionData.csv
# WARNING! All changes made in this file will be lost!
"""Method code available at

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 import save
from ..Functions.load import load_init_dict
from ..Functions.Load.import_class import import_class
from copy import deepcopy
from .Solution import Solution

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

    from ..Methods.Mesh.SolutionData.get_axes_list import get_axes_list
except ImportError as error:
    get_axes_list = error

    from ..Methods.Mesh.SolutionData.get_solution import get_solution
except ImportError as error:
    get_solution = error

from numpy import isnan
from ._check import InitUnKnowClassError

[docs]class SolutionData(Solution): """Define a Solution with SciDataTool objects.""" VERSION = 1 # Check ImportError to remove unnecessary dependencies in unused method # cf Methods.Mesh.SolutionData.get_field if isinstance(get_field, ImportError): get_field = property( fget=lambda x: raise_( ImportError( "Can't use SolutionData method get_field: " + str(get_field) ) ) ) else: get_field = get_field # cf Methods.Mesh.SolutionData.get_axes_list if isinstance(get_axes_list, ImportError): get_axes_list = property( fget=lambda x: raise_( ImportError( "Can't use SolutionData method get_axes_list: " + str(get_axes_list) ) ) ) else: get_axes_list = get_axes_list # cf Methods.Mesh.SolutionData.get_solution if isinstance(get_solution, ImportError): get_solution = property( fget=lambda x: raise_( ImportError( "Can't use SolutionData method get_solution: " + str(get_solution) ) ) ) else: get_solution = get_solution # 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, field=None, type_cell="triangle", label=None, dimension=2, unit="", 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 "field" in list(init_dict.keys()): field = init_dict["field"] if "type_cell" in list(init_dict.keys()): type_cell = init_dict["type_cell"] if "label" in list(init_dict.keys()): label = init_dict["label"] if "dimension" in list(init_dict.keys()): dimension = init_dict["dimension"] if "unit" in list(init_dict.keys()): unit = init_dict["unit"] # Set the properties (value check and convertion are done in setter) self.field = field # Call Solution init super(SolutionData, self).__init__( type_cell=type_cell, label=label, dimension=dimension, unit=unit ) # The class is frozen (in Solution init), for now it's impossible to # add new properties def __str__(self): """Convert this object in a readeable string (for print)""" SolutionData_str = "" # Get the properties inherited from Solution SolutionData_str += super(SolutionData, self).__str__() SolutionData_str += "field = " + str(self.field) + linesep + linesep return SolutionData_str def __eq__(self, other): """Compare two objects (skip parent)""" if type(other) != type(self): return False # Check the properties inherited from Solution if not super(SolutionData, self).__eq__(other): return False if other.field != self.field: 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 Solution diff_list.extend( super(SolutionData, self).compare( other, name=name, ignore_list=ignore_list, is_add_value=is_add_value ) ) if (other.field is None and self.field is not None) or ( other.field is not None and self.field is None ): diff_list.append(name + ".field None mismatch") elif self.field is not None: diff_list.extend( other.field, name=name + ".field", ignore_list=ignore_list, is_add_value=is_add_value, ) ) # 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 Solution S += super(SolutionData, self).__sizeof__() S += getsizeof(self.field) 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 Solution SolutionData_dict = super(SolutionData, self).as_dict( type_handle_ndarray=type_handle_ndarray, keep_function=keep_function, **kwargs ) if self.field is None: SolutionData_dict["field"] = None else: SolutionData_dict["field"] = self.field.as_dict( type_handle_ndarray=type_handle_ndarray, keep_function=keep_function, **kwargs ) # The class name is added to the dict for deserialisation purpose # Overwrite the mother class name SolutionData_dict["__class__"] = "SolutionData" return SolutionData_dict
[docs] def copy(self): """Creates a deepcopy of the object""" # Handle deepcopy of all the properties if self.field is None: field_val = None else: field_val = self.field.copy() type_cell_val = self.type_cell label_val = self.label dimension_val = self.dimension unit_val = self.unit # Creates new object of the same type with the copied properties obj_copy = type(self)( field=field_val, type_cell=type_cell_val, label=label_val, dimension=dimension_val, unit=unit_val, ) return obj_copy
def _set_None(self): """Set all the properties to None (except pyleecan object)""" self.field = None # Set to None the properties inherited from Solution super(SolutionData, self)._set_None() def _get_field(self): """getter of field""" return self._field def _set_field(self, value): """setter of field""" if isinstance(value, str): # Load from file try: value = load_init_dict(value)[1] except Exception as e: self.get_logger().error( "Error while loading " + value + ", setting None instead" ) value = None if isinstance(value, dict) and "__class__" in value: class_obj = import_class( "SciDataTool.Classes", value.get("__class__"), "field" ) value = class_obj(init_dict=value) elif type(value) is int and value == -1: # Default constructor value = DataND() check_var("field", value, "DataND") self._field = value field = property( fget=_get_field, fset=_set_field, doc=u"""Data object containing the numerical values of a solution. One of the axis must be "Indices", a list of indices. If the solution is a vector, one of the axis must be "Direction", values ['x','y'] for example. :Type: SciDataTool.Classes.DataND.DataND """, )