magneticalc.Field.Field

class documentation

class Field(Validatable):

Constructor: Field()

Field class.

Static Method	`get_arrows`	Returns the field arrow parameters needed by `VisPyCanvas`.
Method	`__init__`	Initializes a field.
Method	`get_units`	Gets field units.
Method	`recalculate`	Recalculates field vectors.
Method	`set`	Sets the parameters.
Instance Variable	`type`	Undocumented
Property	`total_calculations`	Gets total number of calculations.
Property	`total_skipped_calculations`	Gets total number of skipped calculations.
Property	`vectors`	Gets field vectors. (The selected field type determined which field was calculated.)
Property	`vectors_count`	Number of field vectors
Instance Variable	`_distance_limit`	Undocumented
Instance Variable	`_length_scale`	Undocumented
Instance Variable	`_total_calculations`	Undocumented
Instance Variable	`_total_skipped_calculations`	Undocumented
Instance Variable	`_vectors`	Undocumented

Inherited from Validatable:

Method	`valid.setter`	No summary
Property	`valid`	True if valid, False if invalid
Instance Variable	`_valid`	Undocumented

@staticmethod
@ConditionalDecorator(get_jit_enabled(), jit, nopython=True, parallel=True)

def get_arrows(sampling_volume_points: np.ndarray, field_vectors: np.ndarray, line_pairs: np.ndarray, head_points: np.ndarray, arrow_scale: float, magnitude_limit: float) -> tuple[np.ndarray, np.ndarray]: ¶

Returns the field arrow parameters needed by VisPyCanvas.

Parameters
sampling_volume_points:`np.ndarray`	Sampling volume points
field_vectors:`np.ndarray`	Field vectors
line_pairs:`np.ndarray`	Arrow line pairs (ordered list of arrow start/stop 3D points)
head_points:`np.ndarray`	Arrow head points (ordered list of arrow stop 3D points)
arrow_scale:`float`	Arrow scale
magnitude_limit:`float`	Magnitude limit (mitigating divisions by zero)

Returns
`tuple[np.ndarray, np.ndarray]`	Line pairs, head points

def __init__(self): ¶

overrides magneticalc.Validatable.Validatable.__init__

Initializes a field.

def get_units(self, show_gauss=False) -> tuple[str, float]: ¶

Gets field units.

Parameters
show_gauss	Enable to show Gauss instead of Tesla

Returns
`tuple[str, float]`	Field units, field factor

@validator

def recalculate(self, wire: Wire, sampling_volume: SamplingVolume, progress_callback: Callable, num_cores: int, backend_type: int) -> bool: ¶

Recalculates field vectors.

Parameters
wire:`Wire`	Wire
sampling_volume:`SamplingVolume`	Sampling volume
progress_callback:`Callable`	Progress callback
num_cores:`int`	Number of cores to use for multiprocessing
backend_type:`int`	Backend type

Returns
`bool`	True if successful, False if interrupted (CUDA backend currently not interruptable)

def set(self, type: int, distance_limit: float, length_scale: float): ¶

Sets the parameters.

Parameters
type:`int`	Field type
distance_limit:`float`	Distance limit (mitigating divisions by zero)
length_scale:`float`	Length scale (m)

type = ¶

Undocumented

@property
@require_valid

total_calculations: int = ¶

Gets total number of calculations.

@property
@require_valid

total_skipped_calculations: int = ¶

Gets total number of skipped calculations.

@property
@require_valid

vectors: np.ndarray = ¶

Gets field vectors. (The selected field type determined which field was calculated.)

@property
@require_valid

vectors_count: int = ¶

Number of field vectors

_distance_limit = ¶

Undocumented

_length_scale = ¶

Undocumented

_total_calculations: int = ¶

Undocumented

_total_skipped_calculations: int = ¶

Undocumented

_vectors: np.ndarray = ¶

Undocumented