The readme states There are a number of other features

The Model class has a density method: <p dir="aut

Convenience Functions? about ceviche-challenges HOT 2 CLOSED

google commented on May 4, 2024

Convenience Functions?

from ceviche-challenges.

Comments (2)

ianwilliamson commented on May 4, 2024 1

The Model class has a density method:

ceviche-challenges/ceviche_challenges/model_base.py

Lines 216 to 217 in 6731eac

 def density(self, design_variable: np.ndarray) -> np.ndarray: 

 """The combined (design + background) density distribution of the model."""

It returns an image array that one could pass to Matplotlib's imshow() or pcolor() functions. The simulator outputs are scattering parameters and fields:

ceviche-challenges/ceviche_challenges/model_base.py

Lines 89 to 119 in 6731eac

 def simulate( 

 self, 

 design_variable: np.ndarray, 

 excite_port_idxs: Sequence[int] = (0,), 

 wavelengths_nm: Optional[np.ndarray] = None, 

 max_parallelizm: Optional[int] = None, 

 ) -> Tuple[np.ndarray, np.ndarray]: 

 """Simulate the device described by the model on a design variable. 

  Args: 

  design_variable: `np.ndarray` specifying the topology of the design. 

  excite_port_idxs: A sorted sequence of ints specifying the ports to 

  excite. These values are indexed starting from 0 for port 1. The default 

  behavior is to excite only port 1. 

  wavelengths_nm: an (optional) ndarray describing the free-space 

  wavelengths for which we will perform simulations. The ndarray must be 

  rank-1. If None, the resulting simulation will be as if the user had 

  passed `self.output_wavelengths`--a rank-1 array. 

  max_parallelizm: Maximum number of parallel threads executing simulations. 

  Parallelizm is applied across excitation ports and wavelengths. If None, 

  we set the number of workers to number of excitation ports times the 

  number of wavelengths. 

  Returns: 

  s_params: A complex-valued `np.ndarray` of shape `wavelengths_nm.shape + 

  (number of excited ports, number of ports,)` corresponding to several 

  columns of a complex scattering matrix. 

  fields: A complex-valued `np.ndarray` of shape `wavelengths_nm.shape + 

  len(excite_port_idxs) + ez.shape`, containing the steady-state Ez field 

  per frequency. 

  """

These arrays can also be plotted through Matplotlib.

Hope this helps.

from ceviche-challenges.

jan-david-fischbach commented on May 4, 2024

Thanks,
I had seen those but thought I might have missed something else.
Thanks for the quick and thorough response!

from ceviche-challenges.

Convenience Functions? about ceviche-challenges HOT 2 CLOSED

Comments (2)

Related Issues (2)

Recommend Projects

React

Vue.js

Typescript

TensorFlow

Django

Laravel

D3

Recommend Topics

javascript

web

server

Machine learning

Visualization

Game

Recommend Org

Facebook

Microsoft

Google

Alibaba

D3

Tencent

	def density(self, design_variable: np.ndarray) -> np.ndarray:
	"""The combined (design + background) density distribution of the model."""

	def simulate(
	self,
	design_variable: np.ndarray,
	excite_port_idxs: Sequence[int] = (0,),
	wavelengths_nm: Optional[np.ndarray] = None,
	max_parallelizm: Optional[int] = None,
	) -> Tuple[np.ndarray, np.ndarray]:
	"""Simulate the device described by the model on a design variable.

	Args:
	design_variable: `np.ndarray` specifying the topology of the design.
	excite_port_idxs: A sorted sequence of ints specifying the ports to
	excite. These values are indexed starting from 0 for port 1. The default
	behavior is to excite only port 1.
	wavelengths_nm: an (optional) ndarray describing the free-space
	wavelengths for which we will perform simulations. The ndarray must be
	rank-1. If None, the resulting simulation will be as if the user had
	passed `self.output_wavelengths`--a rank-1 array.
	max_parallelizm: Maximum number of parallel threads executing simulations.
	Parallelizm is applied across excitation ports and wavelengths. If None,
	we set the number of workers to number of excitation ports times the
	number of wavelengths.

	Returns:
	s_params: A complex-valued `np.ndarray` of shape `wavelengths_nm.shape +
	(number of excited ports, number of ports,)` corresponding to several
	columns of a complex scattering matrix.
	fields: A complex-valued `np.ndarray` of shape `wavelengths_nm.shape +
	len(excite_port_idxs) + ez.shape`, containing the steady-state Ez field
	per frequency.
	"""