Model and modelstack

The escape.core.model module provides methods to create models objects.

Model is a container for a kernel and corresponding experimental data. It is responsible for calculating residuals and cost function, which are used by optimizers for curve fitting. The model has two settings: weight_type-“none” or “data” and residuals_scale - “none”, “log”, “q2” and “q4”.

The latter defines how to calculate residuals, with logarithmic scale or without and the former indicates which weights will be used to calculate cost, no weights or weights obtained from the data object.

Modelstacks are used when several models should be optimized.

escape.core.model.model(name, obj, data_obj data, weight_type=u'data', residuals_scale=u'none')

Creates instance of model_obj.

Parameters:
name: string

Model name

kernel: kernel_obj or functor_obj

Kernel object, which model will use for intensity calculations.

data: data_obj

Experimental data for the calculation of cost function

weight_type: string, [‘none’, ‘data’]

Sets weight type for calculation of residuals

residuals_scale: string, [‘none’, ‘log’, ‘q2’, ‘q4’]

Sets scale for residuals, none, logarithmic, Q^2 or Q^4

Returns:

instance of model_obj

escape.core.model.modelstack(name, model=None)

Creates instance of modelstack_obj.

Parameters:
name: string

Modelstack name.

model: single model instance or list of models

Models to add to modelstack.

Returns:

instance of modelstack_obj

class escape.core.model.model_obj
data
data_length
dof
domain_size
last_cost
name
num_of_params
parameter(self, size_t i)
residuals
shake(self)
simulation
class escape.core.model.modelstack_obj
add(self, model_obj mdl)
data_length
dof
erase(self, size_t idx)
erase_all(self)
model(self, size_t idx)
name
num_of_params
parameter(self, size_t i)
set(self, size_t idx, model_obj mdl)
set_data(self, datastack_obj data)
shake(self)