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Dataset structure
The dataset is an essential concept of the ASpecD framework, and hence of the FitPy package.
Developers frequently need to get an overview of the structure of the dataset as defined in the FitPy package. Whereas the API documentation of fitpy.dataset.CalculatedDataset
and fitpy.dataset.CalculatedDatasetLHS
provides a lot of information, a simple and accessible presentation of the dataset structure is often what is needed.
Therefore, the structures of the dataset classes defined in fitpy.dataset
are provided below in YAML format, automatically generated from the actual source code.
Calculated dataset
class: fitpy.dataset.CalculatedDataset
data:
calculated: true
data:
type: numpy.ndarray
dtype: float64
array: []
axes:
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
residual:
type: numpy.ndarray
dtype: float64
array: []
metadata:
calculation:
type: ''
parameters: {}
model:
type: ''
parameters: {}
data:
id: ''
label: ''
result:
parameters: null
success: false
error_bars: false
n_function_evaluations: 0
n_variables: 0
degrees_of_freedom: 0
chi_square: 0.0
reduced_chi_square: 0.0
akaike_information_criterion: 0.0
bayesian_information_criterion: 0.0
variable_names: []
covariance_matrix:
type: numpy.ndarray
dtype: float64
array: []
initial_values: []
message: ''
history: []
analyses: []
annotations: []
representations: []
id: ''
label: ''
references: []
tasks: []
_origdata:
calculated: true
data:
type: numpy.ndarray
dtype: float64
array: []
axes:
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
residual:
type: numpy.ndarray
dtype: float64
array: []
_package_name: fitpy
_history_pointer: -1
Calculated dataset LHS
class: fitpy.dataset.CalculatedDatasetLHS
data:
calculated: true
data:
type: numpy.ndarray
dtype: float64
array: []
axes:
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
residual:
type: numpy.ndarray
dtype: float64
array: []
metadata:
calculation:
type: ''
parameters: {}
model:
type: ''
parameters: {}
data:
id: ''
label: ''
result:
parameters: null
success: false
error_bars: false
n_function_evaluations: 0
n_variables: 0
degrees_of_freedom: 0
chi_square: 0.0
reduced_chi_square: 0.0
akaike_information_criterion: 0.0
bayesian_information_criterion: 0.0
variable_names: []
covariance_matrix:
type: numpy.ndarray
dtype: float64
array: []
initial_values: []
message: ''
lhs:
samples: null
discrepancy: null
results: []
history: []
analyses: []
annotations: []
representations: []
id: ''
label: ''
references: []
tasks: []
_origdata:
calculated: true
data:
type: numpy.ndarray
dtype: float64
array: []
axes:
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
- quantity: ''
symbol: ''
unit: ''
label: ''
values:
type: numpy.ndarray
dtype: float64
array: []
index: []
residual:
type: numpy.ndarray
dtype: float64
array: []
_package_name: fitpy
_history_pointer: -1