def init_classifier_impl(field_code: str, init_script: str):
if init_script is not None:
init_script = init_script.strip()
if not init_script:
from sklearn import tree as sklearn_tree
return sklearn_tree.DecisionTreeClassifier()
from sklearn import tree as sklearn_tree
from sklearn import neural_network as sklearn_neural_network
from sklearn import neighbors as sklearn_neighbors
from sklearn import svm as sklearn_svm
from sklearn import gaussian_process as sklearn_gaussian_process
from sklearn.gaussian_process import kernels as sklearn_gaussian_process_kernels
from sklearn import ensemble as sklearn_ensemble
from sklearn import naive_bayes as sklearn_naive_bayes
from sklearn import discriminant_analysis as sklearn_discriminant_analysis
from sklearn import linear_model as sklearn_linear_model
eval_locals = {
'sklearn_linear_model': sklearn_linear_model,
'sklearn_tree': sklearn_tree,
'sklearn_neural_network': sklearn_neural_network,
'sklearn_neighbors': sklearn_neighbors,
'sklearn_svm': sklearn_svm,
'sklearn_gaussian_process': sklearn_gaussian_process,
'sklearn_gaussian_process_kernels': sklearn_gaussian_process_kernels,
'sklearn_ensemble': sklearn_ensemble,
'sklearn_naive_bayes': sklearn_naive_bayes,
'sklearn_discriminant_analysis': sklearn_discriminant_analysis
}
return eval_script(
'classifier init script of field {0}'.format(field_code), init_script,
eval_locals)
def calc_formula(cls, field_code: str, formula: str,
depends_on_field_to_value: Dict[str, Any]) -> Any:
if not formula or not formula.strip():
return None
try:
return eval_script(script_title=f'{field_code} formula',
script_code=formula,
eval_locals=depends_on_field_to_value)
except ScriptError as se:
raise DocumentFieldFormulaError(field_code, formula,
depends_on_field_to_value) from se
def calc_formula(cls,
field_code: str,
formula: str,
depends_on_field_to_value: Dict[str, Any],
convert_decimals_to_floats: bool = False) -> Any:
if not formula or not formula.strip():
return None
if convert_decimals_to_floats:
depends_on_field_to_value = {c: TypedField.replace_decimals_with_floats_in_python_value_of_any_type(v)
for c, v in depends_on_field_to_value.items()} \
if depends_on_field_to_value else {}
try:
if settings.DEBUG_SLOW_DOWN_FIELD_FORMULAS_SEC:
import time
time.sleep(settings.DEBUG_SLOW_DOWN_FIELD_FORMULAS_SEC)
return eval_script(script_title=f'{field_code} formula',
script_code=formula,
eval_locals=depends_on_field_to_value)
except ScriptError as se:
raise DocumentFieldFormulaError(field_code, formula,
depends_on_field_to_value) from se
