def build_product_from_data(self, product_data):
""" Custom object builder from stored product data.
"""
product_name = product_data["name"]
def collect_product_comp(component_name):
""" Lookup component based on the product name and the component
name.
"""
# FIXME: support multiple key filters in get_objects_by_type so
# that we can have a key containing both the component_name and the
# target_product
key = {'target_product': product_name}
objects = self.get_objects_by_type('product_components',
filter_by=key)
candidates = [obj for obj in objects if obj.name == component_name]
if len(candidates) == 0:
available_obj = [obj.name for obj in objects]
msg = ("Failed to load one of the product components ({}) from"
" all product components of the datasource ({}). Did "
"you populate the product component objects before the "
"products?".format(component_name, available_obj))
logger.exception(msg)
raise KeyError(msg)
else:
return candidates[0]
comp_names = product_data.pop('product_components')
product_data['product_components'] = [
collect_product_comp(comp) for comp in comp_names
]
return Product(**product_data)
def build_product(self, allow_ui=True):
""" Create an instance of a Product from the characteristics and
component descriptions of the builder.
"""
try:
if not self.expert_mode:
self.expand_product_attributes()
# Collect components
components = self.lookup_components()
# Collect component concentration expressions
concentration_exps = [comp.concentration_exps
for comp in self.component_descs]
if self.add_strip and not self.expert_mode:
strip_desc = self.strip_component_descs[0]
strip_expression = strip_desc.concentration_exps
concentration_exps.append(strip_expression)
# Collect assays:
assay_names = assay_names_from_instances(
self.component_assay_names
)
if self.add_strip and not self.expert_mode:
assay_names.append(STRIP_COMP_NAME)
# Build product instance
prod = Product(
name=self.name, product_type=self.product_type,
description=self.description,
pI=self.pI, product_components=components,
product_component_concentration_exps=concentration_exps,
product_component_assays=assay_names
)
if self.add_strip and not self.expert_mode:
self.datasource.set_object_of_type("product_components",
self.strip_component)
except Exception as e:
msg = ("Failed to create new product. Please try again or report "
"this issue to the software provider if the problem "
"persists, providing the log file of this session.")
details = "\nError was {}.".format(e)
logger.exception(msg + details)
if allow_ui:
error(None, msg)
prod = None
return prod
]
adapter = build_array_adapter(index_name, column_names, row_names)
return adapter
def _param_formula_str_default(self):
param_formula = """The following parameters get combined into an effective Langmuir model according to:
ka(pH) = ka0 + ka1 * pH + ka2 * pH^2 + ka3 * pH^3
kd(pH) = kd0 + kd1 * pH + kd2 * pH^2 + kd3 * pH^3
qmax(pH) = qmax0 + qmax1 * pH + qmax2 * pH^2 + qmax3 * pH^3
""" # noqa
return param_formula
if __name__ == '__main__':
# Create Product for passing component names
from kromatography.model.tests.example_model_data import PRODUCT_DATA, \
Prod001_comp1, Prod001_comp2, Prod001_comp3
from kromatography.model.product import Product
product_components = [Prod001_comp1, Prod001_comp2, Prod001_comp3]
prod = Product(product_components=product_components, **PRODUCT_DATA)
# Build a model you want to visualize:
extl = ExternalLangmuir(len(prod.product_component_names),
component_names=prod.product_component_names)
# Build model view, passing the model as a model and make a window for it:
extl_model_view = ExternalLangmuirView(model=extl)
extl_model_view.configure_traits()
""" Test script modifying the user datasource.
"""
import logging
from kromatography.model.product import Product
logger = logging.getLogger(__name__)
# Example of changing the content of the datasource by adding a new product
new_prod = Product(name="PROD", product_type="Mab")
user_datasource.set_object_of_type("products", new_prod) # noqa
logger.warning("Opening new product {} in central pane...".format(new_prod))
show_label=False,
editor=self._tabular_editor), ),
label="Transport Parameters",
show_border=True,
),
),
# Relevant when used as standalone view:
resizable=True,
buttons=OKCancelButtons,
default_button=OKButton,
title="Configure General Rate model")
return view
def _vector_attributes_default(self):
return ['film_mass_transfer', 'pore_diffusion', 'surface_diffusion']
if __name__ == '__main__':
# Create Product for passing component names
from kromatography.model.tests.example_model_data import PRODUCT_DATA
from kromatography.model.product import Product
prod = Product(**PRODUCT_DATA)
# Build a model you want to visualize:
grm = GeneralRateModel(len(prod.product_component_names),
component_names=prod.product_component_names)
# Build model view, passing the model as a model and make a window for it:
grm_model_view = GeneralRateModelView(model=grm)
grm_model_view.configure_traits()
}
NATIVE_PRODUCT_COMPONENT_DATA = {
'target_product': 'Prod001',
'name': 'Native',
'molecular_weight': UnitScalar(18.8, units=gram_per_mol),
'extinction_coefficient': UnitScalar(0.75,
units=extinction_coefficient_unit),
}
Prod001_comp1 = ProductComponent(**ACIDIC_1_PRODUCT_COMPONENT_DATA)
Prod001_comp2 = ProductComponent(**ACIDIC_2_PRODUCT_COMPONENT_DATA)
Prod001_comp3 = ProductComponent(**NATIVE_PRODUCT_COMPONENT_DATA)
Prod001 = Product(
product_components=[Prod001_comp1, Prod001_comp2, Prod001_comp3],
**PRODUCT_DATA)
Prod001_with_strip, Prod001_strip = add_strip_to_product(Prod001)
PRODUCT_DATA2 = {
'name':
'Mab001',
'product_type':
'MAB',
'product_component_assays':
['CEX_Acidic', 'CEX_Main', 'CEX_Basic', 'SEC_Monomer', 'SEC_Dimer'],
'product_component_concentration_exps': [
'product_concentration * SEC_Monomer * CEX_Acidic / 10000',
'product_concentration * SEC_Monomer * CEX_Main / 10000',
'product_concentration * SEC_Monomer * CEX_Basic / 10000',