AFL.automation.mixing.MassBalance#

Functions

enforce_units(value, unit_type)

Ensure that a number has units and convert to the default_units

lsq_linear(A, b[, bounds, method, tol, ...])

Solve a linear least-squares problem with bounds on the variables.

Classes

Any(*args, **kwargs)

Special type indicating an unconstrained type.

Bounds([lb, ub, keep_feasible])

Bounds constraint on the variables.

Context(name)

Inherited by Pipeline to allow for context manager abuse

Driver(name[, defaults, overrides, useful_links])

MassBalance([name, minimum_volume])

MassBalanceBase()

MassBalanceDriver([overrides])

PipetteAction(source, dest, volume[, ...])

Solution(name[, total_mass, total_volume, ...])

class AFL.automation.mixing.MassBalance.MassBalanceBase[source]#
__init__()[source]#
property components: Set[str]#
property stock_components: Set[str]#
property target_components: Set[str]#
mass_fraction_matrix() → ndarray[source]#
make_target_names(n_letters: int = 2, components=None, name_map: Dict | None = None)[source]#
balance(tol=0.05)[source]#
class AFL.automation.mixing.MassBalance.MassBalance(name='MassBalance', minimum_volume='20 ul')[source]#
__init__(name='MassBalance', minimum_volume='20 ul')[source]#
property stock_components: Set[str]#
property target_components: Set[str]#
class AFL.automation.mixing.MassBalance.MassBalanceDriver(overrides=None)[source]#
defaults = {'minimum_volume': '20 ul', 'stocks': [], 'targets': [], 'tol': 0.001}#
__init__(overrides=None)[source]#
property stock_components: Set[str]#
property target_components: Set[str]#
process_stocks()[source]#
process_targets()[source]#
add_stock(solution: Dict, reset: bool = False)[source]#
add_target(target: Dict, reset: bool = False)[source]#
reset_stocks()[source]#
reset_targets()[source]#
balance()[source]#