mat_dp_core.constraints

There are three more expressive Constraints: GeConstraint, LeConstraint, and EqConstraint.
Each of these can be used to express the conditions of a system in the form of a constraint expression.

Constraint Expressions

Overview:

A constraint expression permits more advanced constraints to be defined according to one or more weighted variables.

If a constraint needs to be expressed in terms of another process, then constraint expressions can be particularly useful.
Hint: Constraint expressions are written just the same as objective functions.

Example Code:

from mat_dp_core import Resources, Processes, GeConstraint

r = Resources()
water = r.create(name="fresh water", unit="litres")

p = Processes() 
pump = p.create("water pump", (water, 100))
valve = p.create("water valve", (water, 40))

# Constraint created:
constraint = GeConstraint("weighted pump and valve GeConstraint", 5 * pump + 3 * valve, 5)

# Expression is:
# 5 * pump + 3 * valve

GeConstraint()

Summary:
The Ge ('greater than or equal to') Constraint class can be used to assert a given process runs at least n times.

Parameters:

• name
  A string name for this constraint

• weighted_processes process variable, or a process expression
  The process variable to be constrained, or a valid process expression.

• bound
  A float value representing the number of cycles this process must be greater than or equal to.

Return Type: GeConstraint

Location: constraints.py - class GeConstraint

Example Code:

from mat_dp_core import Resources, Processes, GeConstraint

r = Resources()
water = r.create(name="fresh water", unit="litres")

p = Processes() 
pump = p.create("water pump", (water, 100))

# Constraint created:
constraint = GeConstraint("minimum pump cycles", pump, 5)

# For display purposes:
print(constraint)
"""
>>> <GeConstraint: minimum pump cycles | Equation:- water pump <= -5>
"""

---

LeConstraint()

Summary:
The Le ('less than or equal to') Constraint class can be used to assert a given process runs at most n times.

Parameters:

• name
  A string name for this constraint

• weighted_processes process variable, or a process expression
  The process variable to be constrained, or a valid process expression.

• bound
  A float value representing the number of cycles this process must be less than or equal to.

Return Type: LeConstraint

Location: constraints.py - class LeConstraint

Example Code:

from mat_dp_core import Resources, Processes, LeConstraint

r = Resources()
engine = r.create(name="engine", unit="ea")

p = Processes() 
factory = p.create("engine factory", (engine, 1))

# Factory can produce no more than 50 engines
constraint = LeConstraint("maximum", factory, 50)

# For display purposes:
print(constraint)
"""
>>> <LeConstraint: maximum | Equation:engine factory <= 50>
"""

---

EqConstraint()

Summary:
The Eq ('equal to') Constraint class can be used to assert a given process runs exactly n times.

Parameters:

• name
  A string name for this constraint

• weighted_processes process variable, or a process expression
  The process variable to be constrained, or a valid process expression.

• bound
  A float value representing the number of cycles this process must run.

Return Type: EqConstraint

Location: constraints.py - class EqConstraint

Example Code:

from mat_dp_core import Resources, Processes, EqConstraint

r = Resources()
sandwich = r.create(name="sandwich", unit="ea")

p = Processes() 
cornerShop = p.create("corner shop", (sandwich, -1))

# corner shop always consumes 20 sandwiches
constraint = EqConstraint("uses exactly 20 sandwiches", cornerShop, 20)

# For display purposes:
print(constraint)
"""
>>> <EqConstraint: uses exactly 20 sandwiches | Equation:corner shop == 20>
"""

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