def test_indicator_and_name():
"""
Tests if the indicator and name are correctly parsed.
"""
data_line = DataLine(" N OBJ") # from the LandS.cor file.
assert_equal(data_line.indicator(), "N")
assert_equal(data_line.first_name(), "OBJ")
def _process_scenarios(self, data_line: DataLine):
if data_line.indicator() == "SC": # new scenario
scen = Scenario(data_line.first_name(), data_line.second_name(),
data_line.third_name(), data_line.first_number())
self._current_scen = scen
return
var = data_line.first_name()
constr = data_line.second_name()
value = data_line.first_number()
assert self._current_scen is not None
self._current_scen.add_modification(constr, var, value)
if data_line.has_third_name() and data_line.has_second_number():
constr = data_line.third_name()
value = data_line.second_number()
self._current_scen.add_modification(constr, var, value)
def _process_rows(self, data_line: DataLine):
indicator = data_line.indicator()
name = data_line.first_name()
assert indicator in _CONSTRAINT_SENSES
# This is a "no restriction" row, which indicates an objective function.
# There can be more than one such row, but there can only be one
# objective. We take the first such row as the objective, and then
# ignore any subsequent "no restriction" rows.
if indicator == 'N':
if self.objective_name == "":
logger.debug(f"Setting {name} as objective.")
self._objective_name = name
return
else:
self._constr_names.append(name)
self._senses.append(indicator)
self._constr2idx[name] = len(self._constr_names) - 1
def _process_bounds(self, data_line: DataLine):
"""
There are a ton of bound types, but the most common are listed below,
originally due to http://lpsolve.sourceforge.net/5.5/mps-format.htm. A
bound is specified by a two-letter type and a value b.
- LO lower bound b <= x (< +inf)
- UP upper bound (0 <=) x <= b
- FX fixed variable x = b
- FR free variable -inf < x < +inf
- MI lower bound -inf -inf < x (<= 0)
- PL upper bound +inf (0 <=) x < +inf
- BV binary variable x = 0 or 1
- LI integer variable b <= x (< +inf)
- UI integer variable (0 <=) x <= b
Raises
------
ValueError
When the bound type is not understood.
"""
if len(self._lb) != len(self.variable_names) != len(self._ub):
self._lb = np.zeros(len(self.variable_names))
self._ub = np.full(len(self.variable_names), np.inf)
bound_type = data_line.indicator()
if bound_type not in _BOUNDS_TYPES:
msg = f"Bounds of type {bound_type} are not understood."
logger.error(msg)
raise ValueError(msg)
var = data_line.second_name()
idx = self._var2idx[var]
# The value is clear from the type, and need not have been specified.
# Hence we treat these separately, and then return.
if bound_type in {"FR", "MI", "PL", "BV"}:
if bound_type == "FR": # free variable
self._lb[idx] = -np.inf
self._ub[idx] = np.inf
if bound_type == "MI": # -inf lower bound
self._lb[idx] = -np.inf
if bound_type == "PL": # +inf upper bound
self._ub[idx] = np.inf
if bound_type == "BV": # binary variable
self._lb[idx] = 0
self._ub[idx] = 1
self._types[idx] = 'B'
return
value = data_line.first_number()
if bound_type == "LO": # lower bound
self._lb[idx] = value
if bound_type == "UP": # upper bound
self._ub[idx] = value
if bound_type == "FX": # fixed variable
self._lb[idx] = value
self._ub[idx] = value
if bound_type == "LI": # integer variable, lower bound
self._lb[idx] = value
self._types[idx] = 'I'
if bound_type == "UI": # integer variable, upper bound
self._ub[idx] = value
self._types[idx] = 'I'
def test_indicator_columns(line, expected):
"""
The indicator field is the 2-3 column range (inclusive).
"""
data_line = DataLine(line)
assert_equal(data_line.indicator(), expected)