Debugging a wrong answer¶

What to read when a model solves to the wrong number, or does not solve, in the order that finds the fault soonest. Each step needs the file, or the file and its data, and none needs a solver run you have not already paid for.

1. Check the file against the sink¶

import specsolve as sps

sps.check('dispatch.yaml', sink='highs')

check raises on a construct outside the language, and with sink= on one the solver cannot take: an sos: set on highs, which has no such concept, until Spec.expand() writes it out as binaries (checking against a sink).

2. Read the shape the build produced¶

model = sps.build('dispatch.yaml', sources)
report = model.diagnostics()
report.columns, report.rows, report.nonzeros  # 8, 4, 8
report.omissions  # rows a constraint declared and did not build
report.sparse_parameters  # parameters whose table is short of their coordinates

A count smaller than you expected is a mask, or a table with a row missing. omissions names the constraint, sparse_parameters the parameter; which one you have is the difference between a where: you wrote and a row you lost (diagnostics).

3. Read the row that is wrong¶

print(model.row('power_balance', snapshot=2))
# power_balance[snapshot=2]: +1 p[2, wind] +1 p[2, gas] == 180

The line is the row as the solver got it: every coefficient the data produced, and no term for a variable a where: removed. Here solar is absent because its p_max is 0.0. A term you expected and do not see is a mask; a coefficient you did not expect is the data (reading one row).

4. When the solve is infeasible¶

result = model.solve()
result.status, result.termination_condition  # 'warning', 'infeasible'
result.has_primal  # False: nothing to read, and every reader raises

There is no IIS (irreducible infeasible subsystem) read-back. Locate the fault instead with a slack: add a variable to the balance row, minimise it, and read where it is nonzero. The feasibility model is that file for a dispatch. Then read the row at a snapshot the slack lands on, as in step 3.

5. When the number is wrong and the rows look right¶

Rows that read right and a number you still believe is wrong mean the file says something other than what you meant. Render it as math and read the constraint as written: typeset.

6. When a loop of re-solves is slow¶

Run the loop once with each keep= and read the clock the package keeps. kept confirms the request was honoured rather than quietly downgraded:

for keep in ('solver', 'progress'):
    model = sps.build('dispatch.yaml', sources)
    for numbers in walk:
        assert model.update(numbers).solve(keep=keep).kept in {keep, 'nothing'}
    print(keep, model.diagnostics().seconds['solve'])

Take the faster one. 'nothing' on every iteration means each update moved a mask and the model was rebuilt, so the loop is paying for the build, not the solve (re-solving with new numbers).