Merge & Center and Merge Cells kept only the upper-left value, but
Merge Across left the other values of each row in place, hidden under
the merge and still counted: with 1 2 / 3 4 in A1:B2, SUM(A1:B2) stayed
10 after Merge Across, where Excel gives 4. Each row's merged area now
keeps only its first value, as the other merges do.
home.manageRules took the number of rules once, before deleting, so
{"delete":0,"moveUp":1} with two rules swapped past the end of the
shortened list and panicked (index out of bounds; the session's guard
kept the workbook). The count is now taken after each step.
apply_filter cloned and sorted the column's numbers for every row it tested,
O(n^2 log n). The threshold is now computed once per criterion with the other
column stats. Adds a test for top/bottom items and percent.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ut3hr3a13szpQdQ7gbYbfc
Builds on the Solver of #327. data.solver takes reports: [answer, limits]
and writes them on new sheets before the model's sheet once a solution
is found. The Answer report lists the objective and variable cells with
their original and final values and each constraint's value, formula,
status (Binding or Not Binding) and slack; cells are named by the
nearest labels to their left and above. The Limits report minimises and
maximises each variable with the others held at the solution, under the
model's constraints, and gives the objective at both ends (Simplex LP
and GRG Nonlinear, without integer constraints).
data.solverReport writes the reports for a given solution and model,
so data.solver's result (which now carries the original values and the
model) can be passed to it as is. The Solver Results dialog offers the
two reports; they are written after Keep Solver Solution or Restore
Original Values.
Builds on the Solver of #327. method: evolutionary runs a genetic search
for models that aren't smooth: tournament selection, blend crossover and
Gaussian mutation inside the variable bounds, feasibility-first ranking
and integer rounding, then a compass search around the best member. It
stops when the population converges, when the best member stops
improving for a number of generations, or at the evaluation budget. A
seeded generator makes runs repeatable. Population size, mutation rate,
random seed, convergence and Require Bounds are options; the method and
its options are saved in the hidden solver_* names. The Solver
Parameters dialog offers the method.
Without a password, file.open returns an error carrying
io::PASSWORD_REQUIRED (never a dialog). A decrypted workbook gets no save
path, so Save never replaces the encrypted original.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Brandon Thomas