[1/6] Add inhibitory_nts, excluded_nts, lambda_max, syn_weight_measure as kwargs

[alexanderbates]

Surface inhibitory_nts, excluded_nts, lambda_max, syn_weight_measure as kwargs

Replaces the hardcoded NEG_NEUROTRANSMITTERS module constant with two
explicit constructor arguments so that the library no longer pre-empts
the user's neurotransmitter sign assignment:

• inhibitory_nts: pre-neuron top_nt values to negate when signed=True
  (required when signed=True; raises ValueError otherwise).
• excluded_nts: pre-neuron top_nt values to drop entirely from W,
  independent of signed=True/False. Useful for transmitter classes
  whose net sign at a given target depends on the receptor mix and so
  cannot be assigned a single sign safely.

Adds lambda_max as a constructor argument (default 0.99 for backwards
compatibility). _normalize_W now always rescales to lambda_max exactly
rather than only capping when the natural eigenvalue exceeds it, so the
parameter is a true control knob over leading-mode amplification rather
than just a stability ceiling. The amplification of the leading mode in
(I - W_rescaled)^-1 is 1 / (1 - lambda_max), so 0.99 gives ~100x and
0.5 gives ~2x.

Surfaces syn_weight_measure ('count' or 'norm') as a constructor
argument and changes the default from 'norm' to 'count'. Fixes a
pre-existing bug in _create_sparse_W: the signed=True path negated the
'count' column unconditionally, but the matrix was populated from the
column named by syn_weight_measure (default 'norm'), so the signed flag
silently produced the same matrix as signed=False. The negation now
applies to the column actually consumed. An inline comment notes that
flipping signs on 'norm' breaks the column-sums-to-1 interpretation, so
'count' is the more natural choice in signed mode.

Sign preservation: _build_influence_dataframe now keeps the real part
of the steady-state vector in signed mode rather than always taking the
magnitude, so net-inhibited targets carry a negative score.

Validates lambda_max in (0, 1) and syn_weight_measure in {'count',
'norm'}. When signed=True or excluded_nts is set, the SQLite meta
table must include a 'top_nt' column or _create_sparse_W raises.

[ZakiAjabi]

I would write instead: lambda_max / max(eigenvalue(W))