Results and data

Every analysis returns a Result - the numbers MC9 wrote to its numeric output - with helpers for the things you normally read off the screen with cursors.

r = c.ac(1, 2e7, 801, ["db(v(Ua)/v(Ue))", "ph(v(Ua)/v(Ue))"])
r.columns                       # ['F', 'db(v(Ua)/v(Ue))', 'ph(v(Ua)/v(Ue))']
r.x                             # first column (frequency)
r["db(v(Ua)/v(Ue))"]            # a column as a list of floats

Reading values

Method	Meaning
r.value_at(col, x)	y at x, interpolated (in log-x for wide AC sweeps, linear otherwise)
r.cross(col, level, edge=None)	all x where the curve crosses level; edge="rising" or "falling"
r.peak(col, xmin, xmax) / r.trough(...)	(x, y) of the maximum / minimum in a window
r.amplitude(col, xmin, xmax)	(max - min) / 2, handy for sine amplitudes in steady state
r.mean(col, xmin, xmax)	average
r.to_csv(path)	export

g = "db(v(Ua)/v(Ue))"
f0, g0 = r.peak(g)                              # centre frequency and gain
f_low = [f for f in r.cross(g, g0 - 3) if f < f0][-1]

Several runs

Temperature lists and stepping produce several tables; they are in r.runs (each a Run with the same helpers and a label):

r = c.dc("V1", 0, 1, 0.01, ["i(D1)"], temp=[-25, 0, 25, 50, 75])
for run in r.runs:
    print(run.label, run.value_at("i(D1)", 0.7))

A Result behaves like its first run (r["col"], r.peak(...)).

Operating point

op = c.op()
op.nodes                 # {'IN': 0.0, 'OUT': 6.667, '3': 0.695}   (named nodes, numbers for the rest)
op.v("out")              # case-insensitive
op["Q1"]["IC"]           # device values: IB IC VBE VCE BETADC GM RPI RO CPI CMU FT ... PD (power)
op["R3"]["PD"], op["R3"]["Ir"]

Number format

MC9 prints values with SI suffixes (1.5K, 4.7u, 2MEG); the parser converts them. A cell that MC9 prints as N/A (for example the phase at DC) becomes nan.