ngspice/tests/regression/sens/sens-dc-1.cir

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* test "sens dc"
* The "sens" analysis does express "sensitivity" as
* S = (d out) / (d parameter)
* instead of the normalized
* S = ((d out)/out) / ((d parameter)/parameter)
*
* here:
* v(1) = (R / m_R) * (m_i1 * i1)
*
* S[R] = (d v(1))/(d R) = m_i1 * i1 / m_R = 42m
* S[i1] = (d v(1))/(d i1) = m_i1 * R1 / m_R = 1k
* S[m_R] = (d v(1))/(d m_R) = -R * i1 *m_i1/m_R^2 = -42
* S[m_i1] = (d v(1))/(d m_i1) = R * i1 / m_R = 42
i1 0 1 dc=42mA
r1 1 0 1k
.control
* express our "golden" expectations:
setplot new
set gold = $curplot
let i1 = 1k
let i1_m = 42.0
let r1 = 42m
let r1_m = -42.0
let r1_scale = 42.0
* run a "sens" analysis
sens v(1) dc
strcmp __flag $curplot $gold
if $__flag = 0
echo "ERROR: sens failed to execute"
quit 1
end
* compare results with "golden" expectation
define mismatch(a,b,err) abs(a-b)>err*abs(b)
let total_count = 0
let fail_count = 0
foreach n i1 i1_m r1 r1_m r1_scale
set n_test = "$n"
set n_gold = "{$gold}.$n"
if mismatch($n_test, $n_gold, 1e-3)
let s_test = $n_test
let s_gold = $n_gold
echo "ERROR, test failure, s[$n] = $&s_test but should be $&s_gold"
let fail_count = fail_count + 1
end
let total_count = total_count + 1
end
if fail_count > 0
echo "ERROR: $&fail_count of $&total_count tests failed"
quit 1
else
echo "INFO: $&fail_count of $&total_count tests failed"
quit 0
end
.endc
.end