Interaction matrix

The first test on interaction matrix is based on a visual check of the matrix with the command: im.displayIM() where "im" is an LgswInteractionMatrix object.

The noise propagation coefficient can calculated as:

np.diag(np.linalg.pinv(np.dot(im.getInteractionMatrix().T,im.getInteractionMatrix())))*(1e9)**2

Interaction Matrix 20180221_234506 on SX side produce these coefficients for modes from 2 to 10 in (nm rms/slopes)^2: [ 63111, 29969 , 61451, 27634, 28181, 23911, 23293, 18151]

The noise propagation coefficients times the noise estimation on the WFS should give the Modal Residual.

Inversion of the Interaction Matrix, building the Reconstructor

The inversion of the Lgsw Interaction Matrix produce the Lgsw Reconstructor.

The singular values of the SVD has to be distributed in a factor 10, more or less. To get the singular values after the Pseudo Inversion use the function: im.getSingularValues()

The product of the Reconstructor and a vector of constant slopes has to return mainly Tip and Tilt values and some small numbers on the higher modes. See DayTime20180222 for more details.

Test of the Reconstructor in CL with disturbance turbulence

Look HowToPerformArgosAoLoopInDayTime to get ready for the test.

Before close the AO loop set a disturbance and enable it. List of Disturbances in AoLoopDisturbances.

Before close the AO loop also set the new combined reconstructor.

Close the loop, ramp the gain, wait for TS convergence (in case you are using TS) and then acquire some snapshots.

Once you have some snapshots it is possible to analyze with the argos_SIDE_snapshot_analyzer, for example:

tnnew=terminal.analyzer('20180222_010121')
tnnew.modalPlot()

tns=terminal.set('20180222_002107','20180222_010832')
tns.tWikiLoopLog()

TN	AO Gain	AO CL	TT Res. WF [nm rms]	HO Res. WF [nm rms]	AO rec	DIMM ["]	JCL	PCL	Notes
20180222_002107	1.2,0.5,0.4	T	88.3177	43.2277	20180221_235700	-1	T	F
20180222_002135	1.2,0.5,0.4	T	94.55	43.2824	20180221_235700	-1	T	F
20180222_002351	1.4,0.5,0.4	T	73.8316	56.0694	20180221_235700	-1	T	F
20180222_002408	1.4,0.5,0.4	T	72.9462	56.1992	20180221_235700	-1	T	F
20180222_004941	1.4,0.5,0.4	T	47.7592	64.1223	20180221_194600	-1	T	F
20180222_010832	1.4,0.5,0.4	T	54.8768	49.5231	20180221_194600	-1	T	F

TT Res. WF [nm rms] is the WaveFront Error residual measured by the Tip/Tilt WFS (the Pyramid WFS in this case).

HO Res. WF [nm rms] is the WFE residual measured by the LGSW.

It is useful to compare new snapshots with old acquisition from previous runs, or perform new measures with old reconstructors.