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Tue Sep 10 15:41:37 2019, aaron, Update, IOO, WFS measurements 
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Wed Sep 11 10:26:56 2019, aaron, Update, IOO, WFS measurements
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Wed Sep 11 14:37:43 2019, aaron, Update, IOO, WFS measurements 
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Thu Sep 12 12:42:31 2019, aaron, Update, IOO, WFS measurements 
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Fri Sep 13 10:36:03 2019, aaron, Update, IOO, WFS measurements 
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Mon Sep 16 12:38:59 2019, aaron, Update, IOO, WFS measurements
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Thu Oct 3 11:38:35 2019, aaron, Update, IOO, WFS measurements
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Mon Sep 30 13:20:55 2019, aaron, Update, IOO, shot noise measurement
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Fri Sep 13 10:53:40 2019, aaron, Update, IOO, WFS loop measurements
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Mon Sep 16 05:08:04 2019, rana, Update, IOO, WFS loop measurements 
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Mon Sep 16 11:55:58 2019, rika, Update, IOO, WFS loop measurements
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Tue Sep 17 09:41:48 2019, gautam, Update, IOO, WFS loop measurements
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Tue Sep 17 10:47:44 2019, rika, Update, IOO, WFS loop measurements
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Wed Sep 18 14:45:52 2019, rika, Update, IOO, WFS loop measurements
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Tue Sep 17 10:34:48 2019, aaron, Update, IOO, WFS loop measurements
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Tue Oct 8 20:39:42 2019, aaron, Update, IOO, WFS loop measurements
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Wed Oct 9 09:37:28 2019, aaron, Update, IOO, WFS loop measurements
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Message ID: 14878
Entry time: Mon Sep 16 05:08:04 2019
In reply to: 14876
Reply to this: 14880
14887
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Author: |
rana |
Type: |
Update |
Category: |
IOO |
Subject: |
WFS loop measurements |
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not need to use DTT. I'm attaching some half-finished notebooks that give the gist.
- Download the data with NDS2
- Downsample the data for ease of use.
- save the data as hdf5 for easy loading later.
- demodulate the data at the specified frequencies.
That's it! Now you have the complex, single frequency TFs. Next you invert the matrix. |
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Get some ASC data - Calculate Sensing Matrix \n",
"### also make the radar plots"
]
},
... 327 more lines ...
|
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Get some ASC data - Calculate Sensing Matrix \n",
"### also make the radar plots"
]
},
... 325 more lines ...
|