408 lines
52 KiB
Plaintext
408 lines
52 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d1bb781f-f286-44cf-a3e3-181e06281487",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"\"\"\"\n",
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"INIT:connect to keithley\n",
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"- has to be run before anything else\n",
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"- the 'keithley' variable represents the device\n",
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"- use keithley.write(), keithley.query(), etc to interact\n",
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"\"\"\"\n",
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"\n",
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"import pyvisa\n",
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"from time import sleep\n",
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"from matplotlib import pyplot as plt\n",
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"import numpy as np\n",
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"import keithley\n",
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"import file_io\n",
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"import measure\n",
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"\n",
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"keithley = keithley.init_keithley()\n",
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"keithley.write(\"format.data = format.ASCII\")\n",
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"print(keithley.query(\"*IDN?\"))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "52743b4a-7e0c-4fb5-ace4-4328e5e18940",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"measure.measure_count(keithley, count=100, interval=0.05, beep_done=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "c6a08ceb-1fe9-4517-af74-40a5006de1e8",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"67"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Task exception was never retrieved\n",
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"future: <Task finished name='Task-5' coro=<_ServiceBrowserBase._async_start_query_sender() done, defined at /usr/lib/python3.10/site-packages/zeroconf/_services/browser.py:442> exception=NotRunningException()>\n",
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"Traceback (most recent call last):\n",
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" File \"/usr/lib/python3.10/site-packages/zeroconf/_services/browser.py\", line 445, in _async_start_query_sender\n",
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" await self.zc.async_wait_for_start()\n",
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" File \"/usr/lib/python3.10/site-packages/zeroconf/_core.py\", line 507, in async_wait_for_start\n",
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" raise NotRunningException\n",
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"zeroconf._exceptions.NotRunningException\n"
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]
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}
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],
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"source": [
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"keithley.write(\"format.data = format.DREAL\\nformat.byteorder = format.LITTLEENDIAN\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "4ffc1758-a27e-4d4f-87ad-d969da05dbad",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.000000e+00, 5.000000e-02, 1.000000e-01, 1.500000e-01, 2.000000e-01, 2.500000e-01, 3.000000e-01, 3.500000e-01, 4.000000e-01, 4.500000e-01, 5.000000e-01, 5.500000e-01, 6.000000e-01, 6.500000e-01, 7.000000e-01, 7.500000e-01, 8.000000e-01, 8.500000e-01, 9.000000e-01, 9.500000e-01, 1.000000e+00, 1.050000e+00, 1.100000e+00, 1.150000e+00, 1.200000e+00, 1.250000e+00, 1.300000e+00, 1.350000e+00, 1.400000e+00, 1.450000e+00, 1.500000e+00, 1.550000e+00, 1.600000e+00, 1.690891e+00, 1.710923e+00, 1.750000e+00, 1.800000e+00, 1.850000e+00, 1.900000e+00, 1.950000e+00, 2.000000e+00, 2.050000e+00, 2.100000e+00, 2.150000e+00, 2.200000e+00, 2.250000e+00, 2.300000e+00, 2.350000e+00, 2.420332e+00, 2.450000e+00, 2.500000e+00, 2.550000e+00, 2.600000e+00, 2.650000e+00, 2.700000e+00, 2.750000e+00, 2.820553e+00, 2.890843e+00, 2.910875e+00, 2.950000e+00, 3.000000e+00, 3.050000e+00, 3.100000e+00, 3.150000e+00, 3.200000e+00, 3.250000e+00, 3.300000e+00, 3.350000e+00, 3.400000e+00, 3.450000e+00, 3.500000e+00, 3.550000e+00, 3.600000e+00, 3.650000e+00, 3.700000e+00, 3.750000e+00, 3.800000e+00, 3.850000e+00, 3.900000e+00, 3.950000e+00, 4.000000e+00, 4.050000e+00, 4.100000e+00, 4.150000e+00, 4.200000e+00, 4.250000e+00, 4.300000e+00, 4.350000e+00, 4.400000e+00, 4.450000e+00, 4.500000e+00, 4.550000e+00, 4.600000e+00, 4.650000e+00, 4.700000e+00, 4.750000e+00, 4.800000e+00, 4.850000e+00, 4.900000e+00, 4.950000e+00\n",
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"\n",
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"[100.0]\n"
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]
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}
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],
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"source": [
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"print(keithley.query(f\"print(smua.nvbuffer1.n)\"))\n",
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"keithley.write(\"format.data = format.ASCII\")\n",
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"buffer = keithley.query_ascii_values(f\"printbuffer(1, smua.nvbuffer1.n, smua.nvbuffer1.timestamps)\") #, datatype='d', container=np.array)\n",
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"print(buffer)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "b7c57345-13ff-4f52-a4b0-58561dcab0a8",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"readings: [ 4.974127e-10 -1.418591e-12 -1.573563e-12 -1.728535e-12 -1.704693e-12\n",
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" -1.847744e-12 -1.931190e-12 -1.788139e-12 -1.871586e-12 -2.169609e-12\n",
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" -2.074242e-12 -1.895428e-12 -1.895428e-12 -1.776218e-12 -1.990795e-12\n",
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" -1.788139e-12 -1.811981e-12 -1.657009e-12 -1.573563e-12 -2.396107e-12\n",
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" -2.515316e-12 -2.765656e-12 -2.825260e-12 -3.147125e-12 -2.300739e-12\n",
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" -2.825260e-12 -3.278255e-12 -5.257130e-12 -6.818771e-12 -8.916855e-12\n",
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" -7.712841e-12 6.437302e-12 -1.142025e-11 -1.206398e-11 -4.649043e-10\n",
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" -3.427613e-09 -2.460408e-09 -2.340376e-09 -1.306653e-10 1.496077e-11\n",
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" 2.933741e-11 1.953280e-09 8.579970e-10 9.226799e-12 -1.095533e-11\n",
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" -2.508163e-11 -2.776039e-09 -8.686423e-09 4.935264e-12 1.246929e-11\n",
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" 3.225744e-09 2.814472e-09 1.877034e-09 2.229273e-09 1.713574e-09\n",
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" 8.355618e-10 -4.332781e-10 5.896091e-11 5.762577e-11 8.129537e-09\n",
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" 4.044378e-09 1.771629e-09 7.849216e-10 4.098892e-10 3.390551e-10\n",
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" 2.956390e-10 3.033876e-10 1.716256e-10 1.463890e-11 -5.078316e-12\n",
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" -6.949902e-12 -8.106232e-12 -6.473065e-12 -4.506111e-12 4.919767e-11\n",
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" 3.052297e-08 1.161162e-08 -9.892106e-09 -3.613818e-09 -5.004287e-09\n",
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" -2.015829e-11 -4.183054e-11 -1.810908e-10 -2.042532e-10 -3.516316e-10\n",
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" 5.099773e-11 1.921976e-08 -1.256589e-08 -4.242897e-10 -1.358986e-12\n",
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" -3.445148e-12 -3.838539e-12 -4.184246e-12 -7.402897e-12 -2.840877e-10\n",
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" -2.872229e-10 -2.730966e-10 -1.134396e-10 -4.376173e-11 -3.576279e-14], \n",
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"timestamps: [0. 0.05 0.1 0.15 0.2 0.25 0.3 0.35\n",
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" 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75\n",
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" 0.8 0.85 0.9 0.95 1. 1.05 1.1 1.15\n",
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" 1.2 1.25 1.3 1.35 1.4 1.45 1.5 1.55\n",
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" 1.6 1.690891 1.710923 1.75 1.8 1.85 1.9 1.95\n",
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" 2. 2.05 2.1 2.15 2.2 2.25 2.3 2.35\n",
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" 2.420332 2.45 2.5 2.55 2.6 2.65 2.7 2.75\n",
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" 2.820553 2.890843 2.910875 2.95 3. 3.05 3.1 3.15\n",
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" 3.2 3.25 3.3 3.35 3.4 3.45 3.5 3.55\n",
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" 3.6 3.65 3.7 3.75 3.8 3.85 3.9 3.95\n",
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" 4. 4.05 4.1 4.15 4.2 4.25 4.3 4.35\n",
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" 4.4 4.45 4.5 4.55 4.6 4.65 4.7 4.75\n",
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" 4.8 4.85 4.9 4.95 ]\n",
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"readings: [-1.556139e-01 -1.663574e-01 -1.621783e-01 -1.685456e-01 -1.634915e-01\n",
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" -1.711711e-01 -1.661170e-01 -1.711710e-01 -1.665548e-01 -1.742343e-01\n",
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" -1.669925e-01 -1.724839e-01 -1.674302e-01 -1.733590e-01 -1.669922e-01\n",
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" -1.729215e-01 -1.687431e-01 -1.772979e-01 -1.770578e-01 -1.829874e-01\n",
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" -1.674301e-01 -1.606676e-01 -1.437982e-01 -1.322218e-01 -1.140394e-01\n",
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" -1.151545e-01 -9.478331e-02 -6.351433e-02 -2.557993e-04 6.995752e-02\n",
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" 1.734703e-01 1.487249e-01 1.095815e-01 1.079751e+01 1.263197e+01\n",
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" 1.362582e+01 1.300827e+01 1.259473e+01 1.025542e+01 3.997076e+00\n",
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" -9.946833e+00 -1.482129e+01 -1.399363e+01 -1.326294e+01 -1.132879e+01\n",
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" -5.142632e+00 1.148345e+01 1.378293e+01 -3.400979e-01 -9.995720e-01\n",
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" -1.749203e+00 -1.385303e+00 -1.056456e+00 -1.082226e+00 -8.675261e-01\n",
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" -7.083023e-01 8.988955e-02 4.139638e+00 -6.590693e+00 -1.697538e+01\n",
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" -1.556470e+01 -1.461764e+01 -1.392116e+01 -1.365366e+01 -1.351573e+01\n",
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" -1.343544e+01 -1.343307e+01 -1.329787e+01 -1.297363e+01 -1.218130e+01\n",
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" -1.076091e+01 -8.683739e+00 -6.708155e+00 -5.400786e+00 -7.245429e+00\n",
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" -1.917886e+01 -1.436163e+01 1.541487e+01 1.495236e+01 1.484173e+01\n",
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" 1.273334e+01 1.251023e+01 1.266481e+01 1.274583e+01 1.290255e+01\n",
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" 1.080429e+01 -1.518563e+01 1.614336e+01 1.317309e+01 1.189001e+01\n",
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" 1.109593e+01 1.094126e+01 1.113482e+01 1.139770e+01 1.268495e+01\n",
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" 1.251639e+01 1.248731e+01 1.230242e+01 1.220341e+01 1.181950e+01], \n",
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"timestamps: [0. 0.05 0.1 0.15 0.2 0.25 0.3 0.35\n",
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" 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75\n",
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" 0.8 0.85 0.9 0.95 1. 1.05 1.1 1.15\n",
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" 1.2 1.25 1.3 1.35 1.4 1.45 1.5 1.55\n",
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" 1.6 1.690891 1.710923 1.75 1.8 1.85 1.9 1.95\n",
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" 2. 2.05 2.1 2.15 2.2 2.25 2.3 2.35\n",
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" 2.420332 2.45 2.5 2.55 2.6 2.65 2.7 2.75\n",
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" 2.820553 2.890843 2.910875 2.95 3. 3.05 3.1 3.15\n",
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" 3.2 3.25 3.3 3.35 3.4 3.45 3.5 3.55\n",
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" 3.6 3.65 3.7 3.75 3.8 3.85 3.9 3.95\n",
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" 4. 4.05 4.1 4.15 4.2 4.25 4.3 4.35\n",
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" 4.4 4.45 4.5 4.55 4.6 4.65 4.7 4.75\n",
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" 4.8 4.85 4.9 4.95 ]\n"
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]
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}
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],
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"source": [
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"buffer1 = measure.collect_buffer(keithley, buffer_nr=1)\n",
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"buffer2 = measure.collect_buffer(keithley, buffer_nr=2)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "3390e755-9e37-4b12-8499-9afb577d6505",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'buffer1' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mbuffer1\u001b[49m)\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[1;32m 3\u001b[0m df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(buffer1)\n",
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"\u001b[0;31mNameError\u001b[0m: name 'buffer1' is not defined"
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]
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}
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],
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"source": [
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"print(buffer1)\n",
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"import pandas as pd\n",
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"df = pd.DataFrame(buffer1)\n",
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"df.colums = [\"Time [s]\", \"Voltage [V]\"]\n",
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"df.save_csv(\"test.csv\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2beb660c-62b7-4d66-8162-601dfabd53f1",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"\n",
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"\n",
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"plt.plot(buffer1)\n",
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"plt.plot(buffer2)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "a96e2c53-67fa-49ac-87b4-22c34190a2b7",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"image/png": 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",
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"text/plain": [
|
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"<Figure size 640x480 with 1 Axes>"
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|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
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"data": {
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"text/plain": [
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"38"
|
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]
|
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},
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"from IPython.display import clear_output\n",
|
|
"\n",
|
|
"smua_settings = \"\"\"\n",
|
|
"display.clear() \n",
|
|
"display.settext('starting')\n",
|
|
"smua.reset()\n",
|
|
"smua.measure.autorangev = smua.AUTORANGE_ON\n",
|
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"smua.source.output = smua.OUTPUT_OFF\n",
|
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"-- max 20 V expected\n",
|
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"smua.measure.rangev = 20\n",
|
|
"\"\"\"\n",
|
|
"measure.run_lua(keithley, \"smua_reset.lua\")\n",
|
|
"keithley.write(\"smua.source.output = smua.OUTPUT_ON\")\n",
|
|
"data = []\n",
|
|
"for i in range(200):\n",
|
|
" data.append(tuple(float(v) for v in keithley.query(\"print(smua.measure.v())\").strip('\\n').split('\\t')))\n",
|
|
" # print(i, data[-1])\n",
|
|
" clear_output(wait=True)\n",
|
|
" plt.plot(data)\n",
|
|
" plt.show()\n",
|
|
" sleep(0.05)\n",
|
|
"\n",
|
|
"keithley.write(\"smua.source.output = smua.OUTPUT_OFF\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"id": "4e78e53e-a34d-4425-906e-0123a502d1f5",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"ename": "VisaIOError",
|
|
"evalue": "VI_ERROR_TMO (-1073807339): Timeout expired before operation completed.",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mVisaIOError\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mkeithley\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_raw\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"File \u001b[0;32m/usr/lib/python3.10/site-packages/pyvisa/resources/messagebased.py:405\u001b[0m, in \u001b[0;36mMessageBasedResource.read_raw\u001b[0;34m(self, size)\u001b[0m\n\u001b[1;32m 388\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mread_raw\u001b[39m(\u001b[38;5;28mself\u001b[39m, size: Optional[\u001b[38;5;28mint\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28mbytes\u001b[39m:\n\u001b[1;32m 389\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Read the unmodified string sent from the instrument to the computer.\u001b[39;00m\n\u001b[1;32m 390\u001b[0m \n\u001b[1;32m 391\u001b[0m \u001b[38;5;124;03m In contrast to read(), no termination characters are stripped.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 403\u001b[0m \n\u001b[1;32m 404\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 405\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mbytes\u001b[39m(\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_read_raw\u001b[49m\u001b[43m(\u001b[49m\u001b[43msize\u001b[49m\u001b[43m)\u001b[49m)\n",
|
|
"File \u001b[0;32m/usr/lib/python3.10/site-packages/pyvisa/resources/messagebased.py:442\u001b[0m, in \u001b[0;36mMessageBasedResource._read_raw\u001b[0;34m(self, size)\u001b[0m\n\u001b[1;32m 435\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m status \u001b[38;5;241m==\u001b[39m loop_status:\n\u001b[1;32m 436\u001b[0m logger\u001b[38;5;241m.\u001b[39mdebug(\n\u001b[1;32m 437\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m - reading \u001b[39m\u001b[38;5;132;01m%d\u001b[39;00m\u001b[38;5;124m bytes (last status \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m)\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 438\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_resource_name,\n\u001b[1;32m 439\u001b[0m size,\n\u001b[1;32m 440\u001b[0m status,\n\u001b[1;32m 441\u001b[0m )\n\u001b[0;32m--> 442\u001b[0m chunk, status \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvisalib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msession\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msize\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 443\u001b[0m ret\u001b[38;5;241m.\u001b[39mextend(chunk)\n\u001b[1;32m 444\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m errors\u001b[38;5;241m.\u001b[39mVisaIOError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
|
|
"File \u001b[0;32m/usr/lib/python3.10/site-packages/pyvisa_py/highlevel.py:519\u001b[0m, in \u001b[0;36mPyVisaLibrary.read\u001b[0;34m(self, session, count)\u001b[0m\n\u001b[1;32m 513\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n\u001b[1;32m 514\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[1;32m 515\u001b[0m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 516\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_return_value(session, StatusCode\u001b[38;5;241m.\u001b[39merror_invalid_object),\n\u001b[1;32m 517\u001b[0m )\n\u001b[0;32m--> 519\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m data, \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhandle_return_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43msession\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstatus_code\u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"File \u001b[0;32m/usr/lib/python3.10/site-packages/pyvisa/highlevel.py:251\u001b[0m, in \u001b[0;36mVisaLibraryBase.handle_return_value\u001b[0;34m(self, session, status_code)\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_last_status_in_session[session] \u001b[38;5;241m=\u001b[39m rv\n\u001b[1;32m 250\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m rv \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m--> 251\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m errors\u001b[38;5;241m.\u001b[39mVisaIOError(rv)\n\u001b[1;32m 253\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m rv \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39missue_warning_on:\n\u001b[1;32m 254\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m session \u001b[38;5;129;01mand\u001b[39;00m rv \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_ignore_warning_in_session[session]:\n",
|
|
"\u001b[0;31mVisaIOError\u001b[0m: VI_ERROR_TMO (-1073807339): Timeout expired before operation completed."
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"keithley.read_raw()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d597ff99-d56d-45c4-8e1c-3ee1eebfb565",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"measure.run_lua(keithley, \"buffer_reset.lua\")\n",
|
|
"measure.run_lua(keithley, \"smua_reset.lua\")\n",
|
|
"keithley.write(\"smua.measure.count = 100\")\n",
|
|
"keithley.write(\"smua.measure.interval = 0.05\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7e7adaa9-e81d-498b-9e01-b838643a1050",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
" keithley.write(\"smua.measure.iv(smua.nvbuffer1, smua.nvbuffer2)\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "aafa7d7e-dedd-4546-bf80-b247eb947402",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"keithley.write(\"format.data = format.DREAL\\nformat.byteorder = format.LITTLEENDIAN\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "40dbecd1-7405-4a6c-81d9-0d3f407c0efc",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"keithley.query_binary_values(\"printbuffer(1, smua.nvbuffer1.n, smua.nvbuffer1)\", container=)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "3979a9de-f4b9-448e-a2f3-b36cbea9658c",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "60431b81-a860-4964-8f60-0aca8fdde36a",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.10"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|