Mercurial > ~darius > hgwebdir.cgi > pyinst
annotate agilent_r5071.py @ 84:4b4ae555067b
Use RMS detector and fix the sweep time for more accuracy.
Add links to app notes discussing theory.
Run forever without pause and print a summary on ctrl-c
author | Daniel O'Connor <doconnor@gsoft.com.au> |
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date | Thu, 03 Oct 2024 08:57:10 +0930 |
parents | 6bd941d96c03 |
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Add Q&D example code for Anritsu MS2034A and Agilent R5071.
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1 # Docs are at http://ena.tm.agilent.com/e5071c/manuals/webhelp/eng/ |
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3 import numpy |
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4 import scpi |
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5 import pylab |
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7 fname = 'data' |
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9 # Connect |
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10 inst = scpi.instURL('vxi://203.31.81.47') |
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12 # Read ID |
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13 inst.write('*IDN?') |
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14 inst.read() |
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15 # 'Agilent Technologies,E5071C,MY46109815,A.09.54\n' |
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17 # Set to 8 byte floats |
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18 inst.write(":FORM:DATA REAL") |
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19 |
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20 # Set to little endian |
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21 inst.write(':FORM:BORD SWAP') |
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23 # Grab frequency data |
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24 inst.write(":SENS1:FREQ:DATA?") |
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25 freqs = scpi.bindecode(inst.read(), dtype = numpy.float64) |
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27 # Grab trace data |
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28 inst.write(":CALC1:TRACE1:DATA:FDATA?") |
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29 dat = scpi.bindecode(inst.read(), dtype = numpy.float64) |
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31 # We only want the real part (no imag for this measurement) |
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32 dat = dat[::2] |
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34 # Plot |
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35 pylab.plot(freqs, dat) |
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36 pylab.show() |
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37 |
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38 # Save for later |
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39 numpy.savez('data.npz', freqs, dat) |
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41 # Load.. |
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42 f = numpy.load(fname + '.npz') |
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43 freqs = f['arr_0'] |
9ce709b7da4b
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44 dat = f['arr_1'] |
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46 f = file(fname + '.csv', 'wb') |
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47 f.write("Frequencies\n") |
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48 numpy.savetxt(f, [freqs], delimiter = ',') |
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49 f.write("Gain\n") |
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50 numpy.savetxt(f, [dat], delimiter = ',') |
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51 del f |
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