{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "

Python Automation of Agilent Instruments

\n", "*Note: This app note only applies to automation using a CPython installation on a Windows machine and assumes some prior knowledge and installation of Python.*\n", "
\n", "

Contents

\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
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General SCPI Instrumentation Control

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\n", " Requirements:
\n", "

    \n", "
  1. Installation of a VISA library such as [Agilent's IO Libraries](http://www.agilent.com/find/iolibs)
    \n", "
  2. Installation of the [PyVISA](https://github.com/hgrecco/pyvisa) Python library
    \n", "
\n", "

\n", "

Example of use with an Agilent [90000 X Series](www.agilent.com/find/90000x-scope) Oscilloscope:

" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from visa import instrument # Import the instrument function from the visa module\n", "scope = instrument(\"TCPIP0::130.30.240.155::inst0::INSTR\") # Connect to the scope using the VISA address (see below)\n", "scope.ask(\"*IDN?\") # Query the IDN properties of the scope" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 1, "text": [ "'Agilent Technologies,MSOX93204A,MY53240105,04.60.0016'" ] } ], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "The instrument's visa address can be found in the IO Libraries Connection Expert:
\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's do something more interesting..." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "# Allow plots to appear inline with the IPython notebook\n", "%pylab inline\n", "scope.write(\":TIM:SCALE 600e-12\")\n", "scope.write(\":DIG\") # Capture a single waveform\n", "wfm_ascii = scope.ask(\":WAV:DATA?\") # Get the waveform data\n", "wfm_ascii = wfm_ascii[:-1] # Remove a trailing ,\n", "wfm = [float(s) for s in wfm_ascii.split(',')] # Convert the ascii list of strings to a list of floats\n", "sa_rate = float(scope.ask(\":ACQ:SRAT:ANAL?\")) # Get the scope's sample rate\n", "mem_depth = float(scope.ask(\":ACQ:POIN?\")) # Get the current memory depth\n", "t = np.linspace(-mem_depth/sa_rate,mem_depth/sa_rate, len(wfm)) # Calculate the sample times of the waveform\n", "plt.plot(t,wfm) # Plot the waveform vs sample times" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 12, "text": [ "[]" ] }, { "metadata": {}, "output_type": "display_data", "png": 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42Ecmo4p9jFPQKYUkUlJ5OYoRaE46+8hUKVCguYTB7SPVQxYnF+PboiYnSzKm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\nEAgEwiCIFAgEAoEwCCIFAoFAIAyCSIFAIBAIgyB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"text": [ "" ] } ], "prompt_number": 12 }, { "cell_type": "markdown", "metadata": {}, "source": [ "How about a screenshot from the instrument to confirm the waveform data we just pulled?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "scope.write(\"disp:data? png\")\n", "data = scope.read_raw() # Read back the raw binary data as a string\n", "hash_idx = data.find('#') # Find the start of the image data\n", "len_datalen = int(data[hash_idx+1]) # The 1st character after '#' indicates the length of the length field\n", "data_start_idx = hash_idx+len_datalen+2 # The binary image data starts here\n", "datalen = int(data[hash_idx+2:hash_idx+len_datalen+2]) # The length of the binary data\n", "img_data = data[data_start_idx:data_start_idx+datalen] # Extract just the image binary data\n", "\n", "from IPython.display import Image # Ipython has some nice tools to display image data.\n", "embed = Image(img_data)\n", "embed" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "png": 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eDoiXA5I41//Qn9q3poSA73//+9trr70m/nH9DntHAGdRL/08YOl7zli+rVxF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BcAAcOBAHIARACEDAHyjgof5C/QUHwAFwABwAB8ABcAAcAAfAAQgBWkJA4rdmt23nd1lv7LxE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\nRK5CYII=\n", "prompt_number": 13, "text": [ "" ] } ], "prompt_number": 13 }, { "cell_type": "markdown", "metadata": {}, "source": [ "A more complete example of handling binary values from an instrument coming soon...\n", "To save the screenshot to a local file:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "target = open('screenshot.png','wb')\n", "target.write(img_data)\n", "target.close()" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 15 }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "

Automation of Infiniium Compliance Applications

\n", "*You can find more information about our scope apps at: [www.agilent.com/find/scope-apps](http://www.agilent.com/find/scope-apps)*
\n", "
Requirements:
\n", "
    \n", "
  1. Installation of a [Python for .NET](http://pythonnet.sourceforge.net) Python module
    \n", " * Unzip & put the files **clr.pyd** & **Python.Runtime.dll** into the \\DLLs directory of your Python installation (ex: C:\\Python27\\DLLS\\)*
    \n", "
    \n", "
  2. Installation of the [Infiniium Remote Programming Toolkit](http://www.agilent.com/find/rpi)
    \n", " * Once installed go to the Tools directory & copy the file **Agilent.Infiniium.AppFW.Remote.dll** into the same Python install \\DLLs directory*
    \n", "
    \n", "
  3. The Remote Programming Interface for the Infiniium Compliance Applications is built on a .NET API and requires a **LAN connection** to the scope.
    \n", "
\n", "\n", "Example:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# First set up the connection to the RPI DLL via the Python for .NET module\n", "import clr # Import the Common Runtime Library Python module\n", "clr.AddReference(\"Agilent.Infiniium.AppFW.Remote\") # Create a reference from CLR to the Compliance App DLL\n", "from Agilent.Infiniium.AppFW.Remote import * # Import the entire compliance app namespace from the Compliance App DLL\n", "scopeIpAddress = \"130.30.240.155\"" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we're ready to start..." ] }, { "cell_type": "code", "collapsed": false, "input": [ "scope.write(\":SYSTEM:LAUNCH 'N5393C PCIExpress Test App'\") # Launch the compliance app using the pyvisa instrument connection\n", "remoteObj = RemoteAteUtilities.GetRemoteAte(scopeIpAddress) # Connect to the compliance app\n", "remoteApp = IRemoteAte(remoteObj)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we want to take a look at the test ID's & test names currently available we can do that using the TestInfo type:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "remoteApp.SetConfig(\"TestPoint_Transmitter\", \"1.0\")\n", "testsinfos = remoteApp.GetCurrentOptions(\"TestsInfo\")\n", "for test in testsinfos:\n", " print test.ID, test.Name" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "2101 Tx, Unit Interval (PCIE 2.0, 2.5 GT/s)\n", "2110 Tx, Template Tests (PCIE 2.0, 2.5 GT/s)\n", "2120 Tx, Median to Max Jitter (PCIE 2.0, 2.5 GT/s)\n", "2130 Tx, Eye-Width (PCIE 2.0, 2.5 GT/s)\n", "2140 Tx, Peak Differential Output Voltage (Transition)(PCIE 2.0, 2.5 GT/s)\n", "21400 Tx, Peak Differential Output Voltage (Non Transition)(PCIE 2.0, 2.5 GT/s)\n", "2151 Tx, Rise/Fall Time (PCIE 2.0, 2.5 GT/s)\n", "2160 Tx, Deemphasized Voltage Ratio (PCIE 2.0, 2.5 GT/s)\n", "2170 Tx, RMS AC Peak Common Mode Output Voltage (PCIE 2.0, 2.5 GT/s)\n", "2181 Tx, Avg DC Common Mode Voltage (PCIE 2.0, 2.5 GT/s)\n", "2182 Tx, DC Common Mode Output Voltage Variation (PCIE 2.0, 2.5 GT/s)\n", "2185 Tx, DC Common Mode Line Delta (PCIE 2.0, 2.5 GT/s)\n" ] } ], "prompt_number": 14 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's select some measurements & run some tests:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "remoteApp.SuppressMessages = True # Suppress the GUI prompts\n", "remoteApp.NewProject(True) # Create a new project\n", "# Set various Configuration Parameters\n", "remoteApp.SetConfig(\"DevicePCIErev\", \"PCIE 2.0\")\n", "remoteApp.SetConfig(\"TestPoint_AddInCard\", \"1.0\")\n", "remoteApp.SetConfig(\"DataRateOpt\", \"2.5 GT/s\")\n", "remoteApp.SetConfig(\"EnableSignalCheck\", \"0.0\")\n", "remoteApp.SelectedTests = [2301, 2310, 2320, 2330, 2340, 2350] # Select the tests to run\n", "remoteApp.Run() # Run the selected tests\n", "# Set up the project save options & save it to disk\n", "saveOptions = SaveProjectOptions()\n", "saveOptions.BaseDirectory = \"c:\\\\temp\"\n", "saveOptions.Name = \"Demo\"\n", "saveOptions.OverwriteExisting = True\n", "projectFullPath = remoteApp.SaveProjectCustom(saveOptions)\n", "# Set up the project results options and then get the results\n", "resultOptions = ResultOptions()\n", "resultOptions.TestIds = [2301]\n", "resultOptions.IncludeCsvData = True\n", "customResults = remoteApp.GetResultsCustom(resultOptions)\n", "results = customResults.CsvResults\n", "#remoteApp.Exit(True,True) # Exit the application" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "# An example of how to manipulate and display results using the Pandas library\n", "import pandas as pd\n", "from StringIO import StringIO\n", "df_data = pd.read_csv(StringIO(results), sep=',', header=0, quotechar = '\"')\n", "pd.set_option('display.max_colwidth', 22)\n", "df_data" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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Test ID Test Name Measured Item Trial 1 Value
0 2301 Add-in Card Tx, Un... Data Lane Lane0
1 2301 Add-in Card Tx, Un... Note: Non-SSC Limits Use...
2 2301 Add-in Card Tx, Un... Actual Value 401.7540
3 2301 Add-in Card Tx, Un... #3500 UI Blocks Me... 992144
4 2301 Add-in Card Tx, Un... Margin -680.8
5 2301 Add-in Card Tx, Un... Min UI 401.7430
6 2301 Add-in Card Tx, Un... Max UI 401.7540
7 2301 Add-in Card Tx, Un... Mean UI 401.7480
8 2301 Add-in Card Tx, Un... Worst Case Data Rate 2489085360.693
9 2301 Add-in Card Tx, Un... Mean Data Rate 2489122534.524
10 2301 Add-in Card Tx, Un... Connection Type Chan 1,3 - Direct ...
\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ " Test ID Test Name Measured Item Trial 1 Value\n", "0 2301 Add-in Card Tx, Un... Data Lane Lane0\n", "1 2301 Add-in Card Tx, Un... Note: Non-SSC Limits Use...\n", "2 2301 Add-in Card Tx, Un... Actual Value 401.7540\n", "3 2301 Add-in Card Tx, Un... #3500 UI Blocks Me... 992144\n", "4 2301 Add-in Card Tx, Un... Margin -680.8\n", "5 2301 Add-in Card Tx, Un... Min UI 401.7430\n", "6 2301 Add-in Card Tx, Un... Max UI 401.7540\n", "7 2301 Add-in Card Tx, Un... Mean UI 401.7480\n", "8 2301 Add-in Card Tx, Un... Worst Case Data Rate 2489085360.693\n", "9 2301 Add-in Card Tx, Un... Mean Data Rate 2489122534.524\n", "10 2301 Add-in Card Tx, Un... Connection Type Chan 1,3 - Direct ..." ] } ], "prompt_number": 6 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Similarly for Compliance Applications on **FlexDCA**:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from visa import *\n", "dca = instrument(\"TCPIP0::130.30.240.150::inst0::INSTR\")\n", "dca.ask(\"*idn?\")" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "code", "collapsed": false, "input": [ "dca.write(\":SYST:LAUN 'N1012A OIF CEI 3_0'\") # Launch the compliance app" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "

Automation of N5990A Automated Test Applications for Receiver Test

\n", "*More information about [N5990A solutions](http://www.home.agilent.com/en/pd-734301-pn-N5990A)*
\n", "
\n", "Requirements:
\n", "
    \n", "
  1. Installation of a [Python for .NET](http://pythonnet.sourceforge.net) Python module/
    \n", " * Unzip & put the files **clr.pyd** & **Python.Runtime.dll** into the \\DLLs directory of your Python installation (ex: C:\\Python27\\DLLS\\)*
    \n", "
    \n", "
  2. The Valiframe dll\u2019s that needed are typically installed in the following directory: C:\\Program Files (x86)\\BitifEye\\ValiFrame\\PCI-Express3\n", "You can copy over the ones you need to a directory that Python looks in but the easiest way to reference them from your Python script is to add this directory to the sys.path variable which tells the Python interpreter where to look for modules and dll\u2019s.
    \n", "
\n", "\n", "Example:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import sys \n", "sys.path.append('C:\\\\Program Files (x86)\\\\BitifEye\\\\ValiFrame\\\\PCI-Express3') # Add the location of the Valiframe dll's to the system path\n", "import clr # Import the Common Runtime Library Python module\n", "clr.AddReference(\"ValiFrameRemote\") # Create a reference from CLR to the Valiframe App DLL\n", "from BitifEye.ValiFrame.ValiFrameRemote import * # Import the entire valiframe app namespace from the DLL\n", "my_vf_pcie = ValiFrameRemote() # Creates an instance of the ValiFrameRemote class\n", "my_vf_pcie.InitApplication(\"PciExpress3\") # Initialize the application\n", "my_vf_pcie.LoadProject(\"my_pcie3_proj.vfp\")\n", "#my_vf_pcie.ConfigureApplication() # This method creates a GUI prompt" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are a couple of interesting things to be aware of when using .NET dll's in Python via the pythonnet module.
\n", "
    \n", "
  1. A .NET method may require the user to pass the variable name it wishes to modify as an argument. Python does not support \"pass by reference\" but the variable name must exist in python before it can be handed to the .NET method. The .NET method will simply point to the new instance.
    \n", " The example below shows how to handle this.\n", "
  2. .NET attributes can often return .NET collections such as Arrays. The object returned by python.net is indexed and iterable in Python but it is not a native Python collection object like a list.
    \n", " The example below shows a simple way to convert Arrays of Strings and Int32s to lists of strings & ints.\n", "
" ] }, { "cell_type": "code", "collapsed": false, "input": [ "procedureIDs = procedureNames = [] # The variable names must be assigned to something but are overwritten in the next call\n", "_, procedureIDs, procedureNames = my_vf_pcie.GetProcedures(procedureIDs, procedureNames)\n", "procedureIDs = [int(id) for id in procedureIDs] # Convert to a python list of integers\n", "procedureNames = [str(name) for name in procedureNames] # Convert to a python list of strings\n", "procs = zip(procedureIDs, procedureNames) # Zip the id's & names together. A dictionary may also be a useful way to store these.\n", "for proc_id,proc_name in procs:\n", " print proc_id, proc_name" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "300101 Random Jitter Calibration\n", "300103 De-Emphasis Calibration\n", "300104 Eye Height Calibration\n", "301101 Random Jitter Calibration\n", "301103 De-Emphasis Calibration\n", "301104 Eye Height Calibration\n", "302120 Equalization Preset Calibration\n", "302121 Equalization Custom Preset Calibration\n", "302122 Random Jitter Calibration\n", "302123 Sinusoidal Jitter Calibration\n", "302125 DM Sinusoidal Interference Calibration\n", "302126 Eye Height and Width Calibration\n", "302127 Compliance Eye Calibration\n", "310101 Compliance Test\n", "311101 Compliance Test\n", "312120 Preset Compliance Test\n", "312121 Compliance Test\n", "320101 Unit Interval \n", "320102 Template Tests \n", "320103 Median to Max Jitter \n", "320104 Eye-Width \n", "320105 Peak Differential Output Voltage (Transition)\n", "320106 Peak Differential Output Voltage (NonTransition)\n", "321140 Unit Interval \n", "321141 Template Tests -3.5dB \n", "321142 Peak Differential Output Voltage -3.5dB \n", "321143 Eye-Width -3.5dB with crosstalk \n", "321144 RMS Random Jitter -3.5dB with crosstalk \n", "321145 Maximum Deterministic Jitter -3.5dB with crosstalk \n", "321146 Total Jitter at BER-12 -3.5dB with crosstalk \n", "321147 Eye-Width -3.5dB without crosstalk \n", "321148 RMS Random Jitter -3.5dB without crosstalk \n", "321149 Maximum Deterministic Jitter -3.5dB without crosstalk \n", "321150 Total Jitter at BER-12 -3.5dB without crosstalk \n", "322160 Unit Interval \n", "322161 Template Tests \n", "322162 Eye-Width \n", "322163 Peak Differential Output Voltage \n" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Valiframe often uses dialog windows to give the user information or prompt the user to make a change to the setup.\n", "There are different ways to handle this in an automation environment. Below is a basic way to suppress all dialog windows but there is a more complete example of [how to handle messaging and events in Valiframe](N5990A_Python_Automation.ipynb)" ] }, { "cell_type": "code", "collapsed": false, "input": [ "my_vf_pcie.DialogPopUp += DialogShowEventHandler(VFDialogInformation()) # Register the Dialog event handler (suppresses all Dialogs)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "eyewidth_result = str()\n", "my_vf_pcie.RunProcedure(320104, eyewidth_result)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ "(True,\n", " u'\\r\\n\\r\\n \\r\\n Eye-Width \\r\\n 320104\\r\\n Incomplete\\r\\n 11/13/2013 12:32:21 PM\\r\\n \\r\\n')" ] } ], "prompt_number": 6 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Copyright \u00a9 2011 Agilent Technologies Inc. All rights reserved.\n", "\n", "You have a royalty-free right to use, modify, reproduce and distribute this content (and/or any modified version) in any way you find useful, provided that you agree that Agilent has no warranty, obligations or liability." ] } ], "metadata": {} } ] }