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Device and Circuit Data Analysis

Project description

DeCiDa Data Analysis and Procedural Simulation Python Library

DeCiDa == Device and Circuit Data Analysis.

DeCiDa man pages

DeCiDa is a Python Library of functions and classes for device characterization, circuit design and data analysis.

DeCida is written in pure Python (2.7, and 3), and requires no code-compilation. It is portable to any operating system where Python is installed, and runs under MacOS, Windows, Cygwin, and Linux. Many DeCiDa classes and functions require the numpy and Tkinter packages.

This version of DeCiDa provides support for Python 3 and can be run under a Python 3 environment, as well as a Python 2.7 environment. The following packages are now required: future, six, numpy and matplotlib. Please let me know if there are any issues that you find.

DeCiDa uses matplotlib XY-plot rendering by default. To use the former XY-plot rendering, add the option -xmat to dataview, plotter, pllss, and pll_phase_noise.

For circuit analysis, DeCiDa provides a flexible scripting class for performing simulations with various circuit simulation tools, such as (Synopsys) HSpice, (Cadence) Spectre, (Silvaco) SmartSpice, (UC Berkeley) NGspice and others. The Tckt class is used to provide a database of process corners for each project, and to provide netlist templating for performing procedural simulations and post-processing. Scripts using Tckt access the database to obtain the corner conditions, modify the netlist, and allow full Python looping structures for running the simulation, viewing and analyzing the simulated data.

For data analysis, DeCiDa provides a Data class for reading-in and analyzing data in a number of formats, including nutmeg (NGspice, Spectre, LTspice), CSDF (HSpice), CSV (comma-separated value), SSV (space-separated value), and others. The Data object can be viewed using the XYplotm, Histogramx or DataViewm classes. DataViewm has commands via menu entries to manipulate and plot the data in different ways, including frequency versus time, eye- and scope-diagrams and column calculations.

DeCiDa started out as a Tcl/Tk application for analyzing measurements of electron devices for performing routine compact-model parameter extraction. To do this fitting, a least-squares optimization algorithm was used. This Python version of DeCiDa has a function LevMar (for Levenberg-Marquardt), based on the mpfit package. It is still under development.

What is in the distribution

  • The decida Python library of functions and classes (./decida). This is installed into the site-packages directory.

  • A test library under decida.test for testing the distribution (./decida/test). This is also installed into the site-packages directory.

  • Applications in the distribution bin directory (./bin). These are installed into the Python bin directory.

  • Tool-specific scripts (./etc):

    • simulation tool wrappers (./etc/wrappers)

      Circuit simulation tool wrappers that DeCiDa interfaces with. These are installed into ~/.DeCiDa/bin

    • HTML documentation of the functions and classes (./doc/html).

      This is installed into ~/.DeCiDa/doc

    • cython (./etc/cython)

      Setup scripts for using cython to compile the Data and XYplotm classes. These are installed into ~/.DeCiDa/cython

    • dot files (./etc/dot)

      Several resource files to be placed in user home directory for Cadence and Python. These are installed into ~/.DeCiDa/dot

    • user local lib directory (./etc/lib)

      A place to put user Python code. This is set up as ~/.DeCiDa/lib

    • models (./etc/models)

      Case-corners and models for two example technologies from the Predictive Technology Models web-site. These are installed into ~/.DeCiDa/models

    • projects (./etc/projects)

      Two example project simulation directories (bird and trane). These are installed into ~/.DeCiDa/projects

    • Cadence skill files (./etc/skill)

      Several scripts for automatically generating DeCiDa Python procedural simulation scripts, and verilog test-bench environments. These are installed into ~/.DeCiDa/skill

    • stdcell (./etc/stdcell)

      Two example standard cell libraries for the two example PTM technologies, from the NangateOpenCell Library. These are installed into ~/.DeCiDa/stdcell

    • verilog (./etc/verilog)

      Files for running Cadence NCsim and viewing the results using SimVision. These are installed into ~/.DeCiDa/verilog

    • matlab (./etc/matlab)

      Matlab file to implement a Data object with a demo. These are installed into ~/.DeCiDa/matlab

DeCiDa applications

All of these should be in the path after installation:

application: description:
calc scientific calculator
dataview read, plot and analyze data
plotter plot Cartesian, Parametric, or Polar functions
twin text editor, with additional capability
gifimg create embedded GIF image Python class from a GIF image
pllss plot PLL small-signal transfer functions, S-domain and Z-domain
pll_phase_noise plot PLL phase noise components and total phase noise
ngsp UC Berkeley NGspice gui
op read Cadence Spectre operating-point analysis, display node voltages and operating points
simvision_csv2col convert exported Cadence SimVision csv data to column data

Simulation tool wrapper scripts

These scripts are installed in ~/.DeCiDa/bin

wrapper script: description:
run_hspice wrapper to run Synopsys HSpice
run_ngspice wrapper to run UC Berkeley NGspice
run_sspice wrapper to run Silvaco SmartSpice
run_spectre wrapper to run Cadence Spectre

Thanks to

  1. Python distribution documentation .

  2. Canopy installation documentation .

  3. decida/ItclObjectx:

    Concepts from [incr Tcl], described in chapter 2, “Object-Oriented Programming with [incr Tcl],” by Michael McLennan, of “Tcl/Tk Tools,” Mark Harrision, 1997, O’Reilly.

  4. decida/FrameNotebook and decida/Balloonhelp:

    Adapted from the Tcl/Tk examples in Mark Harrison and Michael McLennan, “Effective Tcl/Tk Programming”, 1997, Addison-Wesley.

  5. decida/Data.read_nutmeg method:

    Modified from the read_spice module from Werner Hoch (python_spice-0.0.3).

  6. decida/LevMar:

    Modified from the mpfit module from Sergey Koposov, Craig Markwardt and Mark Rivers (mpfit_2013).

  7. bin/gifimg:

    Modified from the img2pytk module from Bill Allen (imageEmbedder-1.0).

  8. Example model files:

    From Predictive Technology Model from the Nanoscale Integration and Modeling (NIMO) group at Arizona State University.

  9. Example standard cell libraries:

    From Si2 openEDA project, Nangate 45nm Open Cell Library, a generic open-source, non-manufacturable standard-cell library.

  10. George Howlett, Michael McLennan, Sani Nassif, Mike Toth and others for developing many of the original concepts which are incorporated in DeCiDa.

  11. Dean Gonzales, Sanquan Song and Phillip Johnson for supplying test data files and test-driving DeCiDa.

  12. MatPlotLib matplotlib.

  13. Barry J. Muldrey, for testing and helping to port to Python 3.

Installing DeCiDa

If you have pip

  • issue this command:

    pip install DeCiDa

Note that the scripts that should be installed in the python bin directory (dataview, plotter, …) may not arrive there. And the home directory directories may not get set up properly. If this happens, simply download the distribution and copy these from the untarred folders.


Download and prepare the distribution

  • unzip/untar the distribution:

    tar xvfz DeCiDa.1.1.3-tar.gz
  • cd into the distribution directory:

    cd DeCiDa-1.1.3
  • you may want to install the DeCiDa html documentation (in ./doc/html) to an appropriate place for future reference. use a browser to read the documentation, using the url file:// specification to point to the index.html file in the html directory.

  • manually modify the wrapper scripts in the distribution ./etc/wrapper directory (run_*), to point to correct tool locations.

    The wrappers have the following references to other tools. Adjust these as needed, as required by your local environment.

wrapper: expected tool location:
run_hspice /tools/hspice/bin/hspice
run_ngspice /opt/local/bin/ngspice
run_sspice /tools/silvaco/bin/sspice
run_spectre /tools/cds/bin/spectre

Installing under Anaconda

refer to: Managing packages
  • be sure that Anaconda python is in your path:

    >>> import sys; sys.prefix

    you should see a path like the following:

    /Users/<user>/anaconda (MacOs)
    /home/<user>/anaconda (Linux)
  • install the distribution:

    conda install DeCiDa

Installing under Enthought Canopy

  • install in the Canopy Python User Virtual Environment

    refer to: Installing packages into Canopy, Canopy python default

  • be sure that User python is in your path:

    >>> import sys; sys.prefix

    you should see a path like one of the following:

    /Users/<user>/Library/Enthought/Canopy_32bit/User (MacOs)
    /home/<user>/Enthought/Canopy_32bit/User (Linux)
  • install the distribution:

    python install
  • you will find a new directory .DeCiDa in your home directory containing various tool specific scripts, models and other data

  • the DeCiDa libraries are installed under site-packages

  • the DeCiDa applications are installed in the python bin directory so they should be in the user path (may require a shell rehash)

Installing under (2.7) python

  • be sure that python2.7 is in your path:

    >>> import sys; sys.prefix

    you should see a path like one of the following:

    /Library/Frameworks/Python.framework/Versions/2.7 (MacOS)
    /opt/local/lib/python2.7 (Linux)
  • install the distribution:

    python install

Installing as a local library

  • DeCiDa can also be installed in a user’s directory without requiring sysadmin privileges.

  • select or make a directory for putting python libraries:

    mkdir ~/python/library
  • copy the decida library to the python library in your home directory:

    cp -R ./decida ~/python/library
  • edit the python resource file in ./etc/dot ( change the pylib definition appropriately to point to ~/python/library

  • copy the resource file to your home directory:

    cp ./etc/dot/ ~/.
  • to use decida, import the user package, which imports ~/

    >>> import user
  • alternatively, define the PYTHONPATH environment variable to include ~/python/library in the path

  • copy the applications to the user home bin directory:

    cp ./bin/* ~/bin

Test the distribution using the distribution tests

  • test the distribution with one or more individual tests:

    >>> import decida.test.test_Calc_1

    should display a calculator

    >>> import decida.test.test_Plotterm

    should display a plot and equation-set text-window

  • list all of the tests:

    >>> import decida.test
    >>> decida.test.test_list()

    should print all of the tests

  • do all of the tests:

    >>> import decida.test.test_all

    this may or may not complete depending on the sequence of closing windows

  • the tests can also be run directly in the unzipped/tarred (pre-install) directory:

    cd DeCiDa-1.1.3/decida/test
  • test the applications installed in the python bin:


    should display a text-window (text-editor)

Project details

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