PyLTSpice 1.0.post0

An set of tools to Automate LTSpice simulations

README

PySpicer is a toolchain of python utilities design to interact with LTSpice Electronic Simulator.

What is contained in this repository

• LTSteps.py An utility that extracts from LTSpice output files data, and formats it for import in a spreadsheet,s uch like Excel or Calc.

• LTSpice_RawRead.py A pure python class that serves to read raw files into a python class.

• Histogram.py A python script that uses numpy and matplotlib to create an histogram and calculate the sigma deviations. This is useful for Monte-Carlo analysis.

• LTSpiceBatch.py This is a script to launch LTSpice Simulations. This is useful because:

  • Can overcome the limitation of only stepping 3 parameters
  • Different types of simulations .TRAN .AC .NOISE can be run in a single batch
  • The RAW Files are smaller and easier to treat
  • When used with the LTSpiceRaw_Reader.py and LTSteps.py, validattion of the circuit can be done automatically.
  • Different models can be simulation in a single batch. The principle of operation is the following :
    1. Add to the Spice circuit a .INC sim_settings.lib . In this include simulation directives are written by the script per each simulation call.
    2. Use the python script to update the simulation directives and call LTSpice to run the simulation in command line.
    3. When the simulation is complete, the simulation results are renamed according to user guidance.

  Note: It only works with Windows based installations.

How to Install

Using PiP Installer

pip install --upgrade PyLTSpice

Using GITHub

git clone https://github.com/nunobrum/PyLTSpice.git

If using this method it would be good to add the path where you cloned the site to python path.

import sys
sys.path.append(<path to PyLTSpice>)

How to use

LTSpice_RawRead.py

Include the following line on your scripts

from PyLTSpice.LTSpice_RawRead import LTSpiceRawRead

from matplotlib import plot

LTR = LTSpiceRawRead("Draft1.raw")

print(LTR.get_trace_names())
print(LTR.get_raw_property())

IR1 = LTR.get_trace("I(R1)")
x = LTR.get_trace('time') # Gets the time axis steps = LTR.get_steps() for step in range(len(steps)): # print(steps[step]) plt.plot(x.get_time_axis(step), IR1.get_wave(step), label=steps[step])`

plt.legend() # order a legend.
plt.show()

LTSpice_Batch

This module is used to launch LTSPice simulations. Results then can be processed with either the LTSpiceRawRead or with the LTSteps module to read the log file which can contain .MEAS results.

The script will firstly invoke the LTSpice in command line to generate a netlist, and then this netlist can be updated directly by the script, in order to change component values, parameters or simulation commands.

Here follows an example of operation.

import os from PyLTSpice.LTSpiceBatch import LTCommander from shutil import copyfile

# get script absolute path meAbsPath = os.path.dirname(os.path.realpath(__file__)); LTC = LTCommander(meAbsPath + "\\Batch_Test.asc")

LTC.set_parameters(res=0, cap=100e-6) # set PARAM variables directly on the netlist LTC.set_component_value('R2', '2k') # Replaces the value of a R2 resistor on the netlist LTC.set_component_value('R1', '4k') # Replaces the value of the R1 resistor # define simulation LTC.add_instructions( "; Simulation settings", ".param run = 0" )

for opamp in ('AD712', 'AD820'): # Will make simulation with two OPAMP models. First the AD712 and then with the AD820 LTC.set_element_model('XU1', opamp) # Sets the U1 OPAMP model. Note that the X prefix must be added for any subcircuit for supply_voltage in (5, 10, 15): LTC.set_component_value('V1', supply_voltage) # set simulation voltages LTC.set_component_value('V2', -supply_voltage) rawfile, logfile = LTC.run() # Runs the simulation, and returns both the RAW filename and LOG filenames. # The line below is optional and serves just to keep a copy of all the netfiles for debug purposes copyfile(LTC.run_netlist_file, "{}_{}_{}.net".format(LTC.circuit_radic, opamp, supply_voltage)) # Keep the netlist for reference # Here the part where the processing of results could be done.

LTC.reset_netlist() # This reverts all the changes done to the netlist # Now making a new simulation type, using an AC (frequency small signal simulation) LTC.add_instructions( "; Simulation settings", ".ac dec 30 10 1Meg", ".meas AC Gain MAX mag(V(out)) ; find the peak response and call it ""Gain""", ".meas AC Fcut TRIG mag(V(out))=Gain/sqrt(2) FALL=last" )

raw, log = LTC.run()

# Sim Statistics print('Successful/Total Simulations: ' + str(LTC.okSim) + '/' + str(LTC.runno))

LTSteps.py

python -m PyLTSpice.LTSteps <logfile or directory where last simulation was made>

Histogram.py

python -m PyLTSpice.Histogram

To whom do I talk to?

• Tools website : https://www.nunobrum.com/pyspicer.html
• Repo owner : [e-mail]
• Alternative contact : [e-mail]

History

• Version 1.0 LTSpiceBatch.py: Implemented an new approach (NOT BACKWARDS COMPATIBLE), that avoids the usage of the sim_settings.inc file. And allows to modify not only parameters, but also models and even the simulation commands.

LTSpice_RawRead.py: Added the get_time_axis method to the RawRead class to avoid the problems with negative values on time axis, when 2nd order compression is enabled in LTSpice.

LTSteps.py: Modified the LTSteps so it can also read measurements on log files without any steps done.

• Version 0.6 Histogram.py now has an option to make the histogram directly from values stored in the clipboard

• Version 0.5 The LTSpice_RawReader.py now uses the struc.unpack function for a faster execution

• Version 0.4 Added LTSpiceBatch.py to the collection of tools

• Version 0.3 A version of LTSteps that can be imported to use in a higher level script

• Version 0.2 Adding LTSteps.py and Histogram.py

• Version 0.1 First commit to the bitbucket repository.