# description: Data conversion utility
# The input file must have three columns: date, time & amplitude
# Line Example: 09/20/2018 08:23:56 0.1765432
#
# The output file will have two columns: time(sec) & amplitude
# The time will start at zero.
– Tom Irvine
The CSV (Comma Separated Values) format is a widely-accepted format for spreadsheet programs. Python has the capability to read and write csv data via the module:
import csv
Here is a demonstration script: csv_read_write.py
Here is the data file for the demonstration script: input_data.csv
See also:
Tom Irvine
Matplotlib is a Python plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.
Tkinter is Python’s standard GUI (Graphical User Interface) package. It is an interface to the Tk GUI toolkit.
Here is a demonstration script using Matplotlib & Tkinter for plotting data in a 2d plot: tk_plot.py
Tom Irvine
Introduction
The lambda keyword creates a small anonymous function or procedure.
It creates a function object the same way that the def keyword does, but with the following rules:
Lambda may also be used to create anonymous procedures for use in GUI callbacks.
Lambda Examples
Here is a simple example of a lambda function.
The result is: 64
Here is an example using two arguments:
The result is: 5
A lambda function may be used inside a regular function.
The result is: 7
Map function
A lambda function may be used with a map function to process a sequence of values.
The result is: [1, 4, 9, 16]
Reduce function
The function reduce(func, seq) continually applies the function func() to the sequence seq. It returns a single value.
The following sum a list of numbers.
Result: 113
These statements find the maximum in a list.
Result: 102
Calculate the sum of the numbers from 1 to 100:
Result: 5050
* * *
Tom Irvine
Python has decimal and fraction classes. These classes provide functions for fraction arithmetic and for conversion between fraction and decimal format.
import decimal,fractions
Here is a demonstration script: fraction_demo.py
Tom Irvine
Gnuplot is a portable command-line driven graphing utility for Linux, OS/2, MS Windows, OSX, VMS, and many other platforms. The source code is copyrighted but freely distributed (i.e., you don’t have to pay for it). It was originally created to allow scientists and students to visualize mathematical functions and data interactively, but has grown to support many non-interactive uses such as web scripting
Gnuplot can be opened as a subprocess within a Python script.
The follow lines of code are required for the case of the sample program running in Windows or Linux:
from subprocess import Popen, PIPE
import platform
if platform.system() == ‘Windows’ or platform.system() == ‘Linux’:
Here is the sample script which generates a gnuplot file, saves it to a folder, then loads it into gnuplot.
Windows & Linux version: python_gnuplot_demo.py
Here is the data file used in the demonstration: drop.txt
See also:
Tom Irvine
Here is a method.
The input data may be either space, tab, or comma delimited.
##########################################################################
import os
import re
from numpy import array,zeros,concatenate,linspace,std
from sys import stdin
import matplotlib.pyplot as plt
########################################################################
def start():
print(” “)
print(“Entpath =stdin.readline()
file_path = input_file_path.rstrip(‘\n’)
if os.path.exists(file_path):
print “This file exists”
print ” ”
infile = open(file_path,”rb”)
lines = infile.readlines()
infile.close()
if not os.path.exists(file_path):
print “This file doesn’t exist”
start()
return lines
########################################################################
def lines_two_columns():
#
# http://flockhart.virtualave.net/RBIF0100/regexp.html
#
lines=start()
a = []
b = []
num=0
for line in lines:
#
if re.search(r”(\d+)”, line): # matches a digit
iflag=0
else:
iflag=1 # did not find digit
#
if re.search(r”#”, line):
iflag=1
#
if iflag==0:
line=line.lower()
if re.search(r”([a-d])([f-z])”, line): # ignore header lines
iflag=1
else:
line = line.replace(“,”,” “)
col1,col2=line.split()
a.append(float(col1))
b.append(float(col2))
num=num+1
return a,b,num
##########################################################################
a,b,num =lines_two_columns()
* * *
Tom Irvine
This project demonstrates wrapping C/C++ functions in Cython. It also shows how to pass numpy arrays to C/C++ arrays and vice versa.
There are potential execution speed advantages to this mixed language approach.
The sample source code uses this approach to calculate a Fourier transform from a time history signal.
The scripts on this page require the utility module tompy.py
The C/C++ source code and its header file are: fourier_ccode.cpp & fourier_ccode.h
The Cython file and its setup script are: fourier_trans.pyx & ft_setup.py
The Cython & C/C++ files are compiled in command-line via: python ft_setup.py build_ext –inplace
The main Python file is: fourier_c.py
This project was developed using the reference material at: Wrapping Cython
Tom Irvine
The follow set of scripts calculate the response of a specific single-degree-of-freedom system to an arbitrary base input time history, via the Runge-Kutta fourth order method.
The scripts also demonstrate the passing of numpy arrays to the function, which processes the the data and then returns the resulting arrays to the main Python script.
The scripts on this page require the utility module tompy.py
The function is defined in: sdof_rk4.pyx
The setup file is: sdof_rk4_setup.py
The function is complied in command-line mode via: python sdof_rk4_setup.py build_ext –inplace
The main Python script which imports the function is: arbit_rk4_c.py
Tom Irvine
Introduction
Cython is a compiler which compiles Python-like code files to C code. The resulting functions can then be imported into other Python scripts.
This method can be used to increase the execution speed of a Python script, particularly if the script uses for-loops.
The Python-like *.pyx script which provides the function must have have static C data types in order for the main Python script to gain full speed performance.
Installation
Cython can be installed on a Ubuntu system using the “Ubuntu Software Center.”
It is also bundled with the Enthought Python Distribution [EPD] and with Sage Notebook.
Steps
Using Cython consists of these steps:
1. Write a .pyx source file for the function
2. Write a setup.py file using the disutils function
3. Compile the source code in command-line mode using: python setup.py build_ext –inplace
4. Import the function into the main Python script and then run it
There are a few alternative compiler methods, but disutils is the most reliable from the author’s experience.
Examples
Tom Irvine
Vibrationdata Python 