Team:EPF Lausanne/Software
Name | Description | |
---|---|---|
code2html | Script creating automatically HTML and CSS code from source files in Python, C++ or BASH. | Download |
ODEs Generator | Program generating automatically the ODEs governing our system from the circuit structure. | |
ODEs Solver | Program solving a system of non-linear ODEs given the initial condition. | Download |
code2html
The following Python script allows to generate HTML (and CSS) code from source files in C++ and Python languages. It is based on Pygment, a Python syntax highlighter. All code in our Wiki is formatted using this script.
This script accepts two command line arguments: the first argument is the name of the file to convert, the second one (optional) is to ask separate HTML and CSS files.
"""
Command:
######################################
python code2html INPUTFILE [CSS]
######################################
INPUTFILE: name (with path) of the file to convert to html
CSS: write "true" (ot "t", "yes", "y") in order to obtain separate .html and .css files ("false" by default)
"""
from pygments import highlight
from pygments.lexers import PythonLexer
from pygments.lexers import CppLexer
from pygments.lexers import BashLexer
from pygments.formatters import HtmlFormatter
# Code formatting style
style = "monokai"
# C++ extensions
cpp = ["cpp","cxx","cc","h"]
# Python extensions
py = ["py"]
# Bash extensions
bash = ["sh","bash"]
def load_file_as_sting(fname):
"""
Open the file FNAME and save all its content in an unformatted string
"""
content = ""
with open(fname,'r') as f: # Open the file (read only)
content = f.read() # Read file and store it in an unformatted string
# The file is automatically closed
return content
def save_string_as_file(fname,string):
"""
Save the unformatted string STRING into the file FNAME
"""
with open(fname,'w') as f: # Open the file (write only)
f.write(string)
# The file is automatically closed
def lexer_formatter(language,css=False):
"""
Return the lexer for the appropriate language and the HTML formatter
"""
L = None
if language in py:
# Python Lexer
L = PythonLexer()
elif language in cpp:
# C++ Lexer
L = CppLexer()
elif language in bash:
# Bash Lexer
L = BashLexer()
else:
raise NameError("Invalid language.")
HF = HtmlFormatter(full=not css,style=style)
return L, HF
def code_to_htmlcss(code,language):
"""
Transform CODE into html and css (separate files)
"""
# Obtain lexer and HtmlFormatter
L, HF = lexer_formatter(language,css=True)
# Create html code
html = highlight(code,L,HF)
# Create css code
css = HF.get_style_defs('.highlight')
return html,css
def code_to_html(code,language):
"""
Transform CODE into html and css (all in the same file)
"""
# Obtain lexer and HtmlFormatter
L, HF = lexer_formatter(language)
# Create fill html code
html = highlight(code,L,HF)
return html
import sys
if __name__ == "__main__":
"""
Command:
######################################
python code2html INPUTFILE [CSS]
######################################
INPUTFILE: name (with path) of the file to convert to html
CSS: write "true" (ot "t", "yes", "y") in order to obtain separate .html and .css files ("false" by default)
"""
# Command line arguments
args = sys.argv
# Check command line arguments
ncla = len(args) # number of command line arguments
if ncla != 2 and ncla != 3 :
raise TypeError("Invalid number of command line arguments.")
css_bool = False
if ncla == 3 and args[-1].lower() in ["true",'t',"yes",'y']:
css_bool = True # Export css separately
# Input file
fname_code = sys.argv[1] # Name of the file containing the code to convert in html
# Input file extension
language = fname_code.split('.')[-1]
# Output files
fname_html = fname_code.split('.')[0] + ".html" # Name of the file where the html code will be stored
fname_css = fname_code.split('.')[0] + ".css" # Name of the file where the css code will be stored
# Save code into a unformatted string
code = load_file_as_sting(fname_code)
if css_bool == False: # Convert to standalone html
html = code_to_html(code,language)
else: # Convert to html and css separately
html,css = code_to_htmlcss(code,language)
# Save html
save_string_as_file(fname_html,html)
if css_bool == True:
# Save css
save_string_as_file(fname_css,css)
ODE Generator
ODE Solver
The Python class Solver simplify the solution of a given system of non-linear ODEs. The user has to provide the function representing the system, the desired integration domain, the initial condition and the time step. The class takes care of solving the system and returns the solution at given time points and the time points themselves (ready to analyze/plot).
import numpy as np
from scipy.integrate import *
import matplotlib.pylab as plt
class Solver:
"""
Class that allows the solution of a system of non-linear ODEs. The system is specified by the function fun
dy/dt = fun(t,y)
where t is a number and y and dy/dt are numpy arrays or lists.
The solution is performed with the dopri5 method, an explicit runge-kutta method of order (4)5.
The method is due to Dormand & Prince, and is implemented by E. Hairer and G. Wanner.
See
http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.integrate.ode.html
for more details.
NOTE:
Our Solver need a function of the type fun(t,y).
In cases where the fun takes additional arguments funArgs(t,y,arg1,...) it is possible to create an alias:
fun = lambda t,y: funArgs(t,y,arg1,...)
The additional arguments are now contained in the alias and fun is of the type fun(t,y).
"""
def __init__(self,dt,fun,t0,T,y0):
self.dt = dt # Time step
self.fun = fun # Function representing the ODE
self.t0 = t0 # Initial time
self.T = T # Final time
self.y0 = y0 # Initial condition
def solve(self):
"""
Solve the system of ODEs
dy/dt = fun(t,y)
on the interval [t0,T], with the initial condition y(0)=y0.
Returns two lists, solution and time, containing time points and the solution at these time points.
"""
# Choose integrator type: dopri5 in this case
r = ode(self.fun).set_integrator('dopri5')
# Initialize the integrator
r.set_initial_value(self.y0, self.t0)
# Initialize solution list and time points list
solution = np.asarray(self.y0)
time = np.asarray(self.t0)
while r.successful() and r.t < self.T:
r.integrate(r.t + self.dt) # Perform one integration step, i.e. obtain the solution y at time t+dt
time = np.append(time,r.t) # Append the new time
solution = np.vstack((solution,r.y)) # Append the new solution
return time, solution # Return time and solution vectors
if __name__ == "__main__":
from test import * # Import test functions for the ODE integrator
# Our test functions:
# rapid_equilibrium (standard function)
# rapid_equilibrium_from_string() (returns a function compiled from a string)
dt = 0.1
t0 = 0
T = 100
y0 = [1,0,0]
# Store the compiled function
rapid_equilibrium_s = rapid_equilibrium_from_string()
mysolver = Solver(dt,rapid_equilibrium,t0,T,y0)
mysolver_string = Solver(dt,rapid_equilibrium_s,t0,T,y0)
t,y = mysolver.solve()
ts,ys = mysolver_string.solve()
plt.plot(t,y)
plt.plot(ts,ys)
plt.show()