Dies ist die Support Website des Buches:
Das Python Praxisbuch
Der große Profi-Leitfaden für Programmierer
Farid Hajji
Addison Wesley / Pearson Education
ISBN 978-3-8273-2543-3 (Sep 2008), 1298 Seiten.
17. Python für Wissenschaftler¶
Das Computer Algebra System sympy¶
Screenshots:
sympy installieren¶
URLs:
- Die Sympy Website (aber mit
easy_install sympyinstallieren)
Die Datentypen Rational, Real und Integer¶
Ein paar Konstanten¶
Ausdrücke¶
Reihen¶
Pattern Matching¶
Lineare Algebra¶
Matrizen erzeugen¶
Matrizenoperationen¶
Screenshots:
Die Funktion CreateMatrix:
def createMatrix(rank):
"Create a rank x rank matrix full of symbols"
varlist = []
for i in range(rank):
for j in range(rank):
varlist.append(Symbol("x%d%d" % (i+1,j+1)))
return Matrix(rank, rank, varlist)
Anwendung: Lösung linearer Gleichungen¶
Anwendung: Eigenwerte und Eigenvektoren¶
Effiziente numerische Berechnungen mit numpy und scipy¶
Screenshots:
URLS:
- Die Scipy Homepage
- Basic Linear Algebra Library (BLAS)
- Automatically Tuned Linear Algebra Software (ATLAS)
numpy¶
numpy unter Unix installieren¶
Wie finde ich mich in numpy zurecht?¶
#!/usr/bin/env python
# introspectme.py -- helper functions to inspect large modules
import inspect
def modules(module):
"Returns a list of submodules of module"
return [m[0] for m in inspect.getmembers(module)
if inspect.ismodule(m[1]) ]
def functions(module):
"Returns a list of functions of module"
return [m[0] for m in inspect.getmembers(module)
if inspect.isfunction(m[1])]
Der array-Datentyp aus numpy¶
Gleichungssysteme lösen¶
Nullstellen eines Polynoms¶
Fourier-Transformationen¶
Lineare Algebra¶
Plotten mit pylab (a.k.a. matplotlib)¶
URLs:
#!/usr/bin/env python
"""
Example: simple line plot.
Show how to make and save a simple line plot with labels, title and grid
"""
import numpy
import pylab
t = numpy.arange(0.0, 1.0+0.01, 0.01)
s = numpy.cos(2*2*numpy.pi*t)
pylab.plot(t, s)
pylab.xlabel('time (s)')
pylab.ylabel('voltage (mV)')
pylab.title('About as simple as it gets, folks')
pylab.grid(True)
pylab.savefig('simple_plot')
pylab.show()
#!/usr/bin/env python
# From Matplotlib Cookbook
from pylab import plot, show, ylim, yticks
from matplotlib.numerix import sin, cos, exp, pi, arange
t = arange(0.0, 2.0, 0.01)
s1 = sin(2*pi*t)
s2 = exp(-t)
s3 = sin(2*pi*t)*exp(-t)
s4 = sin(2*pi*t)*cos(4*pi*t)
t = arange(0.0, 2.0, 0.01)
plot(t, s1, t, s2+1, t, s3+2, t, s4+3, color='k')
ylim(-1,4)
yticks(arange(4), ['S1', 'S2', 'S3', 'S4'])
show()
#!/usr/bin/env python
# From Matplotlib Cookbook
from pylab import figure, show, setp
from matplotlib.numerix import sin, cos, exp, pi, arange
t = arange(0.0, 2.0, 0.01)
s1 = sin(2*pi*t)
s2 = exp(-t)
s3 = sin(2*pi*t)*exp(-t)
s4 = sin(2*pi*t)*cos(4*pi*t)
fig = figure()
t = arange(0.0, 2.0, 0.01)
yprops = dict(rotation=0,
horizontalalignment='right',
verticalalignment='center',
x=-0.01)
axprops = dict(yticks=[])
ax1 =fig.add_axes([0.1, 0.7, 0.8, 0.2], **axprops)
ax1.plot(t, s1)
ax1.set_ylabel('S1', **yprops)
axprops['sharex'] = ax1
axprops['sharey'] = ax1
# force x axes to remain in register, even with toolbar navigation
ax2 = fig.add_axes([0.1, 0.5, 0.8, 0.2], **axprops)
ax2.plot(t, s2)
ax2.set_ylabel('S2', **yprops)
ax3 = fig.add_axes([0.1, 0.3, 0.8, 0.2], **axprops)
ax3.plot(t, s4)
ax3.set_ylabel('S3', **yprops)
ax4 = fig.add_axes([0.1, 0.1, 0.8, 0.2], **axprops)
ax4.plot(t, s4)
ax4.set_ylabel('S4', **yprops)
# turn off x ticklabels for all but the lower axes
for ax in ax1, ax2, ax3:
setp(ax.get_xticklabels(), visible=False)
show()
Screenshots:
