Python for Scientists: Data Acquisition and Analysis
•Download as PPTX, PDF•
6 likes•1,904 views
This is a presentation about using the programming language Python in science and research.
![Python: Qu'est-ce que c'est? Multi-paradigm (objectoriented, functional…) print“Easy as…“ fori in [1,2,3]: printi ctypes,sockets,files,regex,… Matplotlib,SciPy,NumPy,PyQT,…](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Similar to Python for Scientists: Data Acquisition and Analysis
Similar to Python for Scientists: Data Acquisition and Analysis (20)
More from Andreas Dewes
More from Andreas Dewes (8)
Recently uploaded
Recently uploaded (20)
Python for Scientists: Data Acquisition and Analysis
- 1. Python forScientists Dewes Quantronics Group Seminar
- 2. Python: Qu'est-ce que c'est? Multi-paradigm (objectoriented, functional…) print“Easy as…“ fori in [1,2,3]: printi ctypes,sockets,files,regex,… Matplotlib,SciPy,NumPy,PyQT,…
- 3. Whytouseit: A Scientific Workflow
- 6. Data Acquisition http://pyvisa.sourceforge.net http://docs.python.org/library/ctypes.html
- 8. Directly process & analyze measured data
- 12. Data Analysis http://www.scipy.org http://numpy.scipy.org
- 13. SciPy & NumPyExample importscipy.optimize #Define the model to befitted fitfunc= lambda p, x: p[0]+p[1]* exp(-x*abs(p[2]))*cos(p[3]+p[4]*x) #Define the errorfunction errfunc = lambda p, x, y: fitfunc(p, x)– y #Make a fit by minimizing the errorfunction p1 = scipy.optimize.fmin(lambdap,x,y: norm(errfunc(p,x,y)), p0, args=(data [:,0], data[:,1])) #Print the returnedparameters print p1 #Plot the data and the fit… plot(data[:,0], data[:,1], "ro", data[:,0], fitfunc(p1, data[:,0]), "b-") #Add a legend legend(("data","fit")) #Add a title title("Ramsey - $V_{fluxline}= %d mV$, $T_2 = %d$ ns, $A = %f$ " % (int(voltage) , abs(int(1.0/p1[2])),p1[1]))
- 14. Presentation & Visualization http://matplotlib.sourceforge.net/ http://qt.nokia.com/
- 15. MatplotlibExamples grid()#Add gridlinestotheplot #Plot 4 datasets plot(x1,y1,x2,y2,x3,y3,x4,y4) #Add a legend legend((“Amplification…“,“…“)) #Set theaxislabels xlabel(“frequency[GHz]“) ylabel(“attenuation[dB]“) #Save thefigureas a PDF savefig(“attenuation.pdf“) jet() #Select a colorsheme #Plot the matrix imshow(dataMatrix,aspect = 'auto',origin = 'lower',extent = (xmin,xmax,ymin,ymax)) xlabel("$A$ [V]") ylabel("$f$ [GHz]") #Use Latex for text… title("Qubit 1 – Modulated by $V_{flux2} = A dot in{(20 MHz dot 2i t)}$")
- 17. PyQTExample: Instrument frontpanels title = QLabel(„Qubit 1") splitter = QSplitter(Qt.Horizontal) SetButton= QPushButton("Set") splitter.addWidget(SetButton) #... grid = QGridLayout(self) grid.addWidget(title,0,0) grid.addWidget(QLabel("Voltage"),1,0) #... self.connect(SetButton,SIGNAL("clicked()"),self.changeVoltage)self.setLayout(grid) Or use Qt Designer:
- 18. HowToGetStarted 1. Download it… 2. Check out thedocumentation & tutorial (online) 3. Go &contributetotheWiki 4. Askyourcolleagues… http://www.python.org http://docs.python.org/tutorial/ http://wiki-quantro.extra.cea.fr
- 19. That‘s it.
- 20. Object HirarchyExample Dispatcher Subject Reloadable ThreadedDispatcher Instrument RemoteInstrument VisaInstrument VNA AgilentMWG Yokogawa Acqiris