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Motivation DAMARIS Front End: Basics DAMARIS Front End: Advanced Concepts Final Remarks

DAMARIS - An Introduction and Tutorial

Dr. Markus Rosenstihl

Condensed Matter Physics Institute – AG Vogel – Technische Universitat Darmstadt

10.12.2014

Dr. Markus Rosenstihl AG Vogel – Technische Universitat Darmstadt 1/19


1 MotivationOverview and Design PrinciplesArchitecture

2 DAMARIS Front End: BasicsExample: FIDExample: Pulse Length MeasurementsExample: Phase Cycling

3 DAMARIS Front End: Advanced ConceptsExample: Feed BackExample: Temperature ControllerExample: Digital Attenuator

4 Final RemarksOutlook and Future Development



Motivation

DAMARIS stands for . . .

DArmstadt MAgnetic Resonance Instrumentation Softwareby Dr. Achim Gadke, AG Fujara (2005)

Why DAMARIS?

replace good, but aged, home made systemDOS based, ISA/Vesa bus cards

flexible control of home made/non standard hardwarestep motor/piezo positioning system for mechanical field cyclingcontrol of fast field cycling power supply (1 kA)PFG power supply

modern data acquisition hardware (PCI, PCI Express)much higher sampling rate, resolution, number of samples

flexible storage of resultsany ASCII format (CSV, Simpson, etc.)efficient binary format (HDF5)

currently 9.5 spectrometers are running DAMARIS



DAMARIS Architecture I

DAMARIS

front endback end

hardware data

Separation of tasks

Do one thing and do it good:

user interaction only with front end (GUI)

back end responsible for hardware

back end modifications usually not needed after initial setup

Instrumentation only

DAMARIS is for instrumentation, not analysis (possible, but non-interactive)



DAMARIS Architecture II

back end front end

RESULTS

JOBS

Back end

written in C++

hardware interface

jobs read from XML files

results saved in XML result files

Front end

GUI completely in Python

experiment design in Python

jobs written to XML files

data read from XML result files



DAMARIS Architecture III — Back End Processing

Processing principle

states describe experiment: pulse, wait, record data, etc.

states are converted to pulse programmer logic by state traversal

12. Wait3. Pulse 1

9. Loop n=10

1. Experiment

4. Wait

10. Wait5. PFG pulse on11. Pulse

7. Wait

8. Pulse 2

13. Pulse

6. PFG pulse off

2. Set RF source

repeat

5. PFG on 6. PFG off

1. Experiment

4. Wait 7. Wait

……



DAMARIS Architecture III — Back End Processing

Processing principle

states describe experiment: pulse, wait, record data, etc.

states are converted to pulse programmer logic by state traversal

12. Wait3. Pulse 1

9. Loop n=10

1. Experiment

4. Wait

10. Wait5. PFG pulse on11. Pulse

7. Wait

8. Pulse 2

13. Pulse

6. PFG pulse off

2. Set RF source

repeat

5. PFG on 6. PFG off

1. Experiment

4. Wait 7. Wait

……



Supported Hardware

Pulse Programmer

SpinCore PulseBlaster 24bit

SpinCore PulseBlaster DDS III

ADC Acquisition Cards

Spectrum M2i40xx Series

Spectrum MI40xx Series

TiePie Handyscope HS3

Auxiliary

TecMag DAC-20

PTS Frequency Synthesizers(PTS-310, PTS-500)

Hardware coupled to software

Extending back end for other/additional hardware not trivial, but possible.Example: M2i40xx integration in 2012 by Stefan Reutter (PhD student).MI40xx driver source only available with NDA, binaries are freely distributable.



User Interface (Front End)

Experiment Script Result Script Log

Display Configuration

Display Source

Rudimentary Python for experiment and result scripts

Python programming language is easy!

all Python features usable: lists, if/else, for/while loops, etc.

lots of Python libraries, i.e. numpy/scipy (similar to Matlab)



DAMARIS ”Hello World” – Recording an FID

Experiment script

1 def fid_experiment(): # function describing the experiment2 e = Experiment() # begin sequence3 e.ttl_pulse(length=1e-6, value=1) # gating4 e.ttl_pulse(length=2e-6, value=1+2) # RF pulse + gating5 e.wait(length=10e-6) # dead time6 e.record(samples=1024, frequency=2e6, sensitivity=2) # ADC setup7 return e89 def experiment(): # function is executed by front end

10 for i in xrange(10): # repeat 10 times11 yield fid_experiment() # run experiment

Result script

1 def result():2 for timesignal in results: # loop over the incoming results3 data["Timesignal"] = timesignal # provide the timesignal to display



DAMARIS ”Hello World” – Recording an FID

Experiment script

1 def fid_experiment(): # function describing the experiment2 e = Experiment() # begin sequence3 e.ttl_pulse(length=1e-6, value=1) # gating4 e.ttl_pulse(length=2e-6, value=1+2) # RF pulse + gating5 e.wait(length=10e-6) # dead time6 e.record(samples=1024, frequency=2e6, sensitivity=2) # ADC setup7 return e89 def experiment(): # function is executed by front end

10 for i in xrange(10): # repeat 10 times11 yield fid_experiment() # run experiment

Result script

1 def result():2 for timesignal in results: # loop over the incoming results3 data["Timesignal"] = timesignal # provide the timesignal to display



Example: Pulse Length Measurements

Experiment script

Modifications:

modifying parameters programmatically ( <= )

handing over information to result script

1 def fid_experiment(p90): # <= function takes parameter!2 e = Experiment()3 e.set_description("p90", p90) # <= hand over value to result script4 e.ttl_pulse(length=1e-6, value=1)5 e.ttl_pulse(length=p90, value=1+2) # <= variable pulse length p90!6 e.wait(length=10e-6)7 e.record(samples=1024, frequency=2e6, sensitivity=2)8 return e9

10 # this function is executed by front end11 def experiment():12 p90_list = lin_range(1e-6,3e-6,10) # <= 10 values, from 1 to 3 us13 for p in p90_list: # <= loop through list14 yield fid_experiment(p90=p) # <= run experiment




Experiment script

Modifications:

modifying parameters programmatically ( <= )

handing over information to result script

1 def fid_experiment(p90): # <= function takes parameter!2 e = Experiment()3 e.set_description("p90", p90) # <= hand over value to result script4 e.ttl_pulse(length=1e-6, value=1)5 e.ttl_pulse(length=p90, value=1+2) # <= variable pulse length p90!6 e.wait(length=10e-6)7 e.record(samples=1024, frequency=2e6, sensitivity=2)8 return e9

10 # this function is executed by front end11 def experiment():12 p90_list = lin_range(1e-6,3e-6,10) # <= 10 values, from 1 to 3 us13 for p in p90_list: # <= loop through list14 yield fid_experiment(p90=p) # <= run experiment




Result script I

Modifications:

retrieve parameters

storage/display

1 def result():2 for ts in results:3 p90 = ts.get_description("p90") # <= retrieve value4 data["Timesignal %e"%p90] = ts # <= create unique name for results

Note: data

Containera for results (data pool):

viewable in display tab

stored in data pool file (HDF5 file)

aPython dictionary




Result script II

Modifications

retrieve parameters

storage/display + preliminary analysis

1 def result():2 signals = MeasurementResult() # <= "table" to store data3 for timesignal in results:4 p90 = timesignal.get_description("p90")5 signals[p90] = timesignal.y[0].max() # <= store signal maximum6 data["Pulse length"] = signals # <= display table7 data["Timesignal %e"%p90] = timesignal

Note: timesignal

holds time, real and imaginary part (x, y[0], y[1])

indexing, selection, i.e. values between index 10 and 20: y[0][10:20]

features: max, mean, etc., i.e. mean peak value: y[0][10:20].mean()



Example: Phase Cycling

Modifications for CYCLOPS phase cycling

change receiver phase

data routing

Experiment script

1 def fid_experiment(p90, phase): # <= function takes new parameter!2 e.set_description("phase", phase) # <= hand over value to result script3 e.set_phase(phase) # <= change reference phase (degrees)4 e.record(samples=1024, frequency=2e6, sensitivity=2)

Result script

1 accu = Accumulation() # <= special type for accumulating signals2 tmp = timesignal + 0 # <= create copy to be modified3 phase = timesignal.get_description("phase")4 if phase == 90:5 tmp.y[0] = timesignal.y[1] # <= switch real with imaginary part6 tmp.y[1] = -timesignal.y[0]7 accu += tmp # <= add timesignal



Covered until now

Basics:variable experimentsbasic information extractionaccumulation

Limitations:experiments independent of resultasynchronous work flowinformation flow from experiment to result script

Advanced concepts

Synchronization:react to results (feed back)wait for external conditions (stable temperature)

Communication with auxiliary devices:serial connections are easy!digitally controlled attenuator



Feed Back: Stop Accumulation if SNR is Reached

Experiment script

1 def experiment():2 SNR=03 while SNR <= 100: # loop while SNR <= 1004 yield fid()5 synchronize() # wait for result script6 SNR = float(open("snr.dat").read()) # read SNR from file

Result script

1 accu = Accumulation()2 for ts in results:3 accu += ts4 noise = accu.y[0][-128:].std() # std. dev. of last 128 points5 SNR = accu.y[0].max()/noise6 open("snr.dat","w").write("%.2f"%noise) # write SNR to file

Note: synchronize()

stop writing job files until results are processed



Auxiliary Devices: Temperature Controller

Wait until criteria is met

Simplistic implementation:

read temperature in fixed intervals

start experiment when set temperature is reached

Experiment script

1 import serial2 from time import sleep34 def experiment():5 s = serial.Serial("/dev/ttyUSB0") # connect to serial device6 T = 07 while T != 300: # loop8 s.write("KRDG?\n") # request current T9 T = float( s.readline() ) # receive response

10 sleep(10) # wait 10 s11 yield fid() # condition met: start experiment12 s.close() # close connection



Digital Attenuator

Pulse shaping with digital attenuator

switch attenuator during pulse(GATE + RF)

multiple attenuation steps

parallel interface

-1 dB

-2 dB-4 dB

Line 2

Line 3

Line 4

-5 dB = -1 dB + -4 dB = Line 2 + Line 4

GATE

RF TTL



Digital Attenuator

Experiment script

1 def fid_experiment(p90):2 e = Experiment()3 e.ttl_pulse(length=1e-6, value=1)4 # Gate + RF = 20 + 21 = 35 # -1 dB = 22 = 46 # -5 dB = 22 + 24 = 207 e.ttl_pulse(length=p90/3, value=3 + 20) # <= GATE + RF -5 dB8 e.ttl_pulse(length=p90/3, value=3 + 4) # <= GATE + RF -1 dB9 e.ttl_pulse(length=p90/3, value=3 + 20) # <= GATE + RF -5 dB

10 e.wait(length=10e-6)11 e.record(samples=1024, frequency=2e6, sensitivity=2)12 return e

Simplistic example

min. state length PulseBlaster: 90 ns

typical attenuation step: 0.5 dB

practical example: B. Kresse BSc. Thesis 2008



Final remarks

Current state

in use for over 8 years: very stable, hardly crashes

mainly used with Debian/GNU Linux: DAMARIS packages ready to install

proven to be flexible and very adjustable

two external installments (beside Darmstadt):TU Dortmund (Prof. Roland Bohmer)FU Berlin (Prof. Hans-Martin Vieth, retired)

not difficult to learn, but uncommon concept

Future development

slow but steady, not many (back end) developers

constant adjustments needed, i.e. new OS release meansupdated/deprecated libraries

features geared for AG Fujara/Vogel: TD NMR, single nuclei

more work on documentation needed (updating, more user oriented)



Final remarks

Current state

in use for over 8 years: very stable, hardly crashes

mainly used with Debian/GNU Linux: DAMARIS packages ready to install

proven to be flexible and very adjustable

two external installments (beside Darmstadt):TU Dortmund (Prof. Roland Bohmer)FU Berlin (Prof. Hans-Martin Vieth, retired)

not difficult to learn, but uncommon concept

Future development

slow but steady, not many (back end) developers

constant adjustments needed, i.e. new OS release meansupdated/deprecated libraries

features geared for AG Fujara/Vogel: TD NMR, single nuclei

more work on documentation needed (updating, more user oriented)


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