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Psocake Tutorial

Sections in this tutorial

Psocake is a graphical user interface (GUI) for looking at detector images at LCLS. By the end of this tutorial, you will be able to generate mask, find peaks in your images and index crystal diffraction patterns.

  1. Starting psocake
  2. Mask making
  3. Peak finding
  4. Jumping to interesting images based on the number of peaks

  5. Indexing crystals

 

Starting psocake

 

Make sure you have the psana environment setup (psana python Setup) before starting this tutorial. Also, check out a kerberos ticket by typing “kinit” which is needed for communicating with the experiment e-Log.

Type "psocake" on your terminal to open up the GUI: 

$ psocake

 

1) There are four parameters required to uniquely identify an image at LCLS. Type the experiment name, run number, detector name, and event number in the Experiment Parameters panel.

For this tutorial, we will look at experiment cxitut13, run 10, detector DscCsPad, event 11.

Note that available detector names will be printed on the terminal once you have typed in the experiment name and the run number. 
#######################
# Available detectors:  ['DscCsPad']
#######################

2)  You can specify the experiment parameters as command line arguments in psocake using the psana-style experiment run string:

$ psocake exp=cxitut13:run=10 -d DscCsPad -n 11

3)  You can also use the -e and -r arguments for the experiment and the run number:

$ psocake -e cxitut13 -r 10 -d DscCsPad -n 11

Don’t worry if you don’t remember these arguments. For argument options, use --help:

$ psocake --help

Mask making

In this example, let's mask out pixels that should not be used for analysis, mask out the jet streak at the centre of the detector, and mask out the water ring.

1) On the mask panel, click on "Use psana mask". This will mask out the following pixels that should not be used for analysis; calib, status, edge, central, unbonded pixels, unbonded pixel neighbor pixels. These pixels are shown as green on the image panel.

2) On the mask panel, click on "Use streak mask". This will mask out strong intensities originating from the edges of the central asics.

3) To make a donut mask over the water ring, click on "Use user-defined mask". This will bring up a cyan circle and cyan square mask generator.

Select "Toggle" in Masking mode. Move the cyan circle to the centre of the detector by dragging the circle. Resize the cyan circle by dragging the diamond on the perimeter. Once you are happy with the position, click "mask circular ROI" button on the mask panel.

Increase the cyan circle again by dragging the diamond on the perimeter. Click "mask circular ROI" button on the mask panel. Because we are in the "toggle" mode, the previous mask gets toggled and disappears. The area that does not overlap with the previous mask get masked out.

To save the user-defined mask, click on "Save user-defined mask" on the mask panel which will save the mask in the scratch folder. For this example, the mask will be saved here:

/reg/d/psdm/cxi/cxitut13/scratch/<username>/psocake/r0010/mask.npy (3D ndarray)

/reg/d/psdm/cxi/cxitut13/scratch/<username>/psocake/r0010/mask.txt (2D text)

You can load the user-defined mask using the "Load user-defined mask" button and selecting mask.npy.

Peak finding

 

To find the Bragg peaks on the image, set the "Algorithm" to “Droplet” in the Peak Finder panel.
Examine the peaks found by zooming in/out with the middle mouse scroll (or a two finger slide on a Mac touchpad). Notice that the Bragg peaks are composed of 2 to 6 connected pixels. Setting the radius to 2 sets a 5x5 cyan boundary around the Bragg peaks (radius x 2+1 = 5). Change the following values in the Peak Finder panel.
  • Set npix_min: 2
  • Set npix_max: 5
  • radius: 2

Hover the mouse pointer over the Bragg peaks to study the intensities. The sum of the Bragg peak pixels are above 400 ADUs. Set the following values:

  • Set atot_thr: 400
Move the green square over the water ring to study the level of background noise in the ROI Histogram panel. Notice that the water ring intensities can go up to 160 ADUs. Signal to noise ration seems to be around 4, so set the following values.
  • thr_low: 160
  • thr_high: 160
  • son_min: 4

 

You can jump to other events to see if your peak parameters are well tuned. Once you are happy, launch the peak finder on our cluster.

The output directory on the peak finder panel should already be automatically set to: /reg/d/psdm/cxi/cxitut13/scratch/<username>/psocake

Since we are analyzing run 10, /r0010 directory will be generated under the output directory.
The default setting will analyze run 10 on psanaq with 24 CPUs. Number of events to process set to 0 analyzes all the events.
Click "Launch peak finder”. For this demo,
  • CPUs: 3
  • Number of events to process: 30
The CXIDB filename being generated is in the following format: <experiment name>_<4-digit run number>.cxi (i.e., cxitut13_0010.cxi) 

Jumping to interesting images based on the number of peaks

Once you have submitted the peak finder job, let's plot the number of peaks found for each event.

In the small data panel, type the CXIDB filename:

  • filename: /reg/d/psdm/cxi/cxitut13/scratch/<username>/psocake/r0010/cxitut13_0010.cxi
  • metric_dataset: /entry_1/result_1/nPeaksAll
"/entry_1/result_1/nPeaksAll" is an array containing number of peaks found for each event. Unfortunately the naming convention is cryptic, but it is how it is named inside a CXIDB file.
This should load a plot of all the peaks found so far per event. Click "Refresh" to update the plot if your batch job is still running.
You can click on the red marker in the plot to jump to the corresponding events. These lysozyme diffraction patterns have between 15 to 60 peaks.

Indexing crystals

Let's try to index the diffraction pattern at event 11.

  • In the experiment parameters panel, set Event Number to 11.

In the indexing panel, tick "Indexing on". Indexed peaks will be marked with magenta circles. These triple rings represent the integration radius.

Hopefully, you have indexed this diffraction pattern. Notice that the unitcell parameters are a bit off compared to what is expected. Let's load a CrystFEL unitcell file to help the indexer along.

  • In the indexing panel, set the PDB field to: /reg/d/psdm/cxi/cxitut13/scratch/psocake/lys.cell
CrystFEL unit cell file version 1.0
lattice_type = tetragonal
centering = P
unique_axis = c
a = 77.05 A
b = 77.05 A
c = 37.21 A
al = 90 deg
be = 90 deg
ga = 90 deg

 

You should notice that the reindexed result will match the known unit cell parameters more closely.
It is often the case at the beginning of a beamtime that the detector distance to the interaction point (coffset) is not well known, and we can use the diffraction geometry panel to find this distance.
  • In the diffraction geometry panel, set "Detector distance" to 156mm. Try incrementing this distance in 1mm step till the unit cell parameters are as close as possible to lys.cell. The optimum detector distance is around 158mm.
  • Try drawing a resolution ring on top of the water ring by using “Resolution (pixels)” field. If your detector distance is correct, the crystallographic resolution ring should display 3.4A.

Future plans

 

  • More mask shapes
  • More integration with logbook
  • Extend the crystallography analysis to XPP and MFX beamlines
  • cctbx-xfel support

 

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