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Using Gatan K2 Summit in Leginon » History » Version 8

Anchi Cheng, 07/19/2013 11:22 AM

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h1. Using Gatan K2 Summit in Leginon
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The main use of K2 Summit is in Counted or Super-resolution mode in combination with dose fractionation (frame saving).
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If you want to use DM's dose fractionation, activate the "save frames" check box in the particular preset camera configuration.  You can also use DM's frame alignment algorithm by activating "align frames" check box, but the latter is not recommended since the alignment in DM will delay the return of the image to Leginon and therefore affects throughput greatly.
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h2. Configuration
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# Make sure your camera configuration is set to [[Leginon image orientation]] and instruments.cfg matches that resulting orientation and dimension.
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** This is likely 270 degree rotated with a flip. New version of DM can acquire its internal darkware gain references in this configuration.
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# K2's dose fractionation (frame saving) only works with full camera dimension without binning.
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# K2 interface in DM restricts the exposure time to multiple of some set number, depending on the mode.  When you enter in DM an invalid number, it automatically change it to the valid one when you click the acquire button.  pyscope/dmsem.py has hard-coded values for these precision. Compare them to the precision of the DM version you have since it may change with DM version.
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# K2 frame exposure time is adjustable in Leginon gui.  However, you need to check if the number is acceptable by DM.
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h2. Preset Recommendation
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See [[Pre-MSI_Set-up#Preset-Design-Example-for-small-pixel-Gatan-K2-camera-alone]] specific for K2 camera.
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h2. Calibrations
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Most calibration and operation are similar to that of a typical digital camera.
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Leginon treats linear/counted/super-resolution modes of K2 Summit as three cameras.  Therefore, each needs its own calibrations.
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A python script is available to make the copying of the calibrations easier.  See message#1498.  You may need to modify it for different modes you are copying calibrations to.
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h2. Gain/Dark Correction Handling
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Leginon receives images from DM  without software gain correction.   This means gain correction is still needed in Leginon.
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h3. Counted/Super-Resolution mode
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# The hardware correction has been applied in DM before counting.  Therefore, the "raw" image Leginon get are integers and roughly gain corrected.
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# The dark image in Leginon should always be 0.  Therefore, acquiring dark image only need to be done once per camera configuration.  There is also no need to average several images in the making.
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# The bright image acquired in Correction node should be taken at the dose rate to be used.  It should also be taken at close to the total exposure time such as 4-5 s, and a large number of images should be used to get an average image (For example, 20).  Alternatively, take a single very long exposure (100 s).  This will account for variation in sensitivity of the pixels.  There is likely a general gradient across the detector known as growth zone.
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* Movie frames recorded in dose-fractionation or frame-saving mode are "raw".  Appion will use the bright/dark/correction plan of the image transferred to Leginon to make corrected frame during [[appion:GainDark correction of the raw frame with or without drift correction|frame stack making]].
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h3. Linear mode
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# The dark image will have a large mean and the value changes with exposure time.  Ideally, the dark images should therefore be taken at the same exposure time as the later images to be corrected.  Leginon can account for small differences but not a full range.
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# To avoid saturation by the accumulated dark current, long exposure in linear mode is not recommended.  0.5 s is typical.
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# Do not use frame saving with linear mode.  It is not worth while.
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h2. Operation
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# Gatan recommends update hardware dark reference every day which is supposed to keep the normalization in counted/super-resolution mode stable.  This procedure is done through DM under "K2 Direct Detection".
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** Set the mode to Counted (just in case).
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** Click on the botton "Update HW Dark Reference".  It will take about 3 minutes  No beam required.
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# Typical frame saving preset parameters for counted/super-resolution: 0.2 s frame exposure time, 4-5 s total exposure time at 8-10 e/physical pixel/s (Some argue that 5 e/physical pixel/s is better).  You can use DM's reading of dose rate while it is in counted mode and *UNBINNed* to get a reasonable estimate.
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# Because of its small size, we have a modified [[MSI_Quick-start_for_DD_only|Quick-start procedure]] we use regularly at NRAMM FEI F20.
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# /myami/rawtransfer.py should be run on the file server to transfer the raw frames as it is produced. See [[DDD_raw_frame_file_transfer]].  K2 frames are saved as mrc stacks.
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# See [[appion:Direct_Detector_Frame_Processing]] for tools used for processing the frames.
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# To gain correct and align the frames, start parallel instances of Appion makeDDRawFrameStack.py See [[appion:GainDark correction of the raw frame with or without drift correction]].
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h2. Leginon functions that do not work with K2 camera
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h3. General functions
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# The dose matching tool in Preset Manager.  K2's exposure time is not fine grained enough to make small adjustment according to the small dose deviation.  You will have to use fixed exposure time and adjust beam intensity by hand to achieve the right dose.  We find out the equivalent screen reading from the microscope for the acceptable 8-10 e/physical pixel/s dose rate for the detector and make adjustment there.
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h3. Frame saving camera functions
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# The image returned to Leginon display is always integrated over all the frames with K2 summit camera.  Selection of frames to use as in DE series does not work here.
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# Readout delay is not adjustable on K2.  Leave it at 0.
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h2. Clean up
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Frame saving generates a lot of files during acquisition and during processing.
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# python script in leginon directory "cleanddraw.py" can help you clean up the transferred raw frames when you start to run out of disk space.  See Feature #1784 for more details.
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# Selective removal of aligned frame stack in Appion runs is still to be written.