Error In Detector Gain Mosflm
Contents |
however, agree with Andrew's assessment that the default-chosen gain in MOSFLM is adequate for all practical purposes. Any error in GAIN will be almost exactly compensated for by a corresponding change mosflm download in Sdfac in SCALA, and the final value of sigma(I) will be essentially the same. mosflm tutorial The only possible difference will be in the sigma-based outlier rejection within MOSFLM, but since the typical errors in the sigma are
Mosflm Show Resolution Rings
only ~30%, I predict it will be hard to find a situation where this makes or breaks a structure determination. So, by way of explanation: there are three things that led me to this conclusion: 1)
Mosflm Citation
the control: fake data with all pixels independent. adjusting the GAIN as MOSFLM recommends from the BGRATIO analysis does, in fact, reproduce the "correct" value of the gain used to generate the fake data. In SCALA, Sdfac refines to ~1.0, SdB refines to 0, and Sdadd refines to the actual magnitude of fractional error (introduced by beam flicker, shutter jitter, etc.). No surprises here. 2) "blur" the fake data with the point-spread mosflm indexing function (PSF) empirically derived for my detector In this case, the "MOSFLM-refined gain" is too low. In SCALA, Sdfac refines to ~1.3, SdB refines to 3-5, and Sdadd is a bit low. These parameters are about what I see processing good real data. 3) use real data, but force MOSFLM to use the GAIN calibrated independently for the detector MOSFLM grumbles a lot about the BGRATIO. In SCALA, Sdfac refines to ~1, and SdB refines to ~0. Sdadd is consistent with my independently-measured fractional error sources. Now, I have not evaluated this approach on a huge number of data sets, but in this case the PSF was both necessary and sufficient to explain the "mystery of SdB". That is: the need for SdB arises because using an "incorrect" gain creates a correlation between Sdfac and Sdadd. I imagine there are other ways to get a non-zero SdB as well, but for "good data" I suspect this is the dominant mechanism. I never wrote this up because I am fairly certain the article would do nothing to improve the impact factor of the journal in which it was published, but this anecdote might perhaps be useful to Andrew, Phil, and a few other readers of this list. -James Holton MAD Scientist On 3/7/2011 2:00 AM, A L
(0) 1223-248011 Any constructive comments on this User Guide would be very welcome. Index Major Changes Help Library Important notes 1: Overview 1.1 Programs covered
Mosflm Reference
in this guide 1.2 Input and Output files 1.3 Allowed detector types ccp4i 1.3.1 Using the DETECTOR keyword 1.3.2 Using the SITE keyword 1.3 Allowed detector types 1.4 Inspection of images 2: pdb A Quick Guide 2.1 Startup keywords 2.2 Autoindexing 2.3 Estimating mosaic spread 2.4 Running the Strategy option 2.5 Determining oscillation angles with the TESTGEN option 2.6 Integrating the first image https://www.mail-archive.com/ccp4bb@jiscmail.ac.uk/msg20011.html to determine if the exposure time is OK 2.7 Interpreting those "WARNING" messages 2.8 Getting accurate cell parameters 2.9 Integrating a block of images 2.10 Integrating the dataset 3: Determination of crystal orientation, cell parameters and spacegroup 3.1 Autoindexing Interactively 3.2 Autoindexing when running the program in background 4: Running the STRATEGY and TESTGEN options 4.1 Overview of the STRATEGY option 4.2 http://structure.usc.edu/mosflm/ Some Examples of the STRATEGY options 4.3 Determining the oscillation angle for each image (TESTGEN option) 5: Determining Accurate Cell parameters 5.1 Using Post-refinement to refine the cell 6: Collecting data and processing the images 6.1 Overview 6.2 Special MOSFLM features 6.2.1 Accumulating profiles over several images 6.2.2 Addition of partials (ADDPART) 6.2.3 Post-refinement of orientation and cell parameters 6.2.4 Optimisation of measurement box parameters 6.3 Running a processing job 6.3.1 Running MOSFLM interactively 6.3.2 Processing the first block of data) (Non-interactively) 6.3.3 Finally, Processing the dataset 7: Interpreting the output 7.1 The log files 7.2 The summary file 7.3 Checking the quality of the data 8: General tips. 8.1 Estimating the GAIN of a detector 8.2 Processing images with no (or very few) fully recorded reflections 8.3 Processing images when the spots are not fully resolved 8.4 Processing data from other detectors, or standard detectors with different rotation axis orientation. 9: Example command files 9.1 Autoindexing an initial image (interactively) 9.2 Determining an accurate cell 9.3 Integrating a series of images Appendix I Changes in MOSFLM Appendix II Setting the measuremen
developed through a collaboration between Area Detector Systems Corp. and Cornell and Purdue Universities. The working routines include "DPS" programs from http://staff.chess.cornell.edu/~szebenyi/proc_gui/proc_gui_text.html Purdue and Cornell, an image display program from ADSC, and the Mosflm/CCP4 package from Andrew Leslie and the CCP4 group. Development of the software is continuing. This documentation is for Version 2.01, released August 2001. Comments on the programs themselves, and on this documentation, are welcome; send them to Marian Szebenyi. To process a set of data, error in type "process" for an initial run. If you already have a parameter file (created by a previous run of the program), you can type "process name", where "name.param" is the name of the parameter file. Process is a script that copies the necessary shell scripts ("command files") from a standard location to the current directory (if they're error in detector not already there), starts up processing_gui, and loads the specified parameter file, or a standard prototype if no filename is given. The main interactive window, part of which is shown here, will come up. Processing_gui stores information in a parameter file, whose name generally (but not necessarily) has a ".param" extension. This file is updated during processing and can be read in on a subsequent run. Area (1) of the main window allows you to specify a parameter file, load parameters from the file, and save parameters to the file. If you specify a non-existent file and click "SAVE", a new file will be created. It is good practice to make a new parameter file for each dataset: start by loading a file from a similar dataset, or the prototype, change parameters as necessary (see below), change the file name, and save it. A number of "command files" are needed to run the various programs which are part of the system. These are kept in a standard location and c