Difference between revisions of "Guide to roll-your-own python hddm transforms"
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===example 2: splitting files=== | ===example 2: splitting files=== | ||
| + | ===example 3: changing the run number=== | ||
| + | ===example 4: reordering your events=== | ||
| + | ===example 5: stripping out bits of hit information=== | ||
| + | ===example 6: mining data, making histograms=== | ||
Revision as of 12:54, 24 July 2018
At one time, if you wanted to catenate two similar hddm files, you might do it with "hddmcat", or maybe with "hddmcp", or "hddmcp_c". Or if you have been in the collaboration long enough, you might remember our old friend "hddm_merge_files". Each of these utilities had a specific purpose at one time, no two of them are quite identical. There are others that do slightly different things, such as "hddm-xml", "xml-hddm", "hddm_cull_events", etc. The purpose of this page is to convince you that ALL of these are obsolete, now that the hddm python module is available. Using the python shell, you can perform a much more general set of actions on hddm input files, including merging, splitting based on event inspection, and general transforms of the event content. All of this is illustrated with examples below.
First, you need to make sure that your shell environment is properly configured for using the standard GlueX software stack. To verify this, try the following command at your linux shell prompt. If this command returns without an error, you are all set to go. If it complains about the hddm_s module not being found, you need to find the appropriate setup_env script for your login shell, source it and try again.
python -c 'import hddm_s'
Contents
example 1: merging files
In the first example, we learn how to catenate two hddm files named "t1.hddm" and "t2.hddm" into a single output file "tcat.hddm" with a single command.
python -c 'import hddm_s;fout=hddm_s.ostream("tcat.hddm");[[fout.write(rec) for rec in hddm_s.istream(fin)] for fin in ("t1.hddm","t2.hddm")]'
This is more readable if we save it to a file and write it on multiple lines, as follows.
import hddm_s
fout=hddm_s.ostream("tcat.hddm")
fout.compression = hddm_s.k_z_compression
for fin in ("t1.hddm","t2.hddm"):
for rec in hddm_s.istream(fin):
fout.write(rec)
In this example, I introduced one new feature, the ability to turn on compression in an output stream simply by assigning one of the predefined constants to the compression attribute. If you save the above program to a file x.py and execute it as "python x.py" then it will produce a compressed version of tcat.hddm that you created earlier with the one-liner above. Clearly I can extend the number of input files by adding to the list ("t1.hddm", "t2.hddm"). Alternately, I can specify a list of input files on the command line and replace "("t1.hddm", "t2.hddm") with sys.argv[1:]. You would also need to add "import sys" to the file header.
If you are a python user then you know that the command "pydoc hddm_s" gives you a ready-made man page-style documentation on all of the object types and functions provided by the hddm_s module. The "_s" in hddm_s stands for simulation hddm files. For working with REST files, you would use hddm_r. Other than the one-letter difference, the usage is same.
