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--- eman2:e3make3d_point [2026/03/20 16:24] – steveludtke
+++ eman2:e3make3d_point [2026/03/20 17:45] (current) – steveludtke
@@ Line 1: / Line 1: @@
-===== Preview of e3_make3d_point for better 3-D reconstructions =====
+===== Preview of e3make3d_point for better 3-D reconstructions =====
-THE METHOD DESCRIBED ON THIS PAGE IS NOT YET PUBLISHED, IT IS PROVIDED TO GIVE PEOPLE THE OPPORTUNITY TO TRY IT OUT AS WE MAKE FINAL IMPROVEMENTS. If you have any difficulties (or successes) with this method, please let us know, and feel free to ask questions (sludtke@bcm.edu).
+**THE METHOD DESCRIBED ON THIS PAGE IS NOT YET PUBLISHED, IT IS PROVIDED TO GIVE PEOPLE THE OPPORTUNITY TO TRY IT OUT AS WE MAKE FINAL IMPROVEMENTS**
+If you have any difficulties (or successes) with this method, please let us know, and feel free to ask questions (sludtke@bcm.edu).
 The under-development e3make3d_point.py can be used to produce reconstructions which:
@@ Line 15: / Line 16: @@
 ==== If you are starting with an EMAN2/3 project ====
-  * Run a standard e2spa_refine.py on your phase-flipped particle data
+  * Run a standard //e2spa_refine.py// on your phase-flipped particle data
-  * Run exactly the same command with the "--pointrecon 500" option added to the command-line, then compare the results of the 2 refinements.
+  * Run exactly the same command with the //--pointrecon 500// option added to the command-line, then compare the results of the 2 refinements.
   * 500 is the number of first-stage points to use in the reconstruction as described above.
@@ Line 26: / Line 27: @@
     * This involves making a copy of your data (with compression). It is creating a complete EMAN2 project folder, so for a large project will take a little time.
   * cd eman3
-  * e3make3d_point.py sets/fromstar__ctf_flip.lst --volout fromstar.hdf:12 --gaussout fromstar.txt --volfiltlp 3 --initpoints 500 -v 2
+  * e3make3d_point.py sets/fromstar%%__%%ctf_flip.lst --volout fromstar.hdf:12 --gaussout fromstar.txt --volfiltlp 3 --initpoints 500 -v 2
     * volfiltlp is the resolution in Å the final map will be (Gaussian) filtered to. If you decide the map is over/under filtered the final volume can easily be recreated from the other output file.
   * The output volume is fromstar.hdf, which can be opened with e2display.py or Chimera
   * If you wish to generate even/odd maps for a GSFSC calculation, you can run the program twice with the --class 0 (even) option on the first run and the --class 1 (odd) option on the second run (with modified output filenames).
   * Alternatively you could run an EMAN2 style iterative refinement with point-based reconstruction, eg:
-    * e2spa_refine.py --ptcl sets/fromstar__ctf_flip.lst --ref <starting model> --parallel thread:32:<fast scratch folder> --threads 32 --sym <symmetry> --res <start res> --niter 2 --tophat local --pointrecon 500 -v 1
+    * e2spa_refine.py --ptcl sets/fromstar%%__%%ctf_flip.lst --ref <starting model> --parallel thread:32:<fast scratch folder> --threads 32 --sym <symmetry> --res <start res> --niter 2 --tophat local --pointrecon 500 -v 1
     * You may need to look at a full EMAN2 tutorial to pick specific options for your case. The only change is the addition of the --pointrecon option.
@@ Line 41: / Line 42: @@
     * This involves making a copy of your data (with compression). It is creating a complete EMAN2 project folder, so for a large project will take a little time.
   * cd eman3
-  * e3make3d_point.py sets/fromcs__ctf_flip.lst --volout fromcs.hdf:12 --gaussout fromcs.txt --volfiltlp 3 --initpoints 500 -v 2
+  * e3make3d_point.py sets/fromcs%%__%%ctf_flip.lst --volout fromcs.hdf:12 --gaussout fromcs.txt --volfiltlp 3 --initpoints 500 -v 2
     * volfiltlp is the resolution in Å the final map will be (Gaussian) filtered to. If you decide the map is over/under filtered the final volume can easily be recreated from the other output file.
   * The output volume is fromcs.hdf, which can be opened with e2display.py or Chimera
   * You can also test a standard EMAN2 style iterative refinement with point-based reconstruction, eg:
-    * e2spa_refine.py --ptcl sets/fromcs__ctf_flip.lst --ref <starting model> --parallel thread:32:<fast scratch folder> --threads 32 --sym <symmetry> --res <start res> --niter 2 --tophat local --pointrecon 500 -v 1
+    * e2spa_refine.py --ptcl sets/fromcs%%__%%ctf_flip.lst --ref <starting model> --parallel thread:32:<fast scratch folder> --threads 32 --sym <symmetry> --res <start res> --niter 2 --tophat local --pointrecon 500 -v 1
     * You may need to look at a full EMAN2 tutorial to pick specific options for your case. The only change is the addition of the --pointrecon option.