Merge branch 'master'

Author: abartesaghi

config/pyp_config.toml

@@ -4,6 +4,35 @@ Changelog
 
 **Legend**: :fa:`star,text-success` New feature, :fa:`plus-square,text-primary` Improvement, :fa:`bug,text-danger` Bug fix
 
+v0.6.4 (3/24/2024)
+******************
+
+   :fa:`plus-square,text-primary` Implement mechanism to isolate logs from failed jobs in the Logs tab.
+
+   :fa:`plus-square,text-primary` Add support for project names with special characters.
+
+   :fa:`plus-square,text-primary` Remove many commonly used parameters from the advanced category.
+
+   :fa:`plus-square,text-primary` Add progress bars during export of metadata to .star format.
+
+   :fa:`plus-square,text-primary` Allow export of particle coordinates from streaming sessions.
+
+   :fa:`plus-square,text-primary` Check that .order files have the same number of entries as images in the tilt-series.
+
+   :fa:`bug,text-danger` Fix bugs when reading metadata from *.mdoc files.
+
+   :fa:`bug,text-danger` Prevent dragging of multiple connections from block outputs in project view.
+
+   :fa:`bug,text-danger` Fix bug when managing GPU resources in standalone mode.
+
+   :fa:`bug,text-danger` Fix bug when using grouping of frames during movie processing.
+
+   :fa:`bug,text-danger` Fix bug in single-particle pipeline during hot pixel removal.
+
+   :fa:`bug,text-danger` Fix bug in Table view that caused content to overlap when resizing columns.
+
+   :fa:`bug,text-danger` Always export metadata in .star format to current project directory (user specified location is no longer supported).
+
 v0.6.3 (3/01/2024)
 ******************
 

docs/changelog.rst

@@ -675,3 +675,14 @@ Minimal example:
 
 :Examples:
 	``workflowDirs = ['/storage/workflows']``
+
+|
+
+``minPasswordLength``
+~~~~~~~~~~~~~~~~~~~~~
+
+:Type: integer
+:Required: no
+:Default: 12
+:Description:
+	The minimum length accepted for new passwords.

docs/reference/config.rst

@@ -93,8 +93,6 @@ This tutorial shows how to import and export single-particle and tomography proj
 
   - Set the location of the ``Input parfile`` you want to export by clicking on the icon :fa:`search,text-primary` and browsing to the corresponding directory
 
-  - Set the location of the ``Output folder`` by clicking on the icon :fa:`search,text-primary` and browsing to the directory where you want the data to be saved
-
 * Click :badge:`Save,badge-primary`
 
 * Click :badge:`Run,badge-primary` followed by :badge:`Start Run for 1 block,badge-primary` to launch the export process

docs/tutorials/import_export.rst

@@ -229,8 +229,6 @@ Step 4: Reference-based refinement
 
       - Set ``Last iteration`` to 5
 
-      - Check ``Show advanced options``
-
       - Check ``Use alignment priors``
 
       - Click on the **Reconstruction** tab

docs/tutorials/spa_empiar_10025.rst

@@ -140,8 +140,6 @@ Step 3: Pre-processing
 
         - Set ``Binning factor for reconstruction`` to 8
 
-        - Click ``Show advanced options``
-
         - Set ``Thickness of reconstruction (unbinned voxels)`` to 2048
 
         - Click on the **Virion/spike detection** tab
@@ -319,8 +317,6 @@ Step 6: Reference-based refinement
 
         - Set ``Last exposure for refinement`` to 10
 
-        - Check ``Show advanced options``
-
         - Set ``Optimizer - Exhaustive search points`` to 50000
 
         - Check ``Refine particle alignments``
@@ -377,8 +373,6 @@ Step 7. Fully constrained refinement
 
         - Check ``Refine tilt-geometry``
 
-        - Check ``Show advanced options``
-
         - Set ``Optimizer - Max step length`` to 100
 
         - Set ``Optimizer - Exhaustive search points`` to 0
@@ -678,8 +672,6 @@ Step 15: Refinement after movie frame refinement
 
       .. tabbed:: Constrained refinement
 
-        - Check ``Show advanced options``
-
         - Set ``Min number of projections for refinement`` to 2
 
         - Check ``Refine tilt-geometry``

docs/tutorials/tomo_empiar_10164.rst

@@ -122,8 +122,6 @@ Step 3: Pre-processing
 
         - Set ``Thickness of reconstruction (unbinned voxels)`` to 3072
 
-        - Click ``Show advanced options``
-
         - Uncheck ``Resize squares to closest multiple of 512``
 
         - Click on the **Resources** tab
@@ -221,8 +219,6 @@ Step 5: Reference-based refinement
 
         - Set ``Last exposure for refinement`` to 25
 
-        - Click ``Show advanced options``
-
         - Set ``Optimizer - Exhaustive search points`` to 5000000
 
         - Check ``Refine particle alignments``
@@ -356,8 +352,6 @@ Step 8. Fully constrained refinement
 
         - Set ``Last exposure for refinement`` to 25
 
-        - Check ``Show advanced options``
-
         - Set ``Optimizer - Exhaustive search points`` to 0
 
         - Set ``Optimizer - Max step length`` to 100
@@ -517,8 +511,6 @@ Step 12: Region-based refinement after CTF refinement
 
         - Set ``Number of regions`` to 16,16,4
 
-        - Check ``Show advanced options``
-
         - Set ``Optimizer - Max step length`` to 20.0
 
         - Check ``Refine tilt-geometry``

docs/tutorials/tomo_empiar_10304.rst

@@ -3,4 +3,4 @@
 # It is shown directly to the user in micromon's user interface.
 # To the extent that is feasible, it should follow Semantic Versioning conventions:
 # https://semver.org/
-version = "0.6.3"
+version = "0.6.4"

nextpyp.toml

@@ -326,7 +326,7 @@
                     scaling = model_pixel_size / actual_pixel
                     logger.warning(f"Rescaling initial model {initial_model} to {scaling} A per pixel")
                     new_size = int(mparameters["extract_box"])
-                    command = f"{get_imod_path()}/bin/matchvol -size {new_size},{new_size},{new_size} -3dxform {scaling},0,0,0,0,{scaling},0,0,0,0,{scaling},0 {initial_model} {frealign_initial_model}; rm {frealign_initial_model}~"
+                    command = f"{get_imod_path()}/bin/matchvol -size {new_size},{new_size},{new_size} -3dxform {scaling},0,0,0,0,{scaling},0,0,0,0,{scaling},0 '{initial_model}' {frealign_initial_model}; rm {frealign_initial_model}~"
                     local_run.run_shell_command(command=command,verbose=mparameters["slurm_verbose"])
 
                 else:

src/frealign.py

@@ -3558,7 +3558,7 @@ def align_stack_super(
                         )
 
                         # launch FREALIGN refinement (skip reconstruction, score evaluation only)
-                        command = "cd {0}; export MYCORES={1}; echo {2} > `pwd`/mynode; export MYNODES=`pwd`/mynode; {3}/bin/fyp -dataset {4} -iter 2 -maxiter {5} -metric {6} -mode 1 -mask 0,0,0,0,0 -cutoff -1 -rlref {7} -rhref {8} -rrec {9} -fmatch F".format(
+                        command = "cd '{0}'; export MYCORES={1}; echo {2} > `pwd`/mynode; export MYNODES=`pwd`/mynode; {3}/bin/fyp -dataset {4} -iter 2 -maxiter {5} -metric {6} -mode 1 -mask 0,0,0,0,0 -cutoff -1 -rlref {7} -rhref {8} -rrec {9} -fmatch F".format(
                             frealign_path,
                             cores_for_frealign,
                             socket.gethostname(),
@@ -3812,7 +3812,7 @@ def align_stack_super(
 
                     # parse parameter file
 
-                    command = "cd {0}; export MYCORES={1}; echo {2} > `pwd`/mynode; export MYNODES=`pwd`/mynode; {3}/bin/fyp -dataset {4} -iter 2 -maxiter {5} -metric {6} -mode 1 -mask 0,0,0,1,1 -cutoff -1 -rlref {7} -rhref {8} -rrec {9} -fmatch T".format(
+                    command = "cd '{0}'; export MYCORES={1}; echo {2} > `pwd`/mynode; export MYNODES=`pwd`/mynode; {3}/bin/fyp -dataset {4} -iter 2 -maxiter {5} -metric {6} -mode 1 -mask 0,0,0,1,1 -cutoff -1 -rlref {7} -rhref {8} -rrec {9} -fmatch T".format(
                         frealign_path,
                         cores_for_frealign,
                         socket.gethostname(),
@@ -4675,7 +4675,7 @@ def align_movie_super(parameters, name, suffix, isfirst = False):
         bfactor = float(parameters["movie_bfactor"])
         first_frame = int(parameters["movie_first"]) + 1 # pyp from 0, unblur starts from 1
         last_frame = int(parameters["movie_last"]) + 1 if int(parameters["movie_last"]) != -1 else 0 # pyp's end is -1, unblur's end is 0
-        running_average = 1
+        running_average = parameters["movie_group"]
         maximum_shifts_in_A = 40.0
         minimum_shifts_in_A = 0.0
         threads = min(6,parameters["slurm_tasks"]) if "spr" in parameters["data_mode"].lower() else 1