Update versaFlow from development repository

.config/b0_to_template_affine_config.py

@@ -52,7 +52,7 @@
                 1.,
                 64,
                 "Regular",
-                1.,
+                0.7,
                 True
             ],
             "klass": "mrHARDI.traits.ants.MetricMI"
@@ -84,7 +84,7 @@
                 1.,
                 64,
                 "Regular",
-                1.,
+                0.8,
                 True
             ],
             "klass": "mrHARDI.traits.ants.MetricMI"

.config/b0_to_template_syn_config.py

@@ -36,8 +36,8 @@
 
 c.AntsConfiguration.passes = [{
     "conv_eps": 1e-5,
-    "conv_max_iter": [1000, 500, 300, 200, 100],
-    "conv_win": 30,
+    "conv_max_iter": [100, 50, 20, 10, 10],
+    "conv_win": 10,
     "grad_step": 0.2,
     "var_penality": 3,
     "var_total": 0,
@@ -80,6 +80,48 @@
         0.5,
         0
     ]
+}, {
+    "conv_eps": 1e-5,
+    "conv_max_iter": [50, 20, 20],
+    "conv_win": 20,
+    "grad_step": 0.1,
+    "var_penality": 3,
+    "var_total": 0,
+    "klass": "mrHARDI.traits.ants.AntsSyN",
+    "metrics": [
+        {
+            "target_index": 0,
+            "moving_index": 1,
+            "args": [
+                0.65,
+                64,
+                "Regular",
+                1.
+            ],
+            "klass": "mrHARDI.traits.ants.MetricMI"
+        },
+        {
+            "target_index": 0,
+            "moving_index": 2,
+            "args": [
+                0.35,
+                2,
+                "Regular",
+                1.
+            ],
+            "klass": "mrHARDI.traits.ants.MetricCC"
+        }
+    ],
+    "shrinks": [
+        8,
+        4,
+        1
+    ],
+    "smoothing": [
+        1.5,
+        1.,
+        0
+    ]
 }]
 
 c.AntsConfiguration.use_float = False

.config/dwi_n4_normalization_config.py

@@ -27,9 +27,11 @@
 
 c.N4BiasCorrectionConfiguration.filter_width = 0.075
 
-c.N4BiasCorrectionConfiguration.knot_distance = 4.0
+c.N4BiasCorrectionConfiguration.spline_order = 3
 
-c.N4BiasCorrectionConfiguration.iterations = [500, 200, 150, 100]
+c.N4BiasCorrectionConfiguration.knot_distance = 64.0
+
+c.N4BiasCorrectionConfiguration.iterations = [100, 100, 50, 30]
 
 c.N4BiasCorrectionConfiguration.noise = 0.01
 

.config/prepare_topup_base_config.py

@@ -105,7 +105,7 @@
 
 c.TopupConfiguration.reg_model = "bending_energy"
 
-c.TopupConfiguration.scale_intensities = True
+c.TopupConfiguration.scale_intensities = False
 
 c.TopupConfiguration.spl_order = "cubic"
 

.config/t1_n4_normalization_config.py

@@ -27,9 +27,11 @@
 
 c.N4BiasCorrectionConfiguration.filter_width = 0.075
 
-c.N4BiasCorrectionConfiguration.knot_distance = 4.0
+c.N4BiasCorrectionConfiguration.spline_order = 3
 
-c.N4BiasCorrectionConfiguration.iterations = [200, 200, 100, 100]
+c.N4BiasCorrectionConfiguration.knot_distance = 16.0
+
+c.N4BiasCorrectionConfiguration.iterations = [80, 80, 40, 30]
 
 c.N4BiasCorrectionConfiguration.noise = 0.01
 

.config/t1_to_b0_syn_config.py

@@ -36,7 +36,7 @@
 
 c.AntsConfiguration.passes = [{
     "conv_eps": 1e-6,
-    "conv_max_iter": [50, 50],
+    "conv_max_iter": [30, 30],
     "conv_win": 10,
     "grad_step": 0.1,
     "var_penality": 3,
@@ -48,18 +48,18 @@
             "moving_index": 0,
             "args": [
                 0.65,
-                64,
+                2,
                 "Regular",
                 1.
             ],
-            "klass": "mrHARDI.traits.ants.MetricMI"
+            "klass": "mrHARDI.traits.ants.MetricCC"
         },
         {
             "target_index": 1,
             "moving_index": 0,
             "args": [
                 0.35,
-                4,
+                2,
                 "Regular",
                 1.
             ],

.config/t1_to_template_affine_config.py

@@ -46,7 +46,7 @@
 
 c.AntsConfiguration.passes = [{
     "conv_eps": 1e-6,
-    "conv_max_iter": [400, 200, 100, 50],
+    "conv_max_iter": [400, 100, 50, 20],
     "conv_win": 10,
     "grad_step": 0.1,
     "klass": "mrHARDI.traits.ants.AntsRigid",
@@ -78,7 +78,7 @@
     ]
 }, {
     "conv_eps": 1e-6,
-    "conv_max_iter": [500, 300, 150, 75],
+    "conv_max_iter": [200, 100, 50, 20],
     "conv_win": 20,
     "grad_step": 0.1,
     "klass": "mrHARDI.traits.ants.AntsAffine",

.config/t1_to_template_syn_config.py

@@ -35,9 +35,9 @@
 c.AntsConfiguration.match_histogram = True
 
 c.AntsConfiguration.passes = [{
-    "conv_eps": 1e-10,
-    "conv_max_iter": [400, 400, 200, 200],
-    "conv_win": 20,
+    "conv_eps": 1e-7,
+    "conv_max_iter": [50, 50, 20, 20],
+    "conv_win": 10,
     "grad_step": 0.2,
     "var_penality": 3,
     "var_total": 0,
@@ -48,7 +48,7 @@
             "moving_index": 0,
             "args": [
                 1.0,
-                192,
+                64,
                 "Regular",
                 1.0
             ],
@@ -67,6 +67,35 @@
         1.,
         0.
     ]
+}, {
+    "conv_eps": 1e-7,
+    "conv_max_iter": [20, 10],
+    "conv_win": 10,
+    "grad_step": 0.1,
+    "var_penality": 3,
+    "var_total": 0,
+    "klass": "mrHARDI.traits.ants.AntsSyN",
+    "metrics": [
+        {
+            "target_index": 0,
+            "moving_index": 0,
+            "args": [
+                1.0,
+                4,
+                "Regular",
+                1.0
+            ],
+            "klass": "mrHARDI.traits.ants.MetricCC"
+        }
+    ],
+    "shrinks": [
+        4,
+        1
+    ],
+    "smoothing": [
+        2.,
+        0.
+    ]
 }]
 
 c.AntsConfiguration.use_float = False

README.md

@@ -2,9 +2,10 @@
 [![Docker containers](https://img.shields.io/badge/Docker%20images-dockerhub-blue?style=plaflat&logo=docker&labelColor=2e343b)](https://hub.docker.com/repository/docker/avcaron/versa)
 [![DOI](https://zenodo.org/badge/430873937.svg)](https://zenodo.org/badge/latestdoi/430873937)
 
-# versaFlow
 
-versaFlow is a diffusion MRI processing pipeline configured to handle high 
+# versaflow
+
+versaflow is a diffusion MRI processing pipeline configured to handle high 
 angular and spatial resolution data. By default it is configured to process 
 Maccaca Mulatta brain images; profiles to handle other types of primates, as 
 well as the human brain are being developped. The pipeline's pre-processing 
@@ -141,7 +142,14 @@ automatically handled in a future version of the pipeline.
 To run the pipeline, we recommend creating a directory per run that contains log and 
 cache of execution from Nextflow. In that directory, then run the following command
 
-`nextflow run -resume -w cache -dsl2 <root of versaFlow>/main.nf --data_root <data root>
+```
+nextflow run \
+    -resume \
+    -w cache \
+    -dsl2 \
+    <root of versaFlow>/main.nf \
+    --data_root <data root>
+```
 
 Additional parameters to this command can be supplied, such as :
 

USAGE

@@ -73,8 +73,12 @@ OPTIONAL ARGUMENTS [possible values] (default values)
 
 - I/O :
     --output_root                           Output directory where to put processed datasets ($output_root)
-    --publish_all                           Publish all files generated by each process in a directory named "all" under the output root [true|false] ($publish_all)
-    --publish_mode                          Strategy used to copy the processed files in the output root [copy|link] ($publish_mode)
+    --publish_all                           Publish all files generated by each process in a directory named 
+                                            "all" under the output root [true|false] ($publish_all)
+    --publish_mode                          Strategy used to copy the processed files in the output root
+                                            [symlink|rellink|link|copy|copyNoFollow|move] ($publish_mode)
+    --publish_all_mode                      Strategy used to copy to whole processing tree in the output root
+                                            [symlink|rellink|link|copy|copyNoFollow|move] ($publish_all_mode)
     --verbose_outputs                       Output of additional files and of debug messages in logs [true|false] ($verbose_outputs)
     --random_seed                           Random seed to input to all random number generators ($random_seed)
     --check_memory_requirements             Check if enough memory is available to run the pipeline [true|false] ($check_memory_requirements)

main.nf

@@ -79,6 +79,7 @@ def display_run_info () {
     log.info " - Output root     : $params.output_root"
     log.info " - Publish mode    : $params.publish_mode"
     log.info " - Publish all outputs ${params.publish_all ? "(enabled)" : "(disabled)"}"
+    log.info " - Publish all mode : $params.publish_all_mode"
     log.info " - Verbose ${params.verbose_outputs ? "(enabled)" : "(disabled)"}"
     log.info " - Random seed     : $params.random_seed"
     log.info " - Check memory    : $params.check_memory_requirements"
@@ -221,6 +222,7 @@ def display_usage () {
             "output_root" : "$params.output_root",
             "publish_all" : "$params.publish_all",
             "publish_mode" : "$params.publish_mode",
+            "publish_all_mode" : "$params.publish_all_mode",
             "verbose_outputs" : "$params.verbose_outputs",
             "resample_data" : "$params.resample_data",
             "check_memory_requirements": "$params.check_memory_requirements",

modules/functions.nf

@@ -201,4 +201,4 @@ def collect_paths ( data_channel ) {
     return data_channel.map{
         [it[0], (it.size() > 2 ? it[1..-1] : [it[1]] ).findAll{ it }]
     }
-}
+}

modules/processes/brain_extraction.nf

@@ -9,8 +9,8 @@ process deepbet_t1 {
     label params.use_cuda ? "res_single_cpu" : params.on_hcp ? "res_full_node_override" : "res_max_cpu"
     label params.use_cuda ? "res_gpu" : ""
 
-    publishDir "${params.output_root}/all/${sid}/$caller_name/${task.process.replaceAll(":", "/")}", mode: "link", enabled: params.publish_all
-    publishDir "${params.output_root}/${sid}", saveAs: { f -> f.contains("metadata") ? null : remove_alg_suffixes(f) }, mode: params.publish_mode
+    publishDir "${params.output_root}/all/${sid}/$caller_name/${task.process.replaceAll(":", "/")}", mode: "$params.publish_all_mode", enabled: params.publish_all, overwrite: true
+    publishDir "${params.output_root}/${sid}", saveAs: { f -> f.contains("metadata") ? null : remove_alg_suffixes(f) }, mode: params.publish_mode, overwrite: true
 
     input:
         tuple val(sid), path(t1_image)
@@ -28,8 +28,8 @@ process bet_mask {
     label "BET"
     label "res_single_cpu"
 
-    publishDir "${params.output_root}/all/${sid}/$caller_name/${task.process.replaceAll(":", "/")}", mode: "link", enabled: params.publish_all
-    publishDir "${params.output_root}/${sid}", saveAs: { f -> f.contains("metadata") ? null : add_suffix(remove_alg_suffixes(f), suffix ? "$suffix" : "_bet_mask") }, mode: params.publish_mode
+    publishDir "${params.output_root}/all/${sid}/$caller_name/${task.process.replaceAll(":", "/")}", mode: "$params.publish_all_mode", enabled: params.publish_all, overwrite: true
+    publishDir "${params.output_root}/${sid}", saveAs: { f -> f.contains("metadata") ? null : add_suffix(remove_alg_suffixes(f), suffix ? "$suffix" : "_bet_mask") }, mode: params.publish_mode, overwrite: true
 
     input:
         tuple val(sid), path(img)