debugged getting-started tutorial

nipype · Jan 23, 2025 · 076dc84 · 076dc84
1 parent 03c7438
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diff --git a/new-docs/source/tutorial/1-getting-started.ipynb b/new-docs/source/tutorial/1-getting-started.ipynb
@@ -54,13 +54,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from fileformats.medimage import Nifti\n",
+    "from fileformats.medimage import Nifti1\n",
     "\n",
     "nifti_dir = test_dir / \"nifti\"\n",
     "nifti_dir.mkdir()\n",
     "\n",
     "for i in range(10):\n",
-    "    Nifti.sample(nifti_dir, seed=i)  # Create a dummy NIfTI file in the dest. directory"
+    "    Nifti1.sample(nifti_dir, seed=i)  # Create a dummy NIfTI file in the dest. directory"
    ]
   },
   {
@@ -116,7 +116,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "A newer version (0.25) of nipype/pydra is available. You are using 0.25.dev128+g1e817743.d20250104\n"
+      "A newer version (0.25) of nipype/pydra is available. You are using 0.25.dev141+g03c7438b.d20250123\n"
      ]
     }
    ],
@@ -150,7 +150,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Result(output=LoadJsonOutputs(out={'a': True, 'b': 'two', 'c': 3, 'd': [7, 0.55, 6]}), runtime=None, errored=False)\n"
+      "Result(task=<pydra.engine.core.Task object at 0x10dc42fc0>, outputs=LoadJsonOutputs(out={'a': True, 'b': 'two', 'c': 3, 'd': [7, 0.55, 6]}), runtime=None, errored=False)\n"
      ]
     }
    ],
@@ -201,16 +201,19 @@
    "metadata": {},
    "outputs": [
     {
-     "ename": "TypeError",
-     "evalue": "Task.__init__() missing 1 required positional argument: 'definition'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[6], line 8\u001b[0m\n\u001b[1;32m      5\u001b[0m mrgrid \u001b[38;5;241m=\u001b[39m MrGrid(voxel\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m0.5\u001b[39m,\u001b[38;5;241m0.5\u001b[39m,\u001b[38;5;241m0.5\u001b[39m))\u001b[38;5;241m.\u001b[39msplit(\u001b[38;5;28minput\u001b[39m\u001b[38;5;241m=\u001b[39mnifti_dir\u001b[38;5;241m.\u001b[39miterdir())\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# Run the task to resample all NIfTI files\u001b[39;00m\n\u001b[0;32m----> 8\u001b[0m outputs \u001b[38;5;241m=\u001b[39m \u001b[43mmrgrid\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;66;03m# Print the locations of the output files\u001b[39;00m\n\u001b[1;32m     11\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mstr\u001b[39m(p) \u001b[38;5;28;01mfor\u001b[39;00m p \u001b[38;5;129;01min\u001b[39;00m outputs\u001b[38;5;241m.\u001b[39moutput))\n",
-      "File \u001b[0;32m~/git/workflows/pydra/pydra/engine/specs.py:299\u001b[0m, in \u001b[0;36mTaskDef.__call__\u001b[0;34m(self, name, audit_flags, cache_dir, cache_locations, messengers, messenger_args, rerun)\u001b[0m\n\u001b[1;32m    296\u001b[0m     task_type \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mTask\n\u001b[1;32m    297\u001b[0m     definition \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\n\u001b[0;32m--> 299\u001b[0m task \u001b[38;5;241m=\u001b[39m \u001b[43mtask_type\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    300\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdefinition\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    301\u001b[0m \u001b[43m    \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    302\u001b[0m \u001b[43m    \u001b[49m\u001b[43maudit_flags\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maudit_flags\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    303\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    304\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcache_locations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_locations\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    305\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmessenger_args\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmessenger_args\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    306\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmessengers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmessengers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    307\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrerun\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrerun\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    308\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    309\u001b[0m result \u001b[38;5;241m=\u001b[39m task()\n\u001b[1;32m    310\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m result\u001b[38;5;241m.\u001b[39merrored:\n",
-      "File \u001b[0;32m~/git/workflows/pydra/pydra/engine/core.py:708\u001b[0m, in \u001b[0;36mWorkflowTask.__init__\u001b[0;34m(self, definition, name, audit_flags, cache_dir, cache_locations, input_spec, cont_dim, messenger_args, messengers, output_spec, rerun, propagate_rerun, **kwargs)\u001b[0m\n\u001b[1;32m    662\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\n\u001b[1;32m    663\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    664\u001b[0m     definition,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    678\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m    679\u001b[0m ):\n\u001b[1;32m    680\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    681\u001b[0m \u001b[38;5;124;03m    Initialize a workflow.\u001b[39;00m\n\u001b[1;32m    682\u001b[0m \n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    705\u001b[0m \n\u001b[1;32m    706\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 708\u001b[0m     \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[1;32m    709\u001b[0m \u001b[43m        \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    710\u001b[0m \u001b[43m        \u001b[49m\u001b[43minputs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    711\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcont_dim\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcont_dim\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    712\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcache_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    713\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcache_locations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcache_locations\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    714\u001b[0m \u001b[43m        \u001b[49m\u001b[43maudit_flags\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maudit_flags\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    715\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmessengers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmessengers\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    716\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmessenger_args\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmessenger_args\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    717\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrerun\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrerun\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    718\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    720\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgraph \u001b[38;5;241m=\u001b[39m DiGraph(name\u001b[38;5;241m=\u001b[39mname)\n\u001b[1;32m    721\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname2obj \u001b[38;5;241m=\u001b[39m {}\n",
-      "\u001b[0;31mTypeError\u001b[0m: Task.__init__() missing 1 required positional argument: 'definition'"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n"
      ]
     }
    ],
@@ -219,13 +222,13 @@
     "\n",
     "# Instantiate the task definition, \"splitting\" over all NIfTI files in the test directory\n",
     "# by splitting the \"input\" input field over all files in the directory\n",
-    "mrgrid = MrGrid(voxel=(0.5,0.5,0.5)).split(input=nifti_dir.iterdir())\n",
+    "mrgrid = MrGrid(operation=\"regrid\", voxel=(0.5,0.5,0.5)).split(in_file=nifti_dir.iterdir())\n",
     "\n",
     "# Run the task to resample all NIfTI files\n",
     "outputs = mrgrid()\n",
     "\n",
     "# Print the locations of the output files\n",
-    "print(\"\\n\".join(str(p) for p in outputs.output))"
+    "print(\"\\n\".join(str(p) for p in outputs.out_file))"
    ]
   },
   {
@@ -245,15 +248,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n",
+      "/Users/tclose/Library/Caches/pydra/0.24.dev36+g0deadc43/run-cache/Task_c989fc46725c0d124dc287f463674e63/out_file.mif\n"
+     ]
+    }
+   ],
    "source": [
     "\n",
     "\n",
-    "mrgrid_varying_vox_sizes = MrGrid().split(\n",
-    "    (\"input\", \"voxel\"),\n",
-    "    input=nifti_dir.iterdir(),\n",
+    "mrgrid_varying_vox_sizes = MrGrid(operation=\"regrid\").split(\n",
+    "    (\"in_file\", \"voxel\"),\n",
+    "    in_file=nifti_dir.iterdir(),\n",
     "    # Define a list of voxel sizes to resample the NIfTI files to,\n",
     "    # the list must be the same length as the list of NIfTI files\n",
     "    voxel=[\n",
@@ -270,7 +290,7 @@
     "    ],\n",
     ")\n",
     "\n",
-    "print(mrgrid_varying_vox_sizes().output)"
+    "print(\"\\n\".join(str(p) for p in outputs.out_file))"
    ]
   },
   {

diff --git a/new-docs/source/tutorial/tst.py b/new-docs/source/tutorial/tst.py
@@ -1,15 +1,12 @@
 from pathlib import Path
 from tempfile import mkdtemp
-import shutil
 from fileformats.medimage import Nifti1
 from pydra.tasks.mrtrix3.v3_0 import MrGrid
-from pydra.utils import user_cache_dir
 
 
 if __name__ == "__main__":
-    test_dir = Path(mkdtemp())
 
-    shutil.rmtree(user_cache_dir / "run-cache", ignore_errors=True)
+    test_dir = Path(mkdtemp())
 
     nifti_dir = test_dir / "nifti"
     nifti_dir.mkdir()
@@ -19,14 +16,23 @@
             nifti_dir, seed=i
         )  # Create a dummy NIfTI file in the dest. directory
 
-    # Instantiate the task definition, "splitting" over all NIfTI files in the test directory
-    # by splitting the "input" input field over all files in the directory
-    mrgrid = MrGrid(operation="regrid", voxel=(0.5, 0.5, 0.5)).split(
-        in_file=nifti_dir.iterdir()
+    mrgrid_varying_vox_sizes = MrGrid(operation="regrid").split(
+        ("in_file", "voxel"),
+        in_file=nifti_dir.iterdir(),
+        # Define a list of voxel sizes to resample the NIfTI files to,
+        # the list must be the same length as the list of NIfTI files
+        voxel=[
+            (1.0, 1.0, 1.0),
+            (1.0, 1.0, 1.0),
+            (1.0, 1.0, 1.0),
+            (0.5, 0.5, 0.5),
+            (0.75, 0.75, 0.75),
+            (0.5, 0.5, 0.5),
+            (0.5, 0.5, 0.5),
+            (1.0, 1.0, 1.0),
+            (1.25, 1.25, 1.25),
+            (1.25, 1.25, 1.25),
+        ],
     )
 
-    # Run the task to resample all NIfTI files
-    outputs = mrgrid(worker="cf")
-
-    # Print the locations of the output files
-    print("\n".join(str(p) for p in outputs.out_file))
+print(mrgrid_varying_vox_sizes().out_file)
diff --git a/pydra/engine/core.py b/pydra/engine/core.py
@@ -128,7 +128,7 @@ def __init__(
         self.definition = copy(definition)
         # We save the submitter is the definition is a workflow otherwise we don't
         # so the task can be pickled
-        self.submitter = submitter if is_workflow(definition) else None
+        self.submitter = submitter
         self.environment = environment if environment is not None else Native()
         self.name = name
         self.state_index = state_index

diff --git a/pydra/engine/specs.py b/pydra/engine/specs.py
@@ -237,7 +237,7 @@ def split(
                 "set 'overwrite=True' to do so"
             )
         if splitter:
-            unwraped_split = hlpst.unwrap_splitter(splitter)
+            unwraped_split = list(hlpst.unwrap_splitter(splitter))
             if duplicated := [f for f, c in Counter(unwraped_split).items() if c > 1]:
                 raise ValueError(f"Splitter fields {duplicated} are duplicated")
             split_names = set(
@@ -584,17 +584,17 @@ def _run(self, task: "Task[PythonDef]") -> None:
         # Run the actual function
         returned = self.function(**inputs)
         # Collect the outputs and save them into the task.return_values dictionary
-        self.return_values = {f.name: f.default for f in attrs.fields(self.Outputs)}
-        return_names = list(self.return_values)
+        task.return_values = {f.name: f.default for f in attrs.fields(self.Outputs)}
+        return_names = list(task.return_values)
         if returned is None:
-            self.return_values = {nm: None for nm in return_names}
-        elif len(self.return_values) == 1:
+            task.return_values = {nm: None for nm in return_names}
+        elif len(task.return_values) == 1:
             # if only one element in the fields, everything should be returned together
-            self.return_values = {list(self.return_values)[0]: returned}
+            task.return_values = {list(task.return_values)[0]: returned}
         elif isinstance(returned, tuple) and len(return_names) == len(returned):
-            self.return_values = dict(zip(return_names, returned))
+            task.return_values = dict(zip(return_names, returned))
         elif isinstance(returned, dict):
-            self.return_values = {key: returned.get(key, None) for key in return_names}
+            task.return_values = {key: returned.get(key, None) for key in return_names}
         else:
             raise RuntimeError(
                 f"expected {len(return_names)} elements, but {returned} were returned"