removal of excess trial and error

Author: Jessie

.pre-commit-config.yaml

@@ -2,7 +2,7 @@
 # pre-commit install
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.5.0
+  rev: v6.0.0
   hooks:
     - id: end-of-file-fixer
     - id: mixed-line-ending
@@ -11,7 +11,7 @@ repos:
 
 - repo: https://github.com/astral-sh/ruff-pre-commit
   # Ruff version.
-  rev: v0.9.2
+  rev: v0.14.3
   hooks:
     # Run the linter.
     - id: ruff
@@ -20,7 +20,7 @@ repos:
     - id: ruff-format
 
 - repo: https://github.com/numpy/numpydoc
-  rev: v1.6.0
+  rev: v1.9.0
   hooks:
     - id: numpydoc-validation
       files: ^aiida_mlip/

examples/tutorials/workgraphs/md_workgraph.ipynb

@@ -58,16 +58,16 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0360e52f",
+   "id": "a89ba5dd",
    "metadata": {},
    "outputs": [],
    "source": [
     "from aiida.orm import StructureData\n",
     "from ase.build import bulk\n",
-    "from ase.io import read\n",
+    "from ase.io import read, iread\n",
     "\n",
     "# structure = StructureData(ase=read(\"Structures/qmof-ffeef76.cif\"))\n",
-    "structure = StructureData(ase=bulk(\"NaCl\", \"rocksalt\", 5.63))"
+    "init_structure = StructureData(ase=bulk(\"NaCl\", \"rocksalt\", 5.63))"
    ]
   },
   {
@@ -81,17 +81,6 @@
     "janus_code = load_code(\"janus@localhost\")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "65fbe939",
-   "metadata": {},
-   "source": [
-    "Inputs should include the model, code, metadata, and any other keyword arguments expected by the calculation we are running: \n",
-    "\n",
-    "to find out try using \"janus md --help\" which reveals that the arch, struct and ensemble is required, for which we shall use NVT. \n",
-    "The traj output is recorded every 100 steps, which is nested in md_kwargs Dict."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -107,23 +96,16 @@
     "    \"device\": Str(\"cpu\"),\n",
     "    \"metadata\": {\"options\": {\"resources\": {\"num_machines\": 1}}},\n",
     "    \"ensemble\": Str(\"NVT\"),\n",
-    "    \"struct\": structure,\n",
+    "    \"struct\": init_structure,\n",
     "    \"md_kwargs\": Dict(\n",
     "        {\n",
-    "            \"steps\": 400,\n",
+    "            \"steps\": 10,\n",
+    "            \"traj-every\": 2\n",
     "        }\n",
     "    )\n",
     "}"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "1d661593",
-   "metadata": {},
-   "source": [
-    "We now load the calculations we want to run:"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -139,10 +121,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "37df1f81",
+   "id": "0de6dd59",
    "metadata": {},
    "source": [
-    "Now we can create our WorkGraph. "
+    "# Single Descriptor"
    ]
   },
   {
@@ -161,30 +143,15 @@
     ")\n"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "18362513",
-   "metadata": {},
-   "source": [
-    "To know the inputs or outputs from the mdcalc, try using:"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "62f8322b",
    "metadata": {},
    "outputs": [],
    "source": [
-    "mdCalc.get_description()[\"spec\"][\"outputs\"].keys()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d4789f77",
-   "metadata": {},
-   "source": [
-    "Now run the descriptors calc"
+    "# To find inputs/outputs of mdcalc uncomment following: \n",
+    "# mdCalc.get_description()[\"spec\"][\"outputs\"].keys()"
    ]
   },
   {
@@ -197,18 +164,10 @@
     "descriptors_calc = wg.add_task(\n",
     "    descriptorsCalc,\n",
     "    name=\"descriptors_calc\",\n",
-    "    struct=md_calc.outputs.traj_output\n",
+    "    struct=md_calc.outputs.final_structure,\n",
     ")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "5dd1426a",
-   "metadata": {},
-   "source": [
-    "Pass to process_and_split_data "
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -225,14 +184,6 @@
     ")\n"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "2bba0462",
-   "metadata": {},
-   "source": [
-    "Visualise the workgraph"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -244,46 +195,87 @@
    ]
   },
   {
-   "cell_type": "markdown",
-   "id": "c8b7a99b",
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "85f26ee7",
    "metadata": {},
+   "outputs": [],
    "source": [
-    "We can visual the tasks of the Workgraph and run the tasks"
+    "wg.tasks"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "85f26ee7",
+   "id": "57e26db5",
    "metadata": {},
    "outputs": [],
    "source": [
-    "wg.tasks"
+    "# wg.run()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "abf1c398",
+   "metadata": {},
+   "source": [
+    "# Loop Descriptor"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "66c58962",
+   "id": "27bfe04a",
    "metadata": {},
    "outputs": [],
    "source": [
-    "wg.tasks[\"descriptors_calc\"].outputs"
+    "from aiida_workgraph import WorkGraph\n",
+    "\n",
+    "with WorkGraph(\"MD_Simple\") as wg:\n",
+    "    \n",
+    "    # MD simulation\n",
+    "    md_task = wg.add_task(\n",
+    "        mdCalc,\n",
+    "        name=\"md\",\n",
+    "        **inputs\n",
+    "    )\n",
+    " \n",
+    "    \n",
+    "    # Descriptors on final structure\n",
+    "    desc_task = wg.add_task(\n",
+    "        descriptorsCalc,\n",
+    "        name=\"descriptors\",\n",
+    "        code=inputs['code'],\n",
+    "        model=inputs['model'],\n",
+    "        arch=inputs['arch'],\n",
+    "        device=inputs['device'],\n",
+    "        metadata=inputs['metadata'],\n",
+    "        calc_per_element=Bool(True),\n",
+    "        struct=md_task.outputs.final_structure\n",
+    "    )\n",
+    "\n",
+    "wg.run()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "57e26db5",
+   "id": "c3069b29",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# wg.run()"
+    "wg"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "26736d8d",
+   "id": "4b8e7371",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4fe8d0a7",
    "metadata": {},
    "source": []
   }