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Merged
gvarnavi merged 6 commits into from
Jun 25, 2026
Merged

Syncing upstream repo with msa-em repo changes #1

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c3767e3
Update GitHub link in myst.yml
gvarnavi Jun 25, 2026
6e58252
minor edit to trigger actions
gvarnavi Jun 25, 2026
21219c2
switch to pathlib.Path
gvarnavi Jun 25, 2026
b7114d5
sorted files fix
gvarnavi Jun 25, 2026
6906cdd
Rename 01_Introduction.md to 01_introduction.md
gvarnavi Jun 25, 2026
f92b52f
nmf component cross-ref
gvarnavi Jun 25, 2026
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2 changes: 1 addition & 1 deletion 01_Introduction.md → 01_introduction.md
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Expand Up @@ -45,4 +45,4 @@ The approach also implements an efficient pre-processing strategy that highly be
This study demonstrates and benchmarks the PM methodology on the SPED dataset from the model Al-Cu-Li alloy that has previously been released open-source together with a corresponding ground truth phase map [@Thronsen2024].
The workflow is further validated by applying it to the more challenging precipitate structures in an Al-Mg-Si-Cu alloy that contains both partly disordered and structurally similar precipitates [@Sunde2020; @sorhaug2026].
Overall, this study aims to establish a user-friendly and robust framework for SPED phase mapping that handles both known and unknown crystal structures.
The workflow is released open-source, and it can be further modified and readily applied to other material systems, for instance it has already been applied to Al-Zn-Mg-Cu alloys [@Ryggetangen2025] and Al-Mg-Si-Cu alloys in a related publication [@sorhaug2026].
The workflow is released open-source, and it can be further modified and readily applied to other material systems, for instance it has already been applied to Al-Zn-Mg-Cu alloys [@Ryggetangen2025] and Al-Mg-Si-Cu alloys in a related publication [@sorhaug2026].
4 changes: 2 additions & 2 deletions myst.yml
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Expand Up @@ -15,7 +15,7 @@ project:
- Al-Cu-Li
- Al-Mg-Si-Cu
- precipitates
github: https://github.com/tinabe/pattern-matching-paper
github: https://github.com/msa-em/pattern-matching-paper
jupyter: true
# jupyter:
# server:
Expand All @@ -25,7 +25,7 @@ project:
license: CC-BY-4.0
#banner: banner.png
#thumbnail: thumbnail.webp
date: 2026-06-24
date: 2026-06-26
requirements:
- 'Dockerfile'
- requirements.txt
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33 changes: 14 additions & 19 deletions notebooks/advanced_phase_map.ipynb
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Expand Up @@ -21,7 +21,8 @@
"import hyperspy.api as hs\n",
"from matplotlib.colors import to_rgba, LinearSegmentedColormap, ListedColormap\n",
"from IPython.display import display\n",
"from ipywidgets import Dropdown, interactive, Layout"
"from ipywidgets import Dropdown, interactive, Layout\n",
"from pathlib import Path"
]
},
{
Expand All @@ -45,16 +46,18 @@
"folder_data = './data/'\n",
"\n",
"phase_maps = [\n",
" hs.load(folder_data+'phase_map_nmf.hspy'), \n",
" hs.load(folder_data+'phase_map_nmf_overlap.hspy'), \n",
" hs.load(folder_data+'phase_map_nmf_overlap_nmf.hspy'), \n",
" hs.load(folder_data+'phase_map_nmf_overlap_clustering.hspy')]\n",
" hs.load(Path(folder_data+'phase_map_nmf.hspy')), \n",
" hs.load(Path(folder_data+'phase_map_nmf_overlap.hspy')), \n",
" hs.load(Path(folder_data+'phase_map_nmf_overlap_nmf.hspy')), \n",
" hs.load(Path(folder_data+'phase_map_nmf_overlap_clustering.hspy'))\n",
"]\n",
"\n",
"max_nccs = [\n",
" hs.load(folder_data+'nccmax_nmf.hspy'), \n",
" hs.load(folder_data+'nccmax_nmf_overlap.hspy'), \n",
" hs.load(folder_data+'nccmax_nmf_overlap_nmf.hspy'), \n",
" hs.load(folder_data+'nccmax_nmf_overlap_clustering.hspy')]"
" hs.load(Path(folder_data+'nccmax_nmf.hspy')), \n",
" hs.load(Path(folder_data+'nccmax_nmf_overlap.hspy')), \n",
" hs.load(Path(folder_data+'nccmax_nmf_overlap_nmf.hspy')), \n",
" hs.load(Path(folder_data+'nccmax_nmf_overlap_clustering.hspy'))\n",
" ]"
]
},
{
Expand Down Expand Up @@ -162,7 +165,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "58d4c2d38cf04b93b0da2206c2e35dc3",
"model_id": "e1c152e96ef64a09bef56ab8c9b64cca",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -176,7 +179,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "bbc96d0745884970b7fcabfde6650c30",
"model_id": "4c49480a75cc4fa2ae963e77e1370acd",
"version_major": 2,
"version_minor": 0
},
Expand Down Expand Up @@ -256,14 +259,6 @@
"template_widget.observe(update_plot, names='value')\n",
"display(template_widget)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f81732fa-cd13-4d69-b104-1186a5c1109c",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
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13 changes: 7 additions & 6 deletions notebooks/ground_truth_comparison.ipynb
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Expand Up @@ -22,7 +22,8 @@
"import hyperspy.api as hs\n",
"from matplotlib.colors import to_rgba, LinearSegmentedColormap, ListedColormap\n",
"from IPython.display import display\n",
"from ipywidgets import Dropdown, interactive, Layout"
"from ipywidgets import Dropdown, interactive, Layout\n",
"from pathlib import Path"
]
},
{
Expand All @@ -44,7 +45,7 @@
"outputs": [],
"source": [
"folder_data = './data/'\n",
"gt = hs.load(folder_data + 'ground_truth.hspy')\n",
"gt = hs.load(Path(folder_data + 'ground_truth.hspy'))\n",
"\n",
"file_names = []\n",
"diffs = []\n",
Expand All @@ -56,11 +57,11 @@
" for file in files:\n",
" file_names.append(file[:-5])\n",
" if file.startswith('diff_'):\n",
" diff = hs.load(folder_data+file)\n",
" diff = hs.load(Path(folder_data+file))\n",
" diffs.append(diff)\n",
" diffs_names.append(file[:-5])\n",
" elif file.startswith('phase_map_') and file.endswith('_gt.hspy'):\n",
" phase_map = hs.load(folder_data+file)\n",
" phase_map = hs.load(Path(folder_data+file))\n",
" phase_maps.append(phase_map)\n",
" phase_maps_names.append(file[:-5])"
]
Expand Down Expand Up @@ -93,7 +94,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "35826eefc6d54c15bb8d86eb4d4c5c64",
"model_id": "87dcf68ef3f8471492da761c83523d69",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -107,7 +108,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "e7023c14637b41459a9db04e5314f491",
"model_id": "7472c77dd90b46eca97bd16d7d2cdd7e",
"version_major": 2,
"version_minor": 0
},
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29 changes: 16 additions & 13 deletions notebooks/nmf_components.ipynb
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32 changes: 12 additions & 20 deletions notebooks/preprocessing.ipynb
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Expand Up @@ -10,19 +10,10 @@
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 2,
"id": "f8bb324c-10a2-4a0a-aded-c5929b200d44",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/gvarnavides/Documents/git-repos/pattern-matching-paper/.venv/lib/python3.12/site-packages/hyperspy/misc/utils.py:72: VisibleDeprecationWarning: `_get_block_pattern` has moved to `hyperspy.misc.dask_utils`. It is for internal use only and may be removed in the future.\n",
" warnings.warn(\n"
]
}
],
"outputs": [],
"source": [
"%matplotlib widget\n",
"import numpy as np\n",
Expand All @@ -33,6 +24,7 @@
"from matplotlib.colors import LogNorm\n",
"from IPython.display import display\n",
"from ipywidgets import Dropdown, interactive, Layout, FloatSlider\n",
"from pathlib import Path\n",
"\n",
"plt.rcParams['figure.figsize'] = (3, 2)\n",
"plt.rcParams.update({'font.size': 8})\n",
Expand All @@ -41,21 +33,21 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 3,
"id": "8841172e-5d75-41db-9ab1-d5f629377a63",
"metadata": {},
"outputs": [],
"source": [
"folder_data = './data/'\n",
"s = hs.load(folder_data + '2xxx_selected_patterns.hspy')\n",
"tmds = hs.load(folder_data + '2xxx_selected_patterns_tmds.hspy')\n",
"signal_mask = hs.load(folder_data + 'signal_mask.hspy')\n",
"s = hs.load(Path(folder_data + '2xxx_selected_patterns.hspy'))\n",
"tmds = hs.load(Path(folder_data + '2xxx_selected_patterns_tmds.hspy'))\n",
"signal_mask = hs.load(Path(folder_data + 'signal_mask.hspy'))\n",
"names = ['Al', r'$\\theta^{\\prime}_{001}$', r'$\\theta^{\\prime}_{100-1}$', r'$\\theta^{\\prime}_{100-2}$', r'T$_{1-1}$', r'T$_{1-2}$']"
]
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 4,
"id": "f1049b13-049e-4541-bb37-e2f73664291c",
"metadata": {},
"outputs": [],
Expand All @@ -76,7 +68,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 5,
"id": "d892732b-3a86-42ec-b469-795c9b3253df",
"metadata": {},
"outputs": [],
Expand All @@ -92,14 +84,14 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 6,
"id": "e7e0d526-dccf-4977-960b-3d63e8ee6728",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "057d0bb1df694d6f9bf3fd5674c4f83f",
"model_id": "2a2c53a379994ca5ba5826c45a54d8bb",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -113,7 +105,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "366fcb6349c74d5092373ad04af4f1c8",
"model_id": "8c5724651f5448fea447c00f334e94a1",
"version_major": 2,
"version_minor": 0
},
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