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86 | 86 | "│ └── 'transcripts': DataFrame with shape: (<Delayed>, 8) (3D points)\n",
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87 | 87 | "├── Shapes\n",
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88 | 88 | "│ ├── 'cell_boundaries': GeoDataFrame shape: (167780, 1) (2D shapes)\n",
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89 |
| - "│ ├── 'cell_circles': GeoDataFrame shape: (167780, 2) (2D shapes)\n", |
90 |
| - "│ └── 'xenium_landmarks': GeoDataFrame shape: (3, 2) (2D shapes)\n", |
| 89 | + "│ └── 'cell_circles': GeoDataFrame shape: (167780, 2) (2D shapes)\n", |
91 | 90 | "└── Tables\n",
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92 | 91 | " └── 'table': AnnData (167780, 313)\n",
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93 | 92 | "with coordinate systems:\n",
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94 |
| - " ▸ 'aligned', with elements:\n", |
95 |
| - " morphology_focus (Images)\n", |
96 | 93 | " ▸ 'global', with elements:\n",
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97 |
| - " morphology_focus (Images), morphology_mip (Images), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), xenium_landmarks (Shapes)" |
| 94 | + " morphology_focus (Images), morphology_mip (Images), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes)" |
98 | 95 | ]
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99 | 96 | },
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100 | 97 | "execution_count": 2,
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142 | 139 | "│ ├── 'CytAssist_FFPE_Human_Breast_Cancer_hires_image': DataArray[cyx] (3, 2000, 1809)\n",
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143 | 140 | "│ └── 'CytAssist_FFPE_Human_Breast_Cancer_lowres_image': DataArray[cyx] (3, 600, 543)\n",
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144 | 141 | "├── Shapes\n",
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145 |
| - "│ ├── 'CytAssist_FFPE_Human_Breast_Cancer': GeoDataFrame shape: (4992, 2) (2D shapes)\n", |
146 |
| - "│ └── 'visium_landmarks': GeoDataFrame shape: (3, 2) (2D shapes)\n", |
| 142 | + "│ └── 'CytAssist_FFPE_Human_Breast_Cancer': GeoDataFrame shape: (4992, 2) (2D shapes)\n", |
147 | 143 | "└── Tables\n",
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148 | 144 | " └── 'table': AnnData (4992, 18085)\n",
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149 | 145 | "with coordinate systems:\n",
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150 |
| - " ▸ 'aligned', with elements:\n", |
151 |
| - " CytAssist_FFPE_Human_Breast_Cancer_full_image (Images), CytAssist_FFPE_Human_Breast_Cancer_hires_image (Images), CytAssist_FFPE_Human_Breast_Cancer_lowres_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes), visium_landmarks (Shapes)\n", |
152 |
| - " ▸ 'downscaled_hires', with elements:\n", |
| 146 | + " ▸ 'CytAssist_FFPE_Human_Breast_Cancer', with elements:\n", |
| 147 | + " CytAssist_FFPE_Human_Breast_Cancer_full_image (Images), CytAssist_FFPE_Human_Breast_Cancer_hires_image (Images), CytAssist_FFPE_Human_Breast_Cancer_lowres_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)\n", |
| 148 | + " ▸ 'CytAssist_FFPE_Human_Breast_Cancer_downscaled_hires', with elements:\n", |
153 | 149 | " CytAssist_FFPE_Human_Breast_Cancer_hires_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)\n",
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154 |
| - " ▸ 'downscaled_lowres', with elements:\n", |
155 |
| - " CytAssist_FFPE_Human_Breast_Cancer_lowres_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)\n", |
156 |
| - " ▸ 'global', with elements:\n", |
157 |
| - " CytAssist_FFPE_Human_Breast_Cancer_full_image (Images), CytAssist_FFPE_Human_Breast_Cancer_hires_image (Images), CytAssist_FFPE_Human_Breast_Cancer_lowres_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes), visium_landmarks (Shapes)" |
| 150 | + " ▸ 'CytAssist_FFPE_Human_Breast_Cancer_downscaled_lowres', with elements:\n", |
| 151 | + " CytAssist_FFPE_Human_Breast_Cancer_lowres_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)" |
158 | 152 | ]
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159 | 153 | },
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160 | 154 | "execution_count": 3,
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282 | 276 | "outputs": [],
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283 | 277 | "source": [
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284 | 278 | "from spatialdata.models import ShapesModel\n",
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| 279 | + "from spatialdata.transformations import Identity\n", |
285 | 280 | "\n",
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286 | 281 | "visium_landmarks = ShapesModel.parse(\n",
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287 |
| - " np.array([[10556.699, 7829.764], [13959.155, 13522.025], [10621.200, 17392.116]]), geometry=0, radius=500\n", |
| 282 | + " np.array([[10556.699, 7829.764], [13959.155, 13522.025], [10621.200, 17392.116]]), geometry=0, radius=500, transformations={'CytAssist_FFPE_Human_Breast_Cancer': Identity()}\n", |
288 | 283 | ")\n",
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289 | 284 | "visium_sdata[\"visium_landmarks\"] = visium_landmarks\n",
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290 | 285 | "\n",
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| 286 | + "# for Xenium data, the data is aligned to the 'global' coordinate system as with can see with print(xenium_sdata), so there is no need to specify transformations in .parse()\n", |
291 | 287 | "xenium_landmarks = ShapesModel.parse(\n",
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292 | 288 | " np.array([[9438.385, 13933.017], [24847.866, 5948.002], [34082.584, 15234.235]]), geometry=0, radius=500\n",
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293 | 289 | ")\n",
|
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389 | 385 | " reference_element=xenium_sdata[\"morphology_focus\"],\n",
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390 | 386 | " moving_element=visium_sdata[\"CytAssist_FFPE_Human_Breast_Cancer_full_image\"],\n",
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391 | 387 | " reference_coordinate_system=\"global\",\n",
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392 |
| - " moving_coordinate_system=\"global\",\n", |
| 388 | + " moving_coordinate_system=\"CytAssist_FFPE_Human_Breast_Cancer\",\n", |
393 | 389 | " new_coordinate_system=\"aligned\",\n",
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394 | 390 | ")\n",
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395 | 391 | "affine"
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571 | 567 | "name": "python",
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572 | 568 | "nbconvert_exporter": "python",
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573 | 569 | "pygments_lexer": "ipython3",
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574 |
| - "version": "3.11.0" |
| 570 | + "version": "3.10.0" |
575 | 571 | },
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576 | 572 | "vscode": {
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577 | 573 | "interpreter": {
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