|
158 | 158 | {
|
159 | 159 | "data": {
|
160 | 160 | "application/vnd.jupyter.widget-view+json": {
|
161 |
| - "model_id": "a467572f837444d2bd1ebac5fbdaec9b", |
| 161 | + "model_id": "06aa06e6af134d61bb3a40df62a601c2", |
162 | 162 | "version_major": 2,
|
163 | 163 | "version_minor": 0
|
164 | 164 | },
|
|
349 | 349 | {
|
350 | 350 | "data": {
|
351 | 351 | "application/vnd.jupyter.widget-view+json": {
|
352 |
| - "model_id": "7eb6c0c85c334acd8765084783e4e983", |
| 352 | + "model_id": "140a3876e95c46c784ca047e1aeb8fab", |
353 | 353 | "version_major": 2,
|
354 | 354 | "version_minor": 0
|
355 | 355 | },
|
|
453 | 453 | {
|
454 | 454 | "data": {
|
455 | 455 | "application/vnd.jupyter.widget-view+json": {
|
456 |
| - "model_id": "7e30cb38619144d59d4e9e98b8ef0e7f", |
| 456 | + "model_id": "2b0b5a73f52744eaa29a75685d10ed7c", |
457 | 457 | "version_major": 2,
|
458 | 458 | "version_minor": 0
|
459 | 459 | },
|
|
467 | 467 | {
|
468 | 468 | "data": {
|
469 | 469 | "application/vnd.jupyter.widget-view+json": {
|
470 |
| - "model_id": "53d54426e28d46f7bc92ba32ab587572", |
| 470 | + "model_id": "0edf24e9f6764619877928989b16e4ce", |
471 | 471 | "version_major": 2,
|
472 | 472 | "version_minor": 0
|
473 | 473 | },
|
|
528 | 528 | "id": "f672dcd8-f55b-4476-b72a-d7a292fee32e",
|
529 | 529 | "metadata": {},
|
530 | 530 | "source": [
|
531 |
| - "## `ImageWidget` using zebrafish data" |
| 531 | + "## `ImageWidget` using zebrafish whole-brain data\n", |
| 532 | + "\n", |
| 533 | + "## Supports numpy-like array objects and large array formats including: memmaps, zarr, hdf5, etc. via lazy loading\n", |
| 534 | + "\n", |
| 535 | + "#### Visualization is limited by file-formats and file system access performance: it will work with files of arbitrary size!" |
532 | 536 | ]
|
533 | 537 | },
|
534 | 538 | {
|
|
585 | 589 | },
|
586 | 590 | {
|
587 | 591 | "cell_type": "code",
|
588 |
| - "execution_count": 38, |
| 592 | + "execution_count": 19, |
589 | 593 | "id": "770f8242-e8ff-40fc-86c3-9d44abca85d6",
|
590 | 594 | "metadata": {
|
591 | 595 | "tags": []
|
|
594 | 598 | {
|
595 | 599 | "data": {
|
596 | 600 | "application/vnd.jupyter.widget-view+json": {
|
597 |
| - "model_id": "8a1b7240246b4128b4c39d49aeb5d17e", |
| 601 | + "model_id": "92df5a7b047e44e18374c9f85ec2ac14", |
598 | 602 | "version_major": 2,
|
599 | 603 | "version_minor": 0
|
600 | 604 | },
|
|
624 | 628 | " display(iw.show())"
|
625 | 629 | ]
|
626 | 630 | },
|
| 631 | + { |
| 632 | + "cell_type": "code", |
| 633 | + "execution_count": 20, |
| 634 | + "id": "4329ac46-7820-4a4b-8b03-dbbc1d7b545e", |
| 635 | + "metadata": { |
| 636 | + "tags": [] |
| 637 | + }, |
| 638 | + "outputs": [], |
| 639 | + "source": [ |
| 640 | + "for subplot in iw.gridplot:\n", |
| 641 | + " subplot[\"image_widget_managed\"].cmap.reset_vmin_vmax()" |
| 642 | + ] |
| 643 | + }, |
627 | 644 | {
|
628 | 645 | "cell_type": "markdown",
|
629 | 646 | "id": "03c793fa-4d29-45d9-bf8c-c0b9133ee229",
|
|
650 | 667 | {
|
651 | 668 | "cell_type": "code",
|
652 | 669 | "execution_count": 22,
|
| 670 | + "id": "48951d83-c273-451d-84ce-be14cd7fc1c3", |
| 671 | + "metadata": { |
| 672 | + "tags": [] |
| 673 | + }, |
| 674 | + "outputs": [], |
| 675 | + "source": [ |
| 676 | + "for subplot in iw.gridplot:\n", |
| 677 | + " subplot[\"image_widget_managed\"].cmap.vmin = -0.12\n", |
| 678 | + " subplot[\"image_widget_managed\"].cmap.vmax = 2.3" |
| 679 | + ] |
| 680 | + }, |
| 681 | + { |
| 682 | + "cell_type": "code", |
| 683 | + "execution_count": 23, |
653 | 684 | "id": "e49e7b96-c1a7-4c1f-956a-1bab482b0ce0",
|
654 | 685 | "metadata": {
|
655 | 686 | "tags": []
|
|
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