workshop: add berk_workshop_v1 (browse + BF/DF + probe + DPC, Colab T4)

notebooks/berk_workshop_v1.ipynb

@@ -0,0 +1,295 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "686f9970",
+   "metadata": {},
+   "source": [
+    "# Workshop: real-gold 4D-STEM — browse, BF, DF, probe, DPC (Colab T4)\n",
+    "\n",
+    "[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/gist/bobleesj/a05a90185c6cddbb331342cae6d7e9c1/berk_workshop_v1.ipynb)\n",
+    "\n",
+    "Load a real 4D-STEM gold dataset from Hugging Face, browse it interactively,\n",
+    "compute bright field / dark field, find the probe center, and visualize DPC —\n",
+    "all in your browser, on Colab's free T4 GPU. No local install, no `quantem.live`.\n",
+    "\n",
+    "Two installs only: `quantem.widget` (TestPyPI prerelease) and `quantem`\n",
+    "(from the `berk-workshop` branch on `bobleesj/quantem`). Everything runs on\n",
+    "torch on the GPU.\n",
+    "\n",
+    "**Total runtime: 2–3 minutes** (install dominates)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c15f382c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install -q --pre --extra-index-url https://test.pypi.org/simple/ quantem.widget huggingface_hub\n",
+    "!pip install -q git+https://github.com/bobleesj/quantem.git@berk-workshop"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "30258881",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import quantem as em\n",
+    "import quantem.widget\n",
+    "import torch\n",
+    "\n",
+    "print(\"quantem        \", em.__version__)\n",
+    "print(\"quantem.widget \", quantem.widget.__version__)\n",
+    "print(\"torch          \", torch.__version__)\n",
+    "print(\"cuda available:\", torch.cuda.is_available(),\n",
+    "      torch.cuda.get_device_name(0) if torch.cuda.is_available() else \"(no GPU runtime)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b491687f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Download a pre-binned NumPy bundle from the public Hugging Face dataset and\n",
+    "# wrap it as a torch tensor on the GPU. The 4D shape is (scan_row, scan_col,\n",
+    "# k_row, k_col) = (512, 512, 24, 24); detector binned 8x from the original 192x192\n",
+    "# to keep the Colab download small (~300 MB).\n",
+    "import os, json\n",
+    "import numpy as np\n",
+    "from huggingface_hub import snapshot_download\n",
+    "\n",
+    "folder = snapshot_download(\"bobleesj/quantem-data\", repo_type=\"dataset\",\n",
+    "                           allow_patterns=[\"4dstem/gold_512_npy_bin8/*\"])\n",
+    "asset = os.path.join(folder, \"4dstem\", \"gold_512_npy_bin8\")\n",
+    "data = np.load(os.path.join(asset, \"data.npy\"))           # (512, 512, 24, 24) uint16\n",
+    "meta = json.load(open(os.path.join(asset, \"meta.json\")))\n",
+    "\n",
+    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
+    "t = torch.from_numpy(data).to(device)\n",
+    "dset = em.core.datastructures.Dataset4dstem.from_tensor(\n",
+    "    t, sampling=meta[\"sampling\"], units=meta[\"units\"], name=meta[\"name\"],\n",
+    ")\n",
+    "print(f\"dataset on {dset.tensor.device}: shape {dset.shape}, dtype {dset.tensor.dtype}\")\n",
+    "print(f\"sampling {meta['sampling']} {meta['units']}\")\n",
+    "print(f\"optics: {meta['voltage_kV']} kV, probe {meta['probe_semiangle_mrad']} mrad, CL {meta['camera_length_mm']} mm\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a3f9a244",
+   "metadata": {},
+   "source": [
+    "## Step 1 — Browse the 4D-STEM dataset interactively\n",
+    "\n",
+    "Drag the scan cursor in the left panel. The CBED on the right updates live.\n",
+    "This is your real-time bright-field / dark-field — pixels INSIDE the central\n",
+    "disk are BF, OUTSIDE are DF. The widget renders in your browser via WebGPU\n",
+    "(works in Chrome on free Colab)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "59204966",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "quantem.widget.Show4DSTEM(dset)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "61add712",
+   "metadata": {},
+   "source": [
+    "## Step 2 — The probe (mean diffraction pattern)\n",
+    "\n",
+    "Average all diffraction patterns over the scan. What's left is the probe — the\n",
+    "shape of the electron beam at the detector. A clean BF disk should appear."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e49b4f3d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mean_dp = dset.tensor.to(torch.float32).mean(dim=(0, 1))   # (24, 24) on GPU\n",
+    "print(f\"mean_dp shape {tuple(mean_dp.shape)}, device {mean_dp.device}\")\n",
+    "\n",
+    "em.core.visualization.show_2d(\n",
+    "    mean_dp.cpu().numpy(),\n",
+    "    title=\"Probe (mean DP)\",\n",
+    "    cmap=\"inferno\",\n",
+    "    cbar=True,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c09a9ae6",
+   "metadata": {},
+   "source": [
+    "## Step 3 — Probe center via center-of-mass\n",
+    "\n",
+    "Weighted average of the detector coordinates. Should land near the middle of\n",
+    "the detector (~12, 12) for a centered beam — small offset is normal."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "eee02115",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "H, W = mean_dp.shape\n",
+    "row = torch.arange(H, device=mean_dp.device, dtype=torch.float32)[:, None]\n",
+    "col = torch.arange(W, device=mean_dp.device, dtype=torch.float32)[None, :]\n",
+    "total = mean_dp.sum()\n",
+    "cy = (mean_dp * row).sum() / total\n",
+    "cx = (mean_dp * col).sum() / total\n",
+    "print(f\"probe center: row={cy.item():.3f}, col={cx.item():.3f}   \"\n",
+    "      f\"(detector {H}x{W}, geometric center ~{H/2:.1f}, ~{W/2:.1f})\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5028708e",
+   "metadata": {},
+   "source": [
+    "## Step 4 — Bright field + dark field virtual images\n",
+    "\n",
+    "Build an aperture mask at the probe center. For every scan position, sum the\n",
+    "pixels inside the disk (BF) and outside (DF). One line of torch, runs on the\n",
+    "GPU in milliseconds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0c72f95d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "BF_RADIUS_PX = 6.0   # ~30 mrad on the bin8 detector\n",
+    "\n",
+    "rr, cc = torch.meshgrid(row.squeeze(), col.squeeze(), indexing=\"ij\")\n",
+    "r_from_center = ((rr - cy) ** 2 + (cc - cx) ** 2).sqrt()\n",
+    "bf_mask = (r_from_center <= BF_RADIUS_PX).float()\n",
+    "df_mask = 1.0 - bf_mask\n",
+    "\n",
+    "data_f = dset.tensor.to(torch.float32)\n",
+    "bf = (data_f * bf_mask).sum(dim=(-2, -1)).cpu().numpy()\n",
+    "df = (data_f * df_mask).sum(dim=(-2, -1)).cpu().numpy()\n",
+    "\n",
+    "em.core.visualization.show_2d(\n",
+    "    [bf, df, mean_dp.cpu().numpy()],\n",
+    "    title=[\"Bright field\", \"Dark field\", \"Probe\"],\n",
+    "    cmap=[\"gray\", \"gray\", \"inferno\"],\n",
+    "    scalebar=[\n",
+    "        {\"sampling\": meta[\"sampling\"][0], \"units\": meta[\"units\"][0]},\n",
+    "        {\"sampling\": meta[\"sampling\"][0], \"units\": meta[\"units\"][0]},\n",
+    "        {\"sampling\": meta[\"sampling\"][2], \"units\": meta[\"units\"][2]},\n",
+    "    ],\n",
+    "    axsize=(4, 4),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ed35980e",
+   "metadata": {},
+   "source": [
+    "## Step 5 — Differential phase contrast (DPC)\n",
+    "\n",
+    "Per-scan-position center-of-mass. Each detector pattern's centroid shifts when\n",
+    "local electric fields deflect the probe. The maps below show those shifts as\n",
+    "signed deflection — red/blue around features means real DPC contrast.\n",
+    "\n",
+    "Implemented inline as a single torch reduction on the GPU."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1fa064b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_f = dset.tensor.to(torch.float32)\n",
+    "H, W = data_f.shape[-2:]\n",
+    "qx = torch.arange(H, device=data_f.device, dtype=torch.float32)[:, None]\n",
+    "qy = torch.arange(W, device=data_f.device, dtype=torch.float32)[None, :]\n",
+    "\n",
+    "total_per_dp = data_f.sum(dim=(-2, -1))                   # (scan_r, scan_c)\n",
+    "com_row = (data_f * qx).sum(dim=(-2, -1)) / total_per_dp\n",
+    "com_col = (data_f * qy).sum(dim=(-2, -1)) / total_per_dp\n",
+    "\n",
+    "# Detrend (subtract mean) so the colormap is zero-centered on signed deflection.\n",
+    "com_row -= com_row.mean()\n",
+    "com_col -= com_col.mean()\n",
+    "\n",
+    "em.core.visualization.show_2d(\n",
+    "    [com_row.cpu().numpy(), com_col.cpu().numpy()],\n",
+    "    title=[\"DPC — CoM row (qx)\", \"DPC — CoM col (qy)\"],\n",
+    "    cmap=\"RdBu_r\",\n",
+    "    cbar=True,\n",
+    "    scalebar={\"sampling\": meta[\"sampling\"][0], \"units\": meta[\"units\"][0]},\n",
+    "    axsize=(4, 4),\n",
+    ")\n",
+    "print(f\"CoM row range [{com_row.min().item():.4f}, {com_row.max().item():.4f}] px\")\n",
+    "print(f\"CoM col range [{com_col.min().item():.4f}, {com_col.max().item():.4f}] px\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8585e78a",
+   "metadata": {},
+   "source": [
+    "## What you just did\n",
+    "\n",
+    "1. Loaded real 4D-STEM gold from Hugging Face → torch tensor on the Colab T4.\n",
+    "2. Browsed it interactively with `Show4DSTEM`.\n",
+    "3. Computed the probe (mean DP) and found its center on the detector.\n",
+    "4. Computed BF and DF virtual images with one aperture mask.\n",
+    "5. Computed DPC (per-scan-position CoM) showing electric-field deflection.\n",
+    "\n",
+    "Everything ran on the GPU in seconds.\n",
+    "\n",
+    "## Try next\n",
+    "\n",
+    "- Swap `gold_512_npy_bin8` → `gold_512_npy_bin4` (factor-of-2 finer detector\n",
+    "  sampling at 4× the download).\n",
+    "- Change `BF_RADIUS_PX` to expand/shrink the BF disk.\n",
+    "- Detrend DPC differently (e.g. subtract a plane fit) to reveal smaller features.\n",
+    "\n",
+    "v2 will add iterative ptychography (`PtychoLite`) on the same data."
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "gpuType": "T4",
+   "include_colab_link": true,
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}