Merge branch 'main' of https://github.com/flatironinstitute/cryo_em_SBI

README.rst

@@ -18,7 +18,7 @@ cryoSBI - Simulation-based Inference for Cryo-EM
 Summary
 -------
 cryoSBI is a Python module for simulation-based inference in cryo-electron microscopy. The module provides tools for simulating cryo-EM particles, training an amortized posterior model, and sampling from the posterior distribution.
-The code is based on the SBI libary `Lampe <https://lampe.readthedocs.io/en/stable/>`_, which is a using Pytorch. 
+The code is based on the SBI libary `Lampe <https://lampe.readthedocs.io/en/stable/>`_, which is using Pytorch. 
 
 Installing
 ----------
@@ -45,7 +45,7 @@ Download this repository
 ------------------------
 .. code:: bash
 
-    git clone `https://github.com/DSilva27/cryo_em_SBI.git`
+    git clone https://github.com/flatironinstitute/cryoSBI.git
 
 Navigate to the cloned repository and install the module
 --------------------------------------------------------

src/cryo_sbi/utils/image_utils.py

@@ -423,7 +423,9 @@ def load_index_map(self, path: str):
             path (str): Path to load the index map.
         """
         index_map = np.load(path)
-        assert self.paths == index_map["paths"], "Paths do not match the index map."
+        assert len(self.paths) == len(index_map["paths"]), "Number of paths do not match the index map."
+        for path1, path2 in zip(self.paths, index_map["paths"]):
+            assert path1 == path2, "Paths do not match the index map."
         self._path_index = index_map["path_index"]
         self._file_index = index_map["file_index"]
         self._index_map = True

tutorials/tutorial.ipynb

@@ -11,7 +11,6 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "from scipy.spatial.transform import Rotation\n",
-    "import umap\n",
     "\n",
     "from cryo_sbi import CryoEmSimulator\n",
     "import cryo_sbi.inference.train_npe_model as train_npe_model\n",
@@ -20,6 +19,24 @@
     "from cryo_sbi.utils.visualize_models import plot_model"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### If you want to run the latent space analysis with UMAP, you need to install the following package:\n",
+    "You can find the installation instructions [here](https://umap-learn.readthedocs.io/en/latest/). \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# If you installed umap you can import it here \n",
+    "import umap"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -363,7 +380,7 @@
     "plt.scatter(\n",
     "    latent_vecs_transformed[:, 0],\n",
     "    latent_vecs_transformed[:, 1],\n",
-    "    c=dist,\n",
+    "    c=side_length,\n",
     "    cmap=\"viridis\",\n",
     "    s=10,\n",
     ")\n",
@@ -389,13 +406,6 @@
     "plt.xlabel(\"UMAP 1\")\n",
     "plt.ylabel(\"UMAP 2\")"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {