updating notebook params

Author: carsen-stringer

notebooks/rastermap_largescale.ipynb

@@ -103,8 +103,7 @@
    "source": [
     "model = Rastermap(n_clusters=100, # number of clusters to compute\n",
     "                  n_PCs=128, # number of PCs to use\n",
-    "                  locality=0.75, # locality in sorting to find sequences (this is a value from 0-1)\n",
-    "                  time_lag_window=5, # use future timepoints to compute correlation\n",
+    "                  locality=0., # locality in sorting to find sequences (this is a value from 0-1)\n",
     "                  grid_upsample=10, # default value, 10 is good for large recordings\n",
     "                ).fit(spks)\n",
     "y = model.embedding # neurons x 1\n",

notebooks/rastermap_singleneurons.ipynb

@@ -27,7 +27,7 @@
    "outputs": [],
    "source": [
     "!pip install numpy>=1.24 # (required for google colab)\n",
-    "!pip install rastermap \n",
+    "!pip install rastermap\n",
     "!pip install matplotlib"
    ]
   },
@@ -95,7 +95,7 @@
    "source": [
     "model = Rastermap(n_clusters=None, # None turns off clustering and sorts single neurons \n",
     "                  n_PCs=64, # use fewer PCs than neurons\n",
-    "                  locality=0.15, # some locality in sorting (this is a value from 0-1)\n",
+    "                  locality=0.1, # some locality in sorting (this is a value from 0-1)\n",
     "                  time_lag_window=15, # use future timepoints to compute correlation\n",
     "                  grid_upsample=0, # 0 turns off upsampling since we're using single neurons\n",
     "                ).fit(spks)\n",
@@ -255,7 +255,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.16"
   },
   "orig_nbformat": 4,
   "vscode": {

paper/fig4.ipynb

@@ -63,8 +63,8 @@
     "\n",
     "model = Rastermap(n_clusters=None, \n",
     "                  n_PCs=64, \n",
-    "                  locality=0.1,   # 0.1<-include nan's, #0.05 <- interp nan's #0.25 <- remove nan's\n",
-    "                  time_lag_window=15,  # 15<- include nan's, #10 <- interp nan's # 20 <- remove nan's\n",
+    "                  locality=0.1,   \n",
+    "                  time_lag_window=15,  \n",
     "                  symmetric=False,\n",
     "                  grid_upsample=0,\n",
     "                  ).fit(spks)\n",