Add to docs

Author: awf

docs/source/05-speed.ipynb renamed to docs/source/04-benchmark.ipynb

@@ -35,16 +35,18 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Timing tests\n",
+    "# Timing tests\n",
     "\n",
-    "The `gfloat` library is designed for readability over performance, and the reference code for computations is the (slow) scalar code e.g. `round_float`.  There are vectorized implementations (e.g. `round_ndarray`, and when combined with JAX, these can go reasonably fast).\n",
+    "The `gfloat` library is designed for readability over performance, and the reference code for computations is the (slow) scalar code e.g. `round_float`.\n",
     "\n",
-    "Let's try to convert some values to FP8:"
+    "There are vectorized implementations (e.g. `round_ndarray`, and when combined with JAX, these can go reasonably fast).\n",
+    "\n",
+    "Let's see how long it takes to encoed some values to FP8..."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {

docs/source/api.rst

@@ -12,6 +12,12 @@ Scalar Functions
 .. autofunction:: round_float
 .. autofunction:: encode_float
 
+Array Functions
+---------------
+
+.. autofunction:: round_ndarray
+.. autofunction:: encode_ndarray
+
 Block format functions
 ----------------------
 

docs/source/notebooks.rst

@@ -11,3 +11,4 @@ Some notebooks to illustrate uses of the library
    01-decode.ipynb
    02-value-stats.ipynb
    03-value-tables.ipynb
+   04-benchmark.ipynb