moho

book/_toc.yml

@@ -16,6 +16,7 @@ parts:
   chapters:
     - file: chapters/ocean_science
     - file: chapters/rob/shallowprofiler
+    - file: chapters/rob/shallowprofiler_technical
     - file: chapters/rob/issues
     - file: chapters/rob/anomaly
     - file: chapters/rob/data

book/chapters/rob/anomaly.ipynb

@@ -5,7 +5,7 @@
    "id": "1c216635-59e5-4886-bbd5-634c54c5606b",
    "metadata": {},
    "source": [
-    "## anomaly\n",
+    "# Anomaly 1\n",
     "\n",
     "\n",
     "This notebook generates anomaly metadata for an OOI RCA shallow profiler, typically scanning a time series lasting\n",
@@ -818,7 +818,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

book/chapters/rob/data.ipynb

@@ -4,7 +4,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Introduction\n",
+    "# Data\n",
+    "\n",
+    "\n",
+    "\n",
+    "## Introduction\n",
     "\n",
     "\n",
     "Data are pulled in as large files for ingest. These are external to the\n",
@@ -609,7 +613,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

book/chapters/rob/issues.ipynb

@@ -5,7 +5,13 @@
    "id": "d7298eb1-3264-4415-bc2b-b2351e97e8da",
    "metadata": {},
    "source": [
-    "# Duplicate timestamps in THREDDS 1Min data\n",
+    "# Issues\n",
+    "\n",
+    "\n",
+    "## Duplicate timestamps in THREDDS 1Min data\n",
+    "\n",
+    "\n",
+    "Overcome this by using zarr files from CAVA.\n",
     "\n",
     "\n",
     "In the `data.ipynb` notebook the goals are:\n",
@@ -168,12 +174,25 @@
     "```"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "ba920d0e-0b3b-402a-b40b-04e84059cd66",
+   "metadata": {},
+   "source": [
+    "## recreating shallow profiler notebook\n",
+    "\n",
+    "\n",
+    "- Need consistent naming for spkir\n",
+    "- Need to re-get the data from CAVA\n",
+    "- Address bad pCO2 for not-july-22 months"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "53f9a65e-39d8-453c-b667-7f8a2b048f36",
    "metadata": {},
    "source": [
-    "# icepyx install is tetchy\n",
+    "## icepyx install is tetchy\n",
     "\n",
     "\n",
     "* I clone the `argo` branch: `git clone -b argo https://github.com/icesat2/icepyx`\n",

book/chapters/rob/shallowprofiler_technical.ipynb

@@ -0,0 +1,56 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d7face82-f51e-47d3-ab05-cc8c5fec2e0f",
+   "metadata": {},
+   "source": [
+    "# Shallow Profiler: Technical\n",
+    "\n",
+    "\n",
+    "This document documents the code.\n",
+    "\n",
+    "\n",
+    "\n",
+    "From the imported `shallowprofiler.py` module we have available `sensors`: A list of lists. \n",
+    "Each entry is `[sensor_name, instrument_name]` so for example `sensors[4]` is `['temperature', 'ctd']`.\n",
+    "To see the entirety run a Python cell with just `sensors`.\n",
+    "\n",
+    "With instrument and sensor names sorted (with spectral irradiance a special case) the next step\n",
+    "is to build a data dictionary called **`d `** with keys corresponding to sensor (data) types:\n",
+    "**`conductivity`, `temperature`, `pco2`** etcetera. The corresponding value for each sensor\n",
+    "key is a five-tuple indexed \\[0\\], \\[1\\], ..., \\[4\\].\n",
+    "\n",
+    "\n",
+    "```\n",
+    "0: XArray DataArray: sensor data\n",
+    "1: XArray DataArray: sensor depth (meters, negative down) corresponding to data\n",
+    "2: float: Default charting lower limit for data\n",
+    "3: float: Default charting upper limit for data\n",
+    "4: string: Default chart color e.g. \"blue\"\n",
+    "```"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}