Content classification nb (Ch 1) plus question-bank data model

ci/envs/311-dev.yaml

@@ -12,4 +12,5 @@ dependencies:
   - xarray
   - rioxarray
   - pyarrow
-  - pooch
+  - pooch
+  - anaconda::panel

cookbook/question_types.ipynb

@@ -1,12 +1,60 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "da2c1dc2-faa0-4086-b5e3-2483a6b8f762",
+   "metadata": {},
+   "source": [
+    "## Example of how to make questions from a JSON file"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ee2ffe05-66ec-43f8-b7e6-2db9302dee83",
-   "metadata": {
-    "tags": []
-   },
+   "id": "8c947305-86db-4aa3-aa4d-b0d92eaffbbb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pathlib\n",
+    "\n",
+    "import panel as pn\n",
+    "\n",
+    "import coastal_dynamics as cd\n",
+    "from coastal_dynamics.io import load_questions\n",
+    "\n",
+    "# Activate the Panel widget to make the visualizations.\n",
+    "pn.extension()\n",
+    "\n",
+    "# You can save your questions here. Please follow same naming conventions as the notebooks. When converting a Python dictionary\n",
+    "# with the questions as they are ATM to a JSON file, watch out for trailing comma's. Your code error will warn you. But if you\n",
+    "# cannot read the JSON file with the function, it's probably related to that.\n",
+    "QUESTION_DIR = pathlib.Path.cwd().parent / \"notebooks\" / \"questions\"\n",
+    "question_fp = QUESTION_DIR / \"01_coastal_classification.json\"\n",
+    "\n",
+    "# The coastal dynamics package now contains a small utilty function to load the questions from a JSON file\n",
+    "questions = load_questions(question_fp)\n",
+    "\n",
+    "# The QuestionFactory can handle the four question types.\n",
+    "q1 = cd.QuestionFactory(\n",
+    "    questions[\"Q1-1\"]\n",
+    ").serve()  # Here 1-1 refers to notebook 1 question 1.\n",
+    "q2 = cd.QuestionFactory(questions[\"Q1-2\"]).serve()\n",
+    "pn.Column(q1, q2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a98d5110-c1df-4ccd-93a2-69c0766e1b14",
+   "metadata": {},
+   "source": [
+    "## Additional examples for all four question types"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb7b9bac-90cc-45bc-a150-1c8e665ce58a",
+   "metadata": {},
    "outputs": [],
    "source": [
     "import pathlib\n",
@@ -15,29 +63,15 @@
     "import geoviews.tile_sources as gvts\n",
     "import hvplot.pandas\n",
     "import hvplot.xarray\n",
-    "import panel as pn\n",
     "import pooch\n",
     "import requests\n",
     "\n",
     "from coastal_dynamics.geometries import geo_bbox\n",
-    "from coastal_dynamics.questions.factory import QuestionWidgetFactory\n",
-    "from coastal_dynamics.questions.multiple_choice import MultipleChoiceQuestion\n",
-    "from coastal_dynamics.questions.multiple_selection import MultipleSelectionQuestion\n",
-    "from coastal_dynamics.questions.numeric import NumericQuestion\n",
-    "from coastal_dynamics.questions.text import TextQuestion\n",
     "from coastal_dynamics.visualization import DynamicWavePlot\n",
     "\n",
     "pn.extension()"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "a98d5110-c1df-4ccd-93a2-69c0766e1b14",
-   "metadata": {},
-   "source": [
-    "## Examples for all four question types"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "03cd1328-23c5-4cb4-aedb-5e2ccda3d6ca",
@@ -53,7 +87,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "mcq = MultipleChoiceQuestion(\n",
+    "cd.MultipleChoiceQuestion(\n",
     "    question_name=\"Q1: Simple Multiple Choice Question\",\n",
     "    question_text=\"What coastal landform do you typically find in tide-dominated environments?\",\n",
     "    question_options={\n",
@@ -63,7 +97,10 @@
     "        \"d\": \"Mixed sand and gravel beaches\",\n",
     "    },\n",
     "    question_answer=\"a\",\n",
-    "    question_feedback={\"correct\": \"Indeed, ...\", \"incorrect\": \"Unfortunately incorrect. Please consder...\"}\n",
+    "    question_feedback={\n",
+    "        \"correct\": \"Indeed, ...\",\n",
+    "        \"incorrect\": \"Unfortunately incorrect. Please consder...\",\n",
+    "    },\n",
     ").serve()"
    ]
   },
@@ -82,19 +119,22 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "msq = MultipleSelectionQuestion(\n",
+    "cd.MultipleSelectionQuestion(\n",
     "    question_name=\"Q1: Simple Multiple Selection Question\",\n",
     "    question_text=\"Select all morphological systems that are commonly in coastal areas.\",\n",
     "    question_options={\n",
     "        \"a\": \"Beaches\",\n",
     "        \"b\": \"Glaciers\",\n",
     "        \"c\": \"Estuaries\",\n",
     "        \"d\": \"Mountains\",\n",
-    "        \"e\": \"Sand\", \n",
-    "        \"f\": \"Mud\", \n",
+    "        \"e\": \"Sand\",\n",
+    "        \"f\": \"Mud\",\n",
     "    },\n",
     "    question_answers=[\"a\", \"c\"],\n",
-    "    question_feedback={\"correct\": \"Indeed, ...\", \"incorrect\": \"Unfortunately incorrect. Please consder...\"}\n",
+    "    question_feedback={\n",
+    "        \"correct\": \"Indeed, ...\",\n",
+    "        \"incorrect\": \"Unfortunately incorrect. Please consder...\",\n",
+    "    },\n",
     ").serve()"
    ]
   },
@@ -114,13 +154,16 @@
    "outputs": [],
    "source": [
     "kwargs = {\"precision\": 2}\n",
-    "nq = NumericQuestion(\n",
+    "cd.NumericQuestion(\n",
     "    question_name=\"Q3: Simple Numeric Question\",\n",
     "    question_text=\"What is the PSU of the global ocean?\",\n",
     "    question_answer=35,\n",
-    "    question_feedback={\"correct\": \"Indeed, ...\", \"incorrect\": \"Unfortunately incorrect. Please consder...\"}, \n",
+    "    question_feedback={\n",
+    "        \"correct\": \"Indeed, ...\",\n",
+    "        \"incorrect\": \"Unfortunately incorrect. Please consder...\",\n",
+    "    },\n",
     "    **kwargs,\n",
-    ").serve()\n"
+    ").serve()"
    ]
   },
   {
@@ -138,11 +181,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "TextQuestion(\n",
+    "cd.TextQuestion(\n",
     "    question_name=\"Q4: Some simple text question\",\n",
     "    question_text=\"How do you call the force that generates the tide?\",\n",
     "    question_answer=\"Gravitational pull\",\n",
-    "    question_feedback={\"correct\": \"Indeed, ...\", \"incorrect\": \"Unfortunately incorrect. Please consder...\"}\n",
+    "    question_feedback={\n",
+    "        \"correct\": \"Indeed, ...\",\n",
+    "        \"incorrect\": \"Unfortunately incorrect. Please consder...\",\n",
+    "    },\n",
     ").serve().show()"
    ]
   },
@@ -195,74 +241,6 @@
     "pn.Column(wave_plot, base_plot)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "12f41647-179d-499c-bfd0-b60856307b93",
-   "metadata": {},
-   "source": [
-    "## Make questions from a database (json) that is formatted like below"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "faed7b39",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "## NOTE: Cells below are commented because the factory and json data has to be updated"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "fb5cbe03-09f6-4e36-98bb-4304be46a526",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import json\n",
-    "\n",
-    "import pooch\n",
-    "\n",
-    "template_questions_href = pooch.retrieve(\n",
-    "    \"https://coclico.blob.core.windows.net/coastal-dynamics/questions/template.json\",\n",
-    "    known_hash=\"9ef56da50895d243cc5bdb2184f838a33706195522fbb8992767defd6b8d0b96\",\n",
-    ")\n",
-    "\n",
-    "with pathlib.Path(template_questions_href).open(\"r\") as f:\n",
-    "    questions = json.loads(f.read())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "22c3f14c-fad5-44de-9b82-d29e30c3c083",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "questions[\"q1\"]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "1d30b4bf-1feb-4a87-845b-41291c28b8b5",
-   "metadata": {},
-   "source": [
-    "### This is a factory class that builds the quetions based on the question type"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9bfcb690-ea32-41bd-aa64-96a7d987bee9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "question_data = questions[\"q1\"]\n",
-    "factory = QuestionWidgetFactory(question_data)\n",
-    "q1 = factory.create_question_widget().serve()  # factory has to be updated because we added a method to add feedback"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "3d26cb47-d55a-40df-a132-0f15af2dc0f6",
@@ -282,13 +260,11 @@
     "\n",
     "# Add each question's panel to the main Panel column\n",
     "for key, question_data in questions.items():\n",
-    "    question_panel = QuestionWidgetFactory(question_data).create_question_widget().serve()\n",
+    "    question_panel = cd.QuestionFactory(question_data).serve()\n",
     "    all_questions_panel.append(question_panel)\n",
     "\n",
     "# Create a wave plot and a base plot\n",
-    "wave_plot = DynamicWavePlot(\n",
-    "    amplitude_range=(1, 3, 0.5), wavelength_range=(5, 20, 0.1)\n",
-    ")\n",
+    "wave_plot = DynamicWavePlot(amplitude_range=(1, 3, 0.5), wavelength_range=(5, 20, 0.1))\n",
     "base_plot = gvts.EsriImagery(width=900, height=500)\n",
     "\n",
     "# Combine all components into a single dashboard\n",
@@ -331,9 +307,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "jl-full",
+   "display_name": "Python [conda env:coastal]",
    "language": "python",
-   "name": "python3"
+   "name": "conda-env-coastal-py"
   },
   "language_info": {
    "codemirror_mode": {