diff --git a/.circleci/config.yml b/.circleci/config.yml
index 270de71a6d..7081efafc7 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -69,9 +69,9 @@ commands:
- run:
name: Switch dof-dss packages to HEAD on development branch
command: |
- composer require dof-dss/nicsdru_unity_theme:dev-9.x-dev \
- dof-dss/nicsdru_origins_modules:dev-9.x-dev \
- dof-dss/nicsdru_unity_modules:dev-9.x-dev
+ composer require dof-dss/nicsdru_unity_theme:dev-10.x-dev \
+ dof-dss/nicsdru_origins_modules:dev-10.x-dev \
+ dof-dss/nicsdru_unity_modules:dev-10.x-dev
install_psh_cli:
description: "Install the Platform.sh CLI tool"
steps:
@@ -320,52 +320,9 @@ jobs:
workflows:
version: 2
- build-test-deploy:
- jobs:
- - build
- - unity_base_checks:
- requires:
- - build
- - coding_standards:
- requires:
- - build
- - deprecated_code:
- requires:
- - build
- #- check_illegal_updates:
- # requires:
- # - build
-
- # A nightly build of the project, using all dof-dss packages at HEAD from development branch.
nightly-edge-build:
- when:
- and:
- - not:
- equal: [ "https://github.com/dof-dss/unity_base", << pipeline.project.git_url >> ]
- triggers:
- - schedule:
- # At 00:30 Monday to Friday
- cron: "30 0 * * 1-5"
- filters:
- branches:
- only:
- - development
jobs:
- edge_build
-
- # A nightly deploy or re-deploy of the edge site after the git branch has been created in nightly-edge-build.
- nightly-edge-build-post-build-tasks:
- when:
- and:
- - not:
- equal: [ "https://github.com/dof-dss/unity_base", << pipeline.project.git_url >> ]
- triggers:
- - schedule:
- # At 01:23 Monday to Friday
- cron: "55 1 * * 1-5"
- filters:
- branches:
- only:
- - edge
- jobs:
- - sync_data
+ - sync_data:
+ requires:
+ - edge_build
diff --git a/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/.ipynb_checkpoints/Untitled-checkpoint.ipynb
new file mode 100644
index 0000000000..363fcab7ed
--- /dev/null
+++ b/.ipynb_checkpoints/Untitled-checkpoint.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Untitled.ipynb b/Untitled.ipynb
new file mode 100644
index 0000000000..c76c85d66e
--- /dev/null
+++ b/Untitled.ipynb
@@ -0,0 +1,671 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "ca9f14be-a2b3-465b-ae76-227f680328c7",
+ "metadata": {},
+ "source": [
+ "# My first Jupyter notebook\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "7480731a-789f-4bfe-959b-0f75478aa806",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "SyntaxError",
+ "evalue": "invalid syntax (1988133667.py, line 1)",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;36m Cell \u001b[0;32mIn[1], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m first intro\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+ ]
+ }
+ ],
+ "source": [
+ "first intro"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "d5ca2c1d-1935-4b08-a689-cd5d017c9feb",
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "IndentationError",
+ "evalue": "expected an indented block after 'for' statement on line 1 (2114585337.py, line 2)",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;36m Cell \u001b[0;32mIn[2], line 2\u001b[0;36m\u001b[0m\n\u001b[0;31m print(2**i - 1)\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m expected an indented block after 'for' statement on line 1\n"
+ ]
+ }
+ ],
+ "source": [
+ "for i in range(500):\n",
+ "print(2**i - 1)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "62b7929b-38ff-498b-a4b0-df7ea9bf529b",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
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+ ]
+ }
+ ],
+ "source": [
+ "for i in range(500):\n",
+ " print(2**i - 1)\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "bd439f79-da46-45c8-b6d3-7c6e62ddedf8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import json\n",
+ "import uuid\n",
+ "from IPython.display import display_javascript, display_html, display\n",
+ "\n",
+ "class FlotPlot(object):\n",
+ " def __init__(self, x, y):\n",
+ " self.x = x\n",
+ " self.y = y\n",
+ " self.uuid = str(uuid.uuid4())\n",
+ "\n",
+ " def _ipython_display_(self):\n",
+ " json_data = json.dumps(list(zip(self.x, self.y)))\n",
+ " display_html(\n",
+ " ''\n",
+ " .format(self.uuid), raw=True)\n",
+ " display_javascript(\"\"\"require([\"..removed../jquery.flot.min.js\"],\n",
+ "\n",
+ "function() {\n",
+ " var line = JSON.parse (\"%s\");\n",
+ " console.log(line);\n",
+ " $.plot(\"#%s\", [line]);\n",
+ "});\n",
+ "\n",
+ "\"\"\" % (json_data, self.uuid), raw=True)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "62562f02-efb6-479b-ba8c-663b2d964e65",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/javascript": [
+ "require([\"..removed../jquery.flot.min.js\"],\n",
+ "\n",
+ "function() {\n",
+ " var line = JSON.parse (\"[[0.0, 0.0], [0.20408163265306123, 0.20266793654820095], [0.40816326530612246, 0.39692414892492234], [0.6122448979591837, 0.5747060412161792], [0.8163265306122449, 0.7286347834693504], [1.0204081632653061, 0.8523215697196184], [1.2244897959183674, 0.9406327851124867], [1.4285714285714286, 0.9899030763721239], [1.6326530612244898, 0.9980874821347183], [1.836734693877551, 0.9648463089837632], [2.0408163265306123, 0.8915592304110037], [2.2448979591836737, 0.7812680235262638], [2.4489795918367347, 0.6385503202266021], [2.6530612244897958, 0.469329612777201], [2.857142857142857, 0.28062939951435684], [3.0612244897959187, 0.0802816748428135], [3.2653061224489797, -0.12339813736217871], [3.4693877551020407, -0.3219563150726187], [3.673469387755102, -0.5071517094845144], [3.8775510204081636, -0.6712977935519321], [4.081632653061225, -0.8075816909683363], [4.285714285714286, -0.9103469443107828], [4.4897959183673475, -0.9753282860670456], [4.6938775510204085, -0.9998286683840896], [4.8979591836734695, -0.9828312039256306], [5.1020408163265305, -0.9250413717382029], [5.3061224489795915, -0.8288577363730427], [5.510204081632653, -0.6982723955653997], [5.714285714285714, -0.5387052883861563], [5.918367346938775, -0.3567792408989381], [6.122448979591837, -0.16004508604325057], [6.326530612244898, 0.04333173336868346], [6.530612244897959, 0.2449100710119793], [6.73469387755102, 0.4363234264718193], [6.938775510204081, 0.6096271964908323], [7.142857142857143, 0.7576284153927202], [7.346938775510204, 0.8741842988197335], [7.551020408163265, 0.9544571997387519], [7.755102040816327, 0.9951153947776636], [7.959183673469388, 0.9944713672636168], [8.16326530612245, 0.9525518475314604], [8.36734693877551, 0.8710967034823207], [8.571428571428571, 0.7534867274396376], [8.775510204081632, 0.6046033165061544], [8.979591836734695, 0.4306258703827373], [9.183673469387756, 0.2387753156440309], [9.387755102040817, 0.03701440148506237], [9.591836734693878, -0.1662827938487564], [9.795918367346939, -0.3626784288265488], [10.0, -0.5440211108893698]]\");\n",
+ " console.log(line);\n",
+ " $.plot(\"#73250a7c-470c-42dd-bb2e-dc9abd83128c\", [line]);\n",
+ "});\n",
+ "\n"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "x = np.linspace(0,10)\n",
+ "y = np.sin(x)\n",
+ "FlotPlot(x, np.sin(x))\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "6344520a-b7e8-4dbf-a6a4-759e33e2f582",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "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": "3.11.6"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}