Upgrade nbdime for jupyterlab 4

.gitignore

@@ -12,6 +12,7 @@ MANIFEST
 .cache
 .pytest_cache
 .idea
+.yarn
 
 
 .spyderproject

examples/example1/center.ipynb

@@ -0,0 +1,38 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "44a9ad96-674a-49e5-94ee-9d84f386ecbc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "a = np.arange(15).reshape(3, 5)\n",
+ "b = np.arange(5)\n",
+ "c = a + b"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example1/left.ipynb

@@ -0,0 +1,39 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "44a9ad96-674a-49e5-94ee-9d84f386ecbc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy\n",
+ "\n",
+ "a = np.arange(15).reshape(3, 5)\n",
+ "b = np.arange(5)\n",
+ "c = a + b"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example1/right.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "44a9ad96-674a-49e5-94ee-9d84f386ecbc",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy\n",
+ "\n",
+ "a = np.arange(15).reshape(3, 5)\n",
+ "b = np.array([1, 3, 5, 4, 2])\n",
+ "c = a + b\n",
+ "\n",
+ "d = a - b"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example10/center.ipynb

@@ -0,0 +1,56 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "eabfe4e0-d646-4d09-95a4-09ee3d030db6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "def gaussian(x, a, b, c):\n",
+ " #calculate a gaussian\n",
+ " return a * np.exp(-b * (x-c)**2)\n",
+ "\n",
+ "def sinus ():\n",
+ " # Here you can see a sinus function\n",
+ " nx = 100\n",
+ " x = np.linspace(-5.0, 5.0, nx)\n",
+ " y = np.sin(x)\n",
+ " return x, y\n",
+ "\n",
+ "def noisy_gaussian():\n",
+ " # gaussian array y in interval -5 <= x <= 5\n",
+ " nx = 100\n",
+ " x = np.linspace(-5.0, 5.0, nx)\n",
+ " y = gaussian(x, a=2.0, b=0.5, c=1.5)\n",
+ " noise = np.random.normal(0.0, 0.2, nx)\n",
+ " y += noise\n",
+ " return x, y"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example10/left.ipynb

@@ -0,0 +1,53 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2d47bfe2-d91d-4f72-9426-1885c4edb5a9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "%matplotlib inline\n",
+ "%this is a comment\n",
+ "% more more comments\n",
+ "\n",
+ "def gaussian(x, a, b, c):\n",
+ " return a * np.exp(-b * (x-c)**2)\n",
+ " % here a comment\n",
+ " % second line of comment\n",
+ "\n",
+ "def noisy_gaussian():\n",
+ " # gaussian array y in interval -5 <= x <= 5\n",
+ " nx = 100\n",
+ " x = np.linspace(-5.0, 5.0, nx)\n",
+ " y = gaussian(x, a=2.0, b=0.5, c=1.5)\n",
+ " noise = np.random.normal(0.0, 0.2, nx)\n",
+ " y += noise\n",
+ " return x, y"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example10/right.ipynb

@@ -0,0 +1,50 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ff160690-22c8-48f3-9b89-d78a8997baec",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "def gaussian(x, a, b, c):\n",
+ " return a * np.exp(-b * (x-c)**2)\n",
+ "\n",
+ "def noisy_gaussian():\n",
+ " # gaussian array y in interval -5 <= x <= 5\n",
+ " nx = 100\n",
+ " x = np.linspace(-5.0, 5.0, nx)\n",
+ " y = gaussian(x, a=2.0, b=0.5, c=1.5)\n",
+ " noise = np.random.normal(0.0, 0.2, nx)\n",
+ " y += noise\n",
+ " # add a line\n",
+ " # add a second line\n",
+ " return x, y"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example2/center.ipynb

@@ -0,0 +1,39 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "eabfe4e0-d646-4d09-95a4-09ee3d030db6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from matplotlib import pyplot as plt\n",
+ "import numpy as np\n",
+ "x = np.arange(0, 2, 0.1)\n",
+ "y1 = np.exp(x)\n",
+ "plt.plot(x, y1, 'b')"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/example2/left.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2d47bfe2-d91d-4f72-9426-1885c4edb5a9",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from matplotlib import pyplot as plt\n",
+ "import numpy as np\n",
+ "x = np.linspace(0, 2, 10)\n",
+ "z = np.exp(x + 2)\n",
+ "plt.plot(x, z, 'c')\n",
+ "# this is an example"
+ ]
+ }
+ ],
+ "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": "3.11.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}