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Change toggle to dropdown admonition

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Sylvain Tricot 2025-07-22 18:25:07 +02:00
parent 8f5dbf6483
commit 7ac82b1cc2
10 changed files with 253 additions and 103 deletions
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32
msspecbook/Activity01/Activity01.ipynb
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@ -208,7 +208,15 @@
"2. Create an ASE *calculator*\n",
"3. Run the simulation\n",
"\n",
"### PED polar scan for Cu(001)"
"### PED polar scan for Cu(001)\n",
"\n",
"download the [cu.py](cu.py \"download\") python script and the [copper.cif](copper.cif \"download\") file. Put those files in the same folder. You can run your first MsSpec calculation by typing in a terminal:\n",
"\n",
"```shell\n",
"$ python cu.py\n",
"```\n",
"\n",
"Here is the content of the script file:"
]
},
{
@ -597,6 +605,8 @@
"Based on the previous *.cif file, create a new cluster without the deepest plane and run the same calculation for the same emitter\n",
"\n",
"```{note}\n",
"Use the `cluster.edit()` method to interactively remove atoms...\n",
"\n",
"As the cluster will contain fewer atoms, the emitter index will be different\n",
"```\n",
"\n",
@ -617,7 +627,9 @@
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{figure-md} Cu-4planes3planes\n",
"<img src=\"fig2.png\" width=\"600px\" align=\"center\">\n",
@ -913,20 +925,6 @@
"Cu(2p) polar scan for the hemispherical cluster.\n",
":::"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e86ab1b3-fcf3-46e7-9cc7-f5e80becea9d",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"outputs": [],
"source": []
}
],
"metadata": {
@ -945,7 +943,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.13"
"version": "3.11.3"
}
},
"nbformat": 4,

8
msspecbook/Activity02/Activity02.ipynb
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@ -42,7 +42,7 @@
"\n",
"### Building the cluster\n",
"\n",
"Let's start by building the cluster"
"Let's start by building the cluster. You can copy/paste directly the code from this page to your text editor or you can download the script [SbAg.py](SbAg.py \"download\"). You will also need the [data.txt](data.txt \"download\") file."
]
},
{
@ -1164,7 +1164,9 @@
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{figure-md} SbAg-fig2\n",
"<img src=\"fig2.png\" width=\"600px\" align=\"center\">\n",
@ -1200,7 +1202,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.13"
"version": "3.11.3"
}
},
"nbformat": 4,

14
msspecbook/Activity03/Activity03.ipynb
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@ -62,7 +62,7 @@
"::::{tab-set}\n",
"\n",
":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
"By using the `Atoms` class of the `ase` package, try to build a O-Rh chain where atoms are 4 Å apart. Here is the begining of the script. Try to complete the line of code and view your two-atoms chain.\n",
"By using the [`Atoms`](https://wiki.fysik.dtu.dk/ase/ase/atoms.html#ase.Atoms) class of the `ase` package, try to build a O-Rh chain where atoms are 4 Å apart. Here is the begining of the script. Try to complete the line of code and view your two-atoms chain.\n",
"\n",
"```python\n",
"from ase import Atoms\n",
@ -266,7 +266,9 @@
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{literalinclude} RhO_sf.py\n",
":start-at: Compute\n",
@ -333,7 +335,7 @@
"::::{tab-set}\n",
"\n",
":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
"Complete the script below to compute the ($\\theta,\\phi$) scan of the photodiffraction of O(1s) adsorbed on a *fcc* site on Rh(111) surface.\n",
"Complete the [script below](RhO_tofill.py \"download\") to compute the ($\\theta,\\phi$) scan of the photodiffraction of O(1s) adsorbed on a *fcc* site on Rh(111) surface.\n",
"\n",
"```{literalinclude} RhO_tofill.py\n",
":lineno-match:\n",
@ -358,7 +360,9 @@
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{literalinclude} RhO_completed.py\n",
":lineno-match:\n",
@ -409,7 +413,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.13"
"version": "3.11.3"
}
},
"nbformat": 4,

20
msspecbook/Activity04/Activity04.ipynb
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@ -97,7 +97,13 @@
{
"cell_type": "markdown",
"id": "3ed73f46-c12f-452f-a584-00d142f2e133",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{admonition} *Solution...*\n",
":class: tip\n",
@ -136,7 +142,13 @@
{
"cell_type": "markdown",
"id": "626708d9-c421-4bf0-bd70-f32113360f9c",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{admonition} *Solution...*\n",
":class: tip\n",
@ -150,6 +162,10 @@
"Polar scan of a Ni chain of 2-5 atoms for single and full mutliple scattering.\n",
":::\n",
"\n",
":::{literalinclude} Ni_chain2.py\n",
":linenos: true\n",
":::\n",
"\n",
"```"
]
}

90
msspecbook/Activity05/Activity05.ipynb
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@ -181,12 +181,12 @@
"::::{tab-set}\n",
"\n",
":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
"Complete the code snipet provided below to create a small TiSe{sub}`2` cluster with Ti emitter in the 2{sup}`nd` plane:\n",
"Complete the code snipet provided below (or [here](TiSe2_1_tofill.py \"download\")) to create a small TiSe{sub}`2` cluster with Ti emitter in the 2{sup}`nd` plane:\n",
"\n",
"```{literalinclude} TiSe2_1_tofill.py\n",
":start-at: from\n",
":end-before: Create a calculator\n",
":lineno-match:\n",
":lines: 1-29\n",
":linenos:\n",
":emphasize-lines: 7,11,15,26 \n",
"```\n",
"\n",
":::\n",
@ -195,53 +195,32 @@
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "b65b569e-242b-4fe9-9c87-ea90d80d9b44",
"cell_type": "markdown",
"id": "1f2e014f-8963-4ae6-bbf5-7f4ebde3b16a",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": [
"hide-cell"
]
"tags": []
},
"outputs": [],
"source": [
"from ase.build import mx2\n",
"from ase.visualize import view\n",
"from msspec.calculator import MSSPEC\n",
"from msspec.utils import hemispherical_cluster, get_atom_index\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
"# Some usefull constants (a, c, d, D) for defining the structure\n",
"a=3.535;c=6.004;d=3.450;D=2.554\n",
":::{literalinclude} TiSe2_1_completed.py\n",
":linenos: true\n",
":lines: 1-18\n",
":::\n",
"\n",
"# Create the TiSe2 trilayer\n",
"# use ase help for this function\n",
"TiSe2 = mx2(formula='TiSe2', kind='1T', a=a, thickness=d, size=(1, 1, 1), vacuum=None)\n",
"\n",
"# The preious cell is 2D, let's define the c-axis to take into account \n",
"# the Van der Waals gap between trilayers\n",
"TiSe2.cell[2] = [0, 0, c]\n",
"\n",
"# To be aligned like in the paper\n",
"TiSe2.rotate(60, 'z', rotate_cell=True)\n",
"\n",
"# Since the material is multi-elements, \"tag\" each inequivalent atom \n",
"# of the unit cell with a number. The \"Ti\" atom is tagged 0 and \"Se\" \n",
"# atoms are 1 and 2.\n",
"for i in range(3): \n",
" TiSe2[i].tag = i\n",
"\n",
"cluster = hemispherical_cluster(TiSe2, emitter_tag=0, emitter_plane=1, planes=5)\n",
"cluster.emitter = get_atom_index(cluster, 0, 0, 0)"
"```"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "515064d0-3751-4fae-af0c-c4b15ea221b3",
"execution_count": 1,
"id": "b65b569e-242b-4fe9-9c87-ea90d80d9b44",
"metadata": {
"editable": true,
"slideshow": {
@ -777,12 +756,39 @@
"<IPython.core.display.HTML object>"
]
},
"execution_count": 15,
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from ase.build import mx2\n",
"from ase.visualize import view\n",
"from msspec.calculator import MSSPEC\n",
"from msspec.utils import hemispherical_cluster, get_atom_index\n",
"\n",
"# Some usefull constants (a, c, d, D) for defining the structure\n",
"a=3.535;c=6.004;d=3.450;D=2.554\n",
"\n",
"# Create the TiSe2 trilayer\n",
"# use ase help for this function\n",
"TiSe2 = mx2(formula='TiSe2', kind='1T', a=a, thickness=d, size=(1, 1, 1), vacuum=None)\n",
"\n",
"# The preious cell is 2D, let's define the c-axis to take into account \n",
"# the Van der Waals gap between trilayers\n",
"TiSe2.cell[2] = [0, 0, c]\n",
"\n",
"# To be aligned like in the paper\n",
"TiSe2.rotate(60, 'z', rotate_cell=True)\n",
"\n",
"# Since the material is multi-elements, \"tag\" each inequivalent atom \n",
"# of the unit cell with a number. The \"Ti\" atom is tagged 0 and \"Se\" \n",
"# atoms are 1 and 2.\n",
"for i in range(3): \n",
" TiSe2[i].tag = i\n",
"\n",
"cluster = hemispherical_cluster(TiSe2, emitter_tag=0, emitter_plane=1, planes=5)\n",
"cluster.emitter = get_atom_index(cluster, 0, 0, 0)\n",
"view(cluster, viewer='x3d')"
]
},
@ -847,7 +853,9 @@
]
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{figure-md} results-completed-fig\n",
"<img src=\"results_completed.jpg\" width=\"400px\" align=\"center\">\n",
@ -878,7 +886,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.13"
"version": "3.11.3"
}
},
"nbformat": 4,

16
msspecbook/Activity06/Activity06.ipynb
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@ -3,7 +3,13 @@
{
"cell_type": "markdown",
"id": "c0a860db-0f72-4785-81f4-831e48b3a49f",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"# Activity 6: Effect of the temperature\n",
"\n",
@ -73,7 +79,7 @@
"\n",
":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
"With the help of the [MsSpec documentation](https://msspec.cnrs.fr/parameters.html) and the second paragraph p6791 of the [article cited above](#msd-paper),\n",
"complete the hilighted lines in the following script to compute the anisotropy of Cu(2p) $\\phi$-scans for polar angle $\\theta$=45° and 83°.\n",
"complete the hilighted lines in the [following script](Cu_temperature.py \"download\") to compute the anisotropy of Cu(2p) $\\phi$-scans for polar angle $\\theta$=45° and 83°.\n",
"\n",
"How is varying the anisotropy versus the temperature. How can you qualitatively explain this variation ?\n",
"\n",
@ -98,7 +104,9 @@
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{literalinclude} Cu_temperature_completed.py\n",
":lineno-match:\n",
@ -133,7 +141,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.13"
"version": "3.11.3"
}
},
"nbformat": 4,

57
msspecbook/Activity07/Activity07.ipynb
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@ -3,7 +3,13 @@
{
"cell_type": "markdown",
"id": "42cfa8b1-20d2-47e4-a1f0-161c4517df2c",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"(path-filtering)=\n",
"# Activity 7: Large clusters and path filtering"
@ -42,7 +48,13 @@
{
"cell_type": "markdown",
"id": "0f78af28-335e-4f6b-9b98-929f9e6965f8",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"::::{tab-set}\n",
"\n",
@ -66,16 +78,24 @@
{
"cell_type": "markdown",
"id": "a83ee1b8-dc25-4db9-a3bd-c5ba8443f758",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
":::{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
"To get the total number of paths generated by a cluster of $N$ atoms up to order $M$, use the following formula:\n",
"\n",
"```{math}\n",
":::{math}\n",
":label: eq-nbpaths\n",
"\\sum_{i=0}^{i=M} (N-1)^i\n",
"```\n",
":::\n",
"\n",
":::{figure-md} nbpaths-fig\n",
"<img src=\"fig1.jpg\" alt=\"path filtering\" width=\"600px\" align=\"center\">\n",
@ -83,7 +103,7 @@
"The time for computing all scattering path for increasing cluster size and scattering order (up to 6{sup}`th` order with 739 atoms. (One path is assumed to be calculated within 1 µs)\n",
":::\n",
"\n",
":::"
"```"
]
},
{
@ -110,7 +130,13 @@
{
"cell_type": "markdown",
"id": "28aae2f7-2af9-4630-b89d-ab634725ad79",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"## Application to a deep plane in a Si(001) sample\n",
"\n",
@ -129,7 +155,7 @@
"\n",
":::{tab-item} <i class=\"fa-solid fa-circle-question\"></i> Quiz\n",
"\n",
"The following script is almost completed, try to define path filtering options (no backscattering, accept all paths with forward angles < 40° and reject paths longer than the diameter of the cluster).\n",
"The [following script](Si001.py \"download\") is almost completed, try to define path filtering options (no backscattering, accept all paths with forward angles < 40° and reject paths longer than the diameter of the cluster).\n",
"\n",
"```{literalinclude} Si001.py\n",
":lineno-match:\n",
@ -148,9 +174,18 @@
{
"cell_type": "markdown",
"id": "19fbd486-b0c1-450c-a00d-79984945aefd",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
"The calculation took few seconds and the result is very close to the calculation with all scattering paths.\n",
"\n",
"Only 0.01% of 3{sup}`rd` order paths were actually taken into account\n",

34
msspecbook/Activity08/Activity08.ipynb
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@ -3,7 +3,13 @@
{
"cell_type": "markdown",
"id": "2ff5929f-c066-496f-b078-0bbc2ab49428",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"# Activity 8: Inequivalent emitters and the XPD of a substrate"
]
@ -92,9 +98,17 @@
{
"cell_type": "markdown",
"id": "8a3a48ef-196f-435a-b342-3a73e62160f8",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
":::{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{figure-md} AlN-fig3\n",
"<img src=\"AlN-fig3.jpg\" alt=\"AlN number of clusters\" width=\"600px\" align=\"center\">\n",
@ -102,7 +116,7 @@
"Number of different clusters to build for Al(2p) and N(1s) in 3 planes\n",
":::\n",
"\n",
":::"
"```"
]
},
{
@ -123,9 +137,17 @@
{
"cell_type": "markdown",
"id": "abc64fdb-5895-4112-a987-66b3420d78eb",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{figure-md} AlN-fig4\n",
"<img src=\"AlN-fig4.png\" alt=\"AlN results\" width=\"600px\" align=\"center\">\n",

54
msspecbook/Activity09/Activity09.ipynb
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@ -4,7 +4,13 @@
"attachments": {},
"cell_type": "markdown",
"id": "aa43e0e7-0c18-4750-9e2b-3a48f106d2ca",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"(RFactor)=\n",
"# Activity 9: Comparing simulation and experiment with R-factors\n",
@ -33,7 +39,13 @@
{
"cell_type": "markdown",
"id": "91c03801-b46b-4844-8c89-655700419063",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"::::{tab-set}\n",
"\n",
@ -61,9 +73,18 @@
{
"cell_type": "markdown",
"id": "d1be5047-fb75-4e98-a6a2-fc6f678e68ff",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
"Here is the code of the `create_cluster` function\n",
"\n",
":::{literalinclude} COFe_completed.py\n",
@ -98,9 +119,18 @@
{
"cell_type": "markdown",
"id": "670cbd24-efd4-4c51-89e2-f1d96c53908d",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
"Here are the code of the nested *for loops*\n",
"\n",
":::{literalinclude} COFe_completed.py\n",
@ -144,9 +174,17 @@
{
"cell_type": "markdown",
"id": "aa8d2dc4-286a-441d-9c21-dab6bac8145c",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
"6 R-factors out of 12 do agree that *variable set n°30* gives the best agreement. The set n°30 corresponds to\n",
"$\\theta=55°$ and $\\phi=0°$.\n",

31
msspecbook/Activity10/Activity10.ipynb
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@ -3,7 +3,13 @@
{
"cell_type": "markdown",
"id": "38d3e621-e866-43e1-9c92-f473d1e755c0",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"# Activity 10: Parallelization and multi-processing in MsSpec"
]
@ -11,7 +17,13 @@
{
"cell_type": "markdown",
"id": "1dccb5e3-1cd3-4732-a7ba-81a8a94c89dc",
"metadata": {},
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"As you can see from the previous examples, a complete simulation may require several multiple scattering calculations, for instance to calculate the total intensity of a substrate or to optimize the geometry of a system. As the calculations are often time consuming, it can be useful to distribute these tasks over several processors to make the most of hardware resources.\n",
"Although MsSpec is not fully parallelized, the code does offer a number of features, which we will explore here.\n",
@ -67,10 +79,18 @@
},
{
"cell_type": "markdown",
"id": "0a1fabce-c42d-4cb4-9720-bcd21ff0cd09",
"metadata": {},
"id": "3833a4c3-2d47-49e8-b78d-5c97dad47716",
"metadata": {
"editable": true,
"slideshow": {
"slide_type": ""
},
"tags": []
},
"source": [
"```{toggle}\n",
"```{admonition} *Solution...*\n",
":class: tip\n",
":class: dropdown\n",
"\n",
":::{literalinclude} COFe_mp_completed.py\n",
":lineno-start: 63\n",
@ -79,7 +99,6 @@
":emphasize-lines: 6,7, 9,10, 18\n",
":::\n",
"\n",
"\n",
"```"
]
}