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add Dirac GOS for EELS quantification #8

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add Dirac GOS for EELS quantification #8

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75 changes: 73 additions & 2 deletions EELS/EELS_analysis.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@
"* 20/7/2019 Katherine MacArthur - Checked for Hyperspy 1.5.1 and commented out sections requiring Gatan GOS files.\n",
"* 30/7/2019 Magnus Nord - Minor text improvements for M&M19 short course\n",
"* 9/3/2024 Magnus Nord - Updated to work with HyperSpy 2.0.0\n",
"* 23/8/2024 Zezhong Zhang - Add Dirac GOS example in curve fitting quantification\n",
"\n",
"## Table of contents\n",
"\n",
Expand Down Expand Up @@ -753,6 +754,76 @@
"hs.plot.plot_spectra([m[edge].intensity.as_signal() for edge in edges], legend=edges)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By default, exspy uses the [DFT GOS](https://zenodo.org/records/7645765) based on the Schrödinger equation. As alternative, we can also use the [Dirac GOS](https://zenodo.org/records/12800856) to include the relativistic effects, as described in this [arxiv paper](https://arxiv.org/pdf/2405.10151). The switch of the GOS is simply done by assigning the `GOS` parameter when creating the model."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"m_dirac = s.create_model(low_loss=s_ll, GOS='dirac')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can plot the difference between the two GOS models for each edge, where the solid lines are Dirac results and dashed lines are DFT results. "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.figure()\n",
"edges = (\"Ti_L3\", \"Mn_L3\", \"O_K\", \"La_M5\")\n",
"color_list = [\"r\", \"g\", \"b\", \"k\"]\n",
"for edge in edges:\n",
" color = color_list.pop()\n",
" plt.plot(m_dirac[edge].GOS.energy_axis, m_dirac[edge].GOS.qint, label=edge + \" (Dirac)\", color=color)\n",
" plt.plot(m[edge].GOS.energy_axis, m[edge].GOS.qint, label=edge + \" (DFT)\", color=color, linestyle=\"--\")\n",
"plt.xlim(400, 1000)\n",
"plt.legend()\n",
"plt.show()\n",
"plt.xlabel(\"Energy loss (eV)\")\n",
"plt.ylabel(\"Scattering cross-section (barn/eV)\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also compare the quantification line profiles:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"m_dirac.components.O_K.onset_energy.value = 528\n",
"m_dirac.components.O_K.onset_energy.assign_current_value_to_all()\n",
"m_dirac.components.Mn_L3.onset_energy.value\n",
"m_dirac.components.Mn_L3.onset_energy.value = 638.5\n",
"m_dirac.components.Mn_L3.onset_energy.assign_current_value_to_all()\n",
"m_dirac.enable_fine_structure()\n",
"m_dirac.multifit(kind='smart')\n",
"edges = (\"Ti_L3\", \"Mn_L3\", \"O_K\", \"La_M5\")\n",
"linestyle_list = ['-']* len(edges) + ['--']* len(edges)\n",
"color_list = ['r', 'g', 'b', 'k']*2\n",
"hs.plot.plot_spectra([m_dirac[edge].intensity.as_signal() for edge in edges] + [m[edge].intensity.as_signal() for edge in edges], legend=edges, linestyle=linestyle_list, color=color_list)"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down Expand Up @@ -1024,7 +1095,7 @@
},
"outputs": [],
"source": [
"m = s.create_model(low_loss=s_ll, auto_background=False)"
"m = s.create_model(low_loss=s_ll, auto_background=False, GOS='dirac')"
]
},
{
Expand Down Expand Up @@ -1506,7 +1577,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.11.9"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
Expand Down
32 changes: 30 additions & 2 deletions EELS/EELS_elemental_mapping.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,8 @@
"\n",
"* 2017/09/27: Initial version by Ida Hjorth\n",
"* 2019/11/14: Update to HyperSpy 1.5, and minor improvements to text by Magnus Nord\n",
"* 2024/3/16: Update to work with HyperSpy 2.0, by Magnus Nord"
"* 2024/3/16: Update to work with HyperSpy 2.0, by Magnus Nord\n",
"* 23/8/2024 Zezhong Zhang - Add Dirac GOS example in mapping"
]
},
{
Expand Down Expand Up @@ -438,6 +439,33 @@
"Cu_map.save(\"Cu_map.jpg\", scalebar=True, output_size=500)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By default, exspy utilizes the [DFT GOS](https://zenodo.org/records/7645765), which is based on the Schrödinger equation. However, if you need to account for relativistic effects, you can switch to the [Dirac GOS](https://zenodo.org/records/12800856), as detailed in this [arxiv paper](https://arxiv.org/pdf/2405.10151). Changing the GOS is straightforward; you can do this by setting the GOS parameter when creating the model."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"m_dirac = s_eels.create_model(GOS='dirac')\n",
"m.fit_component(m.components.PowerLaw, signal_range=(700, 900), only_current=False)\n",
"m_dirac.fit_component(m_dirac.components.Cu_L3, signal_range=(950, 1000), only_current=False)\n",
"m_dirac.fit_component(m_dirac.components.Zn_L3, signal_range=(1050, 1150), only_current=False)\n",
"m_dirac.set_all_edges_intensities_positive()\n",
"m_dirac.multifit()\n",
"Zn_map_dirac = m_dirac.components.Zn_L3.intensity.as_signal()\n",
"Cu_map_dirac = m_dirac.components.Cu_L3.intensity.as_signal()\n",
"hs.plot.plot_images([Zn_map_dirac, Cu_map_dirac])\n",
"plt.savefig(\"Zn_Cu_elemental_maps_dirac.png\")\n",
"hs.plot.plot_images([Zn_map_dirac, Cu_map_dirac], overlay=True, label=[\"Zn\", \"Cu\"], axes_decor=\"off\")\n",
"plt.savefig(\"Zn_Cu_elemental_maps_overlay_dirac.png\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down Expand Up @@ -518,7 +546,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.11.9"
}
},
"nbformat": 4,
Expand Down
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