.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/plot_gr_hv_scan.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_gr_hv_scan.py: Graphene hv scan ================ Simple workflow for analyzing a photon energy scan data of graphene as simulated from a third nearest neighbor tight binding model. The same workflow can be applied to any photon energy scan. .. GENERATED FROM PYTHON SOURCE LINES 12-13 Import the "fundamental" python libraries for a generic data analysis: .. GENERATED FROM PYTHON SOURCE LINES 13-17 .. code-block:: default import numpy as np import matplotlib.pyplot as plt .. GENERATED FROM PYTHON SOURCE LINES 18-19 Instead of loading the file as for example: .. GENERATED FROM PYTHON SOURCE LINES 19-24 .. code-block:: default # from navarp.utils import navfile # file_name = r"nxarpes_simulated_cone.nxs" # entry = navfile.load(file_name) .. GENERATED FROM PYTHON SOURCE LINES 25-27 Here we build the simulated graphene signal with a dedicated function defined just for this purpose: .. GENERATED FROM PYTHON SOURCE LINES 27-36 .. code-block:: default from navarp.extras.simulation import get_tbgraphene_hv entry = get_tbgraphene_hv( scans=np.arange(90, 150, 2), angles=np.linspace(-7, 7, 300), ebins=np.linspace(-3.3, 0.4, 450), tht_an=-18, ) .. GENERATED FROM PYTHON SOURCE LINES 37-41 Plot a single analyzer image at scan = 90 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ First I have to extract the isoscan from the entry, so I use the isoscan method of entry: .. GENERATED FROM PYTHON SOURCE LINES 41-43 .. code-block:: default iso0 = entry.isoscan(scan=90) .. GENERATED FROM PYTHON SOURCE LINES 44-45 Then to plot it using the 'show' method of the extracted iso0: .. GENERATED FROM PYTHON SOURCE LINES 45-47 .. code-block:: default iso0.show(yname='ekin') .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_001.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 48-49 Or by string concatenation, directly as: .. GENERATED FROM PYTHON SOURCE LINES 49-51 .. code-block:: default entry.isoscan(scan=90).show(yname='ekin') .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_002.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_002.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 52-60 Fermi level determination ^^^^^^^^^^^^^^^^^^^^^^^^^ The initial guess for the binding energy is: ebins = ekins - (hv - work_fun). However, the better way is to proper set the Fermi level first and then derives everything form it. In this case the Fermi level kinetic energy is changing along the scan since it is a photon energy scan. So to set the Fermi level I have to give an array of values corresponding to each photon energy. By definition I can give: .. GENERATED FROM PYTHON SOURCE LINES 60-64 .. code-block:: default efermis = entry.hv - entry.analyzer.work_fun entry.set_efermi(efermis) .. GENERATED FROM PYTHON SOURCE LINES 65-69 Or I can use a method for its detection, but in this case, it is important to give a proper energy range for each photon energy. For example for each photon a good range is within 0.4 eV around the photon energy minus the analyzer work function: .. GENERATED FROM PYTHON SOURCE LINES 69-76 .. code-block:: default energy_range = ( (entry.hv[:, None] - entry.analyzer.work_fun) + np.array([-0.4, 0.4])[None, :]) entry.autoset_efermi(energy_range=energy_range) .. rst-class:: sphx-glr-script-out Out: .. code-block:: none scan(eV) efermi(eV) FWHM(meV) new hv(eV) 90.0000 85.4000 58.8 90.0000 92.0000 87.4003 58.6 92.0003 94.0000 89.4002 58.1 94.0002 96.0000 91.4002 58.7 96.0002 98.0000 93.4000 59.2 98.0000 100.0000 95.4003 58.4 100.0003 102.0000 97.4006 58.3 102.0006 104.0000 99.4010 56.6 104.0010 106.0000 101.3999 59.4 105.9999 108.0000 103.4004 58.7 108.0004 110.0000 105.4006 57.6 110.0006 112.0000 107.4003 58.5 112.0003 114.0000 109.4003 60.6 114.0003 116.0000 111.3999 59.3 115.9999 118.0000 113.3998 60.0 117.9998 120.0000 115.4002 59.4 120.0002 122.0000 117.4005 58.2 122.0005 124.0000 119.4002 59.3 124.0002 126.0000 121.4009 58.6 126.0009 128.0000 123.4005 58.1 128.0005 130.0000 125.4001 59.4 130.0001 132.0000 127.4006 57.4 132.0006 134.0000 129.4000 59.7 134.0000 136.0000 131.4003 58.2 136.0003 138.0000 133.3999 58.9 137.9999 140.0000 135.4004 58.6 140.0004 142.0000 137.3998 58.7 141.9998 144.0000 139.4003 60.1 144.0003 146.0000 141.4002 59.3 146.0002 148.0000 143.4004 59.1 148.0004 .. GENERATED FROM PYTHON SOURCE LINES 77-80 In both cases the binding energy and the photon energy will be updated consistently. Note that the work function depends on the beamline or laboratory. If not specified is 4.5 eV. .. GENERATED FROM PYTHON SOURCE LINES 82-84 To check the Fermi level detection I can have a look on each photon energy. Here I show only the first 10 photon energies: .. GENERATED FROM PYTHON SOURCE LINES 84-93 .. code-block:: default for scan_i in range(10): print("hv = {} eV, E_F = {:.0f} eV, Res = {:.0f} meV".format( entry.hv[scan_i], entry.efermi[scan_i], entry.efermi_fwhm[scan_i]*1000 )) entry.plt_efermi_fit(scan_i=scan_i) .. rst-class:: sphx-glr-horizontal * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_003.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_003.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_004.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_004.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_005.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_005.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_006.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_006.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_007.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_007.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_008.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_008.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_009.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_009.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_010.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_010.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_011.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_011.png :class: sphx-glr-multi-img * .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_012.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_012.png :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none hv = 90.0000026322631 eV, E_F = 85 eV, Res = 59 meV hv = 92.00034396834147 eV, E_F = 87 eV, Res = 59 meV hv = 94.00020052850076 eV, E_F = 89 eV, Res = 58 meV hv = 96.0002071725171 eV, E_F = 91 eV, Res = 59 meV hv = 97.99996511943282 eV, E_F = 93 eV, Res = 59 meV hv = 100.00033060955292 eV, E_F = 95 eV, Res = 58 meV hv = 102.00057713915359 eV, E_F = 97 eV, Res = 58 meV hv = 104.00101948382944 eV, E_F = 99 eV, Res = 57 meV hv = 105.99986522692515 eV, E_F = 101 eV, Res = 59 meV hv = 108.0004287342628 eV, E_F = 103 eV, Res = 59 meV .. GENERATED FROM PYTHON SOURCE LINES 94-96 Plot a single analyzer image at scan = 110 with the Fermi level aligned ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. GENERATED FROM PYTHON SOURCE LINES 96-99 .. code-block:: default entry.isoscan(scan=110).show(yname='eef') .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_013.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_013.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 100-102 Plotting iso-energetic cut at ekin = efermi ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. GENERATED FROM PYTHON SOURCE LINES 102-105 .. code-block:: default entry.isoenergy(0).show() .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_014.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_014.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 106-113 Plotting in the reciprocal space (k-space) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ I have to define first the reference point to be used for the transformation. Meaning a point in the angular space which I know it correspond to a particular point in the k-space. In this case the graphene Dirac-point is for hv = 120 is at ekin = 114.3 eV and tht_p = -0.6 (see the figure below), which in the k-space has to correspond to kx = 1.7. .. GENERATED FROM PYTHON SOURCE LINES 113-133 .. code-block:: default hv_p = 120 entry.isoscan(scan=hv_p, dscan=0).show(yname='ekin', cmap='cividis') tht_p = -0.6 e_kin_p = 114.3 plt.axvline(tht_p, color='w') plt.axhline(e_kin_p, color='w') entry.set_kspace( tht_p=tht_p, k_along_slit_p=1.7, scan_p=0, ks_p=0, e_kin_p=e_kin_p, inn_pot=14, p_hv=True, hv_p=hv_p, ) .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_015.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_015.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none tht_an = -18.040 scan_type = hv inn_pot = 14.000 phi_an = 0.000 k_perp_slit_for_kz = 0.000 kspace transformation ready .. GENERATED FROM PYTHON SOURCE LINES 134-136 Once it is set, all the isoscan or iscoenergy extracted from the entry will now get their proper k-space scales: .. GENERATED FROM PYTHON SOURCE LINES 136-139 .. code-block:: default entry.isoscan(120).show() .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_016.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_016.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 140-141 sphinx_gallery_thumbnail_number = 17 .. GENERATED FROM PYTHON SOURCE LINES 141-143 .. code-block:: default entry.isoenergy(0).show(cmap='cividis') .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_017.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_017.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 144-145 I can also place together in a single figure different images: .. GENERATED FROM PYTHON SOURCE LINES 145-153 .. code-block:: default fig, axs = plt.subplots(1, 2) entry.isoscan(120).show(ax=axs[0]) entry.isoenergy(-0.9).show(ax=axs[1]) plt.tight_layout() .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_018.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_018.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 154-156 Many other options: ^^^^^^^^^^^^^^^^^^^ .. GENERATED FROM PYTHON SOURCE LINES 156-205 .. code-block:: default fig, axs = plt.subplots(2, 2) scan = 110 dscan = 0 ebin = -0.9 debin = 0.01 entry.isoscan(scan, dscan).show(ax=axs[0][0], xname='tht', yname='ekin') entry.isoscan(scan, dscan).show(ax=axs[0][1], cmap='binary') axs[0][1].axhline(ebin-debin) axs[0][1].axhline(ebin+debin) entry.isoenergy(ebin, debin).show( ax=axs[1][0], xname='tht', yname='phi', cmap='cividis') entry.isoenergy(ebin, debin).show( ax=axs[1][1], cmap='magma', cmapscale='log') axs[1][0].axhline(scan, color='w', ls='--') axs[0][1].axvline(1.7, color='r', ls='--') axs[1][1].axvline(1.7, color='r', ls='--') x_note = 0.05 y_note = 0.98 for ax in axs[0][:]: ax.annotate( "$scan \: = \: {} eV$".format(scan, dscan), (x_note, y_note), xycoords='axes fraction', size=8, rotation=0, ha="left", va="top", bbox=dict( boxstyle="round", fc='w', alpha=0.65, edgecolor='None', pad=0.05 ) ) for ax in axs[1][:]: ax.annotate( "$E-E_F \: = \: {} \pm {} \; eV$".format(ebin, debin), (x_note, y_note), xycoords='axes fraction', size=8, rotation=0, ha="left", va="top", bbox=dict( boxstyle="round", fc='w', alpha=0.65, edgecolor='None', pad=0.05 ) ) plt.tight_layout() .. image-sg:: /auto_examples/images/sphx_glr_plot_gr_hv_scan_019.png :alt: plot gr hv scan :srcset: /auto_examples/images/sphx_glr_plot_gr_hv_scan_019.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 7.404 seconds) .. _sphx_glr_download_auto_examples_plot_gr_hv_scan.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_gr_hv_scan.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_gr_hv_scan.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_