save_xps module to save XPS data in two column format (#9)

* save_xps to save XPS data in two column format

* Update __init__.py

* Update glossary.md

* Update xps.md

* Update xps.md

* Update xps.md

* Update save_xps.py

* Add files via upload

* Update xps.md

* Update xps.md

__init__.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 """
 Purpose: Python libraries for ARPES data analysis
-Version: 20210821
+Version: 20220325
 @author: Pranab Das (GitHub: @pranabdas)
 """
 from arpespythontools.src.crop_2d import crop_2d
@@ -18,3 +18,4 @@
 from arpespythontools.src.plane_slice import plane_slice
 from arpespythontools.src.rotate_2d import rotate_2d
 from arpespythontools.src.rotate_3d import rotate_3d
+from arpespythontools.src.save_xps import save_xps

docs/glossary.md

@@ -220,6 +220,23 @@ URL address.
 - `energy` : 1D vector (numpy ndarry) of kinetic energy values in eV.
 
 
+## plane_slice
+
+```python
+surf = arp.plane_slice(data, x, x_min, x_max)
+```
+Returns the 2D slice along the first dimension of `data` and integrated in the
+width [x_min, x_max].
+
+**Inputs:**
+- `data` : 3D matrix.
+- `x` : axes scaling along the first dimension.
+- `x_min`, `x_max` : integration bounds.
+
+**Outputs:**
+- `surf` : 2D array.
+
+
 ## rotate_2d
 
 ```python
@@ -264,18 +281,16 @@ set to `NaN` (not a number).
 - `phi_r` : 1D array of axis scaling along the third dimension of `data_r`.
 
 
-## slice_plane
+## save_xps
 
 ```python
-surf = arp.slice_plane(data, x, x_min, x_max)
+arp.save_xps(energy, intensity, "xps_data.x_y")
 ```
-Returns the 2D slice along the first dimension of `data` and integrated in the
-width [x_min, x_max].
+Save XPS energy and intensity in two column plaintext file.
 
 **Inputs:**
-- `data` : 3D matrix.
-- `x` : axes scaling along the first dimension.
-- `x_min`, `x_max` : integration bounds.
+- `energy` : one dimensional vector
+- `intensity` : one dimensional vector
+- `filename` : string value corresponding to filename.
 
-**Outputs:**
-- `surf` : 2D array.
+No output is returned, only the data file is saved at specified filename.

docs/xps.md

@@ -20,17 +20,21 @@ import numpy as np
 
 data, energy, angle = arp.load("xps_data.txt")
 intensity = arp.line_profile(data, angle, -2.5, 2.5)
+```
 
-# energy is in terms of kinetic energy (eV)
-# if you need in terms of binding energy:
-# e_bin = fermi_energy - e_kin
+If you require energy in terms of binding energy instead of kinetic energy, you
+can convert using:
 
-xps_data = np.array([energy, intensity]).T
-np.savetxt("xps_data.x_y", xps_data)
-```
+$$
+E_{bin} = E_F - E_{kin}
+$$
 
-In the above example, we have saved the data in two column (`.x_y`) format,
-which is suitable for importing to other XPS analysis software (like CasaXPS).
+$$
+E_F = h\nu - W_{\phi}
+$$
+
+where $E_F$ is Fermi energy, and $W_{\phi}$ is work function which is about 4.5
+eV for our setup.
 
 :::tip
 
@@ -43,3 +47,24 @@ intensity = np.sum(data, axis=1)
 ```
 
 :::
+
+### Save/export XPS data
+
+```python
+xps_data = np.array([energy, intensity]).T
+np.savetxt("xps_data.x_y", xps_data)
+```
+
+In the above example, we have saved the data in two column (`.x_y`) format,
+which is suitable for importing to other XPS analysis software (like CasaXPS).
+
+We may also use the module `save_xps` to save data.
+
+```python
+arp.save_xps(energy, intensity, "xps_data.x_y")
+```
+
+If you need to load the two column data using python:
+```python
+energy, intensity = np.loadtxt("xps_data.x_y", unpack=True)
+```

package.json

@@ -1,7 +1,7 @@
 {
   "homepage": ".",
   "name": "arpespythontools",
-  "version": "0.2.1",
+  "version": "0.3.0",
   "private": true,
   "scripts": {
     "docusaurus": "docusaurus",

src/save_xps.py

@@ -0,0 +1,22 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Program: Save XPS data in two column format
+Version: 20220325
+@author: Pranab Das (GitHub: @pranabdas)
+"""
+
+
+def save_xps(energy, intensity, filename=""):
+    import numpy as np
+    import datetime
+
+    if (filename == ""):
+        filename = "XPS_data_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S") + ".x_y"
+
+    # check energy and intensity have same length
+    if (len(energy) != len(intensity)):
+        raise ValueError("Lengths of input arrays do not match")
+    else:
+        data = np.array([energy, intensity]).T
+        np.savetxt(filename, data)