XPS: Scale Experimental Data Instead of Simulated Data

Changes the logic for the intensity scaling feature of PR aiidalab#627
to scale the intensities of the experimental data instead of the
simulated data. This approach is intended to greatly speed up the
response time for the intensity scale widget.

This change also uses `numpy` rather than `pandas` to read the
incoming CSV data, in order to make data manipulation more intuitive.
This change strictly enforces the requirement that the CSV file should
have no header line.

src/aiidalab_qe/plugins/xps/result.py

@@ -30,7 +30,7 @@ def export_xps_data(outputs):
 
 
 def xps_spectra_broadening(
-    points, equivalent_sites_data, gamma=0.3, sigma=0.3, label="", intensity=1.0
+    points, equivalent_sites_data, gamma=0.3, sigma=0.3, label=""
 ):
     """Broadening the XPS spectra with Voigt function and return the spectra data"""
 
@@ -55,7 +55,7 @@ def xps_spectra_broadening(
         )
         for site in point:
             # Weight for the spectra of every atom
-            intensity = equivalent_sites_data[site]["multiplicity"] * intensity
+            intensity = equivalent_sites_data[site]["multiplicity"]
             relative_core_level_position = point[site]
             y = (
                 intensity
@@ -182,7 +182,6 @@ def _update_view(self):
             equivalent_sites_data,
             gamma=gamma.value,
             sigma=sigma.value,
-            intensity=intensity.value,
         )
         # only plot the selected spectrum
         for site, d in spectra[spectrum_select.value].items():
@@ -204,7 +203,6 @@ def response(change):
                 equivalent_sites_data,
                 gamma=gamma.value,
                 sigma=sigma.value,
-                intensity=intensity.value,
             )
 
             for site, d in spectra[spectrum_select.value].items():
@@ -232,13 +230,26 @@ def response(change):
                         )
                 self.g.layout.barmode = "overlay"
                 self.g.layout.xaxis.title = xaxis
-            self.plot_experimental_data()
+            datasets = [dataset["name"] for dataset in self.g.data]
+            if (
+                self.experimental_data is not None
+                and "Experimental Data" not in datasets
+            ):
+                self.plot_experimental_data(intensity=intensity.value)
+
+        def response_exp_intensity(change):
+            new_intensity = intensity.value
+            y = self.experimental_data[:, 1] * new_intensity
+            with self.g.batch_update():
+                for index, dataset in enumerate(self.g.data):
+                    if dataset["name"] == "Experimental Data":
+                        self.g.data[index].y = y
 
         spectra_type.observe(response, names="value")
         spectrum_select.observe(response, names="value")
         gamma.observe(response, names="value")
         sigma.observe(response, names="value")
-        intensity.observe(response, names="value")
+        intensity.observe(response_exp_intensity, names="value")
         fill.observe(response, names="value")
         self.children = [
             spectra_type,
@@ -257,22 +268,27 @@ def response(change):
 
     def _handle_upload(self, change):
         """Process the uploaded experimental data file."""
-        import pandas as pd
+        import numpy as np
 
         uploaded_file = next(iter(change.new.values()))
         content = uploaded_file["content"]
         content_str = content.decode("utf-8")
 
         from io import StringIO
 
-        df = pd.read_csv(StringIO(content_str), header=None)
-
-        self.experimental_data = df
-        self.plot_experimental_data()
+        self.experimental_data = np.loadtxt(
+            StringIO(content_str), delimiter=",", converters=lambda i: np.float64(i)
+        )
+        self.plot_experimental_data(intensity=1)
 
-    def plot_experimental_data(self):
+    def plot_experimental_data(self, intensity):
         """Plot the experimental data alongside the calculated data."""
         if self.experimental_data is not None:
-            x = self.experimental_data[0]
-            y = self.experimental_data[1]
-            self.g.add_scatter(x=x, y=y, mode="lines", name="Experimental Data")
+            x = self.experimental_data[:, 0]
+            y = self.experimental_data[:, 1]
+            self.g.add_scatter(
+                x=x,
+                y=y * intensity,
+                mode="lines",
+                name="Experimental Data",
+            )