Merge pull request #187 from pycroscopy/use_dict3

Use dict3

notebooks/Spectroscopy/Analyse_Low_Loss.ipynb

@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 15,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2024-09-25T17:48:50.060660Z",
@@ -206,7 +206,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "24d5e4408b284b4b8f51f8bcbdf62af4",
+       "model_id": "71ad1392b8164a899ff8186c459d546d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -228,37 +228,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "infoWidget._update()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0"
+       "21"
       ]
      },
-     "execution_count": 47,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "\n",
-    "#infoWidget.datasets['_dif'] = infoWidget.spectrum\n",
-    "\n",
     "infoWidget.x"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -8018,7 +8018,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.12.8"
   },
   "toc": {
    "base_numbering": "3",

pyTEMlib/info_widget3.py

@@ -508,9 +508,12 @@ def plot_spectrum(self):
         for key in self.added_spectra:
             self.added_spectra[key]
             spectrum = self.get_additional_spectrum(key)
+
             self.spectrum_plot.add_trace(go.Scatter(x=self.energy_scale, y=spectrum, mode='markers+lines', marker_size=.1, name=self.added_spectra[key]))
-
+            if key == 'zero_loss':
+                self.low_loss.low_loss_tab[14, 1].value = np.round(np.log(self.spectrum.sum()/spectrum.sum()), 4)
 
+
     def _update(self, ev=None):
         self.get_spectrum()
         self.plot_spectrum()
@@ -589,7 +592,6 @@ def get_spectrum(self):
 
     @out.capture(clear_output=True)
     def click_callback(self, trace, points, selector):
-        self.status_message(f'click_callback: {selector}')
         if selector.shift:
             self.spectrum_plot.add_trace(go.Scatter(x=self.energy_scale, 
                                                     y=self.dataset[points.point_inds[0][1], points.point_inds[0][0]], 
@@ -598,11 +600,14 @@ def click_callback(self, trace, points, selector):
         else: 
             if selector.ctrl:
                 self.spectrum_plot.data =[self.spectrum_plot.data[0]]
-            self.spectrum_plot.data[0].y= self.dataset[points.point_inds[0][1],points.point_inds[0][0]] 
-            self.spectrum_plot.data[0].name = 'spectrum'+str(points.point_inds[0])
+
 
             self.image_plot.data[1].x = [points.point_inds[0][1]]
             self.image_plot.data[1].y = [points.point_inds[0][0]]
+            self.x = points.point_inds[0][1]
+            self.y = points.point_inds[0][0]
+
+            self._update()
 
     @out.capture(clear_output=True)
     def selection_fn(self, trace,points,selector):
@@ -626,6 +631,7 @@ def plot_spectrum_image(self):
         else:
             self.image_plot.data[0].z=np.array(self.image).T
         self.plot_spectrum()
+        self.image_plot.data = [self.image_plot.data[0]]
         self.image_plot.add_trace(
                     go.Scatter(mode="markers", x=[0], y=[0], marker_symbol=[101],
                    marker_color="darkgray", 

pyTEMlib/low_loss_widget.py

@@ -202,7 +202,7 @@ def get_drude(self, value=0):
 
         if 'low_loss_model' not in self.parent.datasets.keys():
             self.parent.datasets['low_loss_model'] = self.parent.dataset.copy()*0
-
+        self.parent.status_message(str(self.parent.x))
         plasmon = eels_tools.fit_plasmon(self.parent.spectrum, fit_start, fit_end)
 
         p = plasmon.metadata['plasmon']['parameter']
@@ -383,12 +383,12 @@ def _update(self, ev=0):
         low_loss = None
         plasmon = None
         resolution_function = None
-        if 'zero_loss' in self.get_additional_spectrum.keys():
-            del self.get_additional_spectrum['zero_loss']
-        if 'plasmon' in self.get_additional_spectrum.keys():
-            del self.get_additional_spectrum['plasmon']
-        if 'low_loss_model' in self.get_additional_spectrum.keys():
-            del self.get_additional_spectrum['low_loss_model']
+        if 'zero_loss' in self.parent.added_spectra.keys():
+            del self.parent.added_spectra['zero_loss']
+        if 'plasmon' in self.parent.added_spectra.keys():
+            del self.parent.added_spectra['plasmon']
+        if 'low_loss_model' in self.parent.added_spectra.keys():
+            del self.parent.added_spectra['low_loss_model']
 
         if self .low_loss_tab[3, 0].value:
             if 'zero_loss' in self.parent.datasets.keys():

pyTEMlib/probe_tools.py

@@ -37,6 +37,7 @@ def make_lorentz(size_x, size_y, gamma=1.0, x0=0., y0=0., intensity=1.):
     x, y = np.mgrid[-size_x:size_x, -size_y:size_y]
     g = gamma / (2 * np.pi) / np.power(((x - x0) ** 2 + (y - y0) ** 2 + gamma ** 2), 1.5)
     probe = g / g.sum() * intensity
+
     return probe
 
 
@@ -46,6 +47,7 @@ def zero_loss_peak_weight():
     y = [0.0143, 0.0193, 0.0281, 0.0440, 0.0768, 0.1447, 0.2785, 0.4955, 0.7442, 0.9380, 1.0000, 0.9483, 0.8596,
          0.7620, 0.6539, 0.5515, 0.4478, 0.3500, 0.2683, 0.1979, 0.1410, 0.1021, 0.0752, 0.0545, 0.0401, 0.0300,
          0.0229, 0.0176, 0.0139]
+
     return x, y