Fix 209 eeg signals appears flat in the dashboard

examples/plot_10_run_pipeline.py

@@ -6,6 +6,13 @@
 In this notebook, we will run the pyLossless pipeline on a publicly available dataset.
 """
 
+# %%
+# Installation (in the terminal or through Jupyter)
+# -------
+#!pip install -q pylossless
+#!pip install -q openneuro-py
+
+
 # %%
 # Imports
 # -------
@@ -14,7 +21,12 @@
 import pylossless as ll
 
 # %%
-# Get the data
+# Get the data.
+#
+# Note: If you are testing this examples in Google Colab, the
+# openneuro-py download function does not always work flawlessly. You may have
+# to run this cell twice for the files to be properly downloaded and usable by
+# the next cell.
 # ------------
 raw, config, bids_path = ll.datasets.load_openneuro_bids()
 

pylossless/dash/css_defaults.py

@@ -19,11 +19,10 @@
 DEFAULT_LAYOUT_XAXIS = {
     "zeroline": False,
     "showgrid": True,
-    "title": "time (seconds)",
+    "title": {"text": "time (seconds)", "font": {"color": "#ADB5BD"}},
     "gridcolor": "white",
     "fixedrange": True,
     "showline": True,
-    "titlefont": dict(color="#ADB5BD"),
     "tickfont": dict(color="#ADB5BD"),
     "automargin": True,
 }
@@ -35,7 +34,7 @@
     "autorange": False,  # 'reversed',
     "scaleratio": 0.5,
     "tickmode": "array",
-    "titlefont": dict(color="#ADB5BD"),
+    "title": {"font": {"color": "#ADB5BD"}},
     "tickfont": dict(color="#ADB5BD"),
     "fixedrange": True,
     "automargin": True,

pylossless/dash/mne_visualizer.py

@@ -215,7 +215,8 @@ def inst(self, inst):
         )
         if self.scalings_arg == "auto":
             for kind in np.unique(self.inst.get_channel_types()):
-                self.scalings[kind] = np.percentile(self.inst.get_data(), 99.5)
+                data = self.inst.get_data(picks=kind)
+                self.scalings[kind] = np.percentile(data, 99.5)
         else:
             self.scalings.update(self.scalings_arg)
 

pylossless/dash/qcannotations.py

@@ -35,16 +35,15 @@
         self._duration = duration
         self._description = description_str
 
-        self._dash_layout = layout
         self._dash_shape = dict(
-            name=self.id,
+            name=self._id,
             type="rect",
             xref="x",
             yref="y",
             x0=self.onset,
-            y0=self._dash_layout.yaxis["range"][0],
+            y0=layout.yaxis["range"][0],
             x1=self.onset + self.duration,
-            y1=self._dash_layout.yaxis["range"][1],
+            y1=layout.yaxis["range"][1],
             fillcolor="red",
             opacity=0.25 if self.duration else 0.75,
             line_width=1,
@@ -53,13 +52,20 @@
         )
         self._dash_description = dict(
             x=self.onset + self.duration / 2,
-            y=self._dash_layout.yaxis["range"][1],
+            y=layout.yaxis["range"][1],
             text=self.description,
             showarrow=False,
             yshift=10,
             font={"color": "#F1F1F1"},
         )
 
+    def to_dict(self):
+        """Return a dict representation of the EEGAnnotation object."""
+        return {"_id": self._id, "_onset": self._onset,
+                "_duration": self._duration, "_description": self._description,
+                "_dash_description": self._dash_description,
+                "_dash_shape": self._dash_shape}
+
     def update_dash_objects(self):
         """Update plotly shape/annotations.
 
@@ -174,6 +180,14 @@
         else:
             self.annotations = pd.Series()
 
+    def to_plotly_json(self):
+        """Return a dict representation of the EEGAnnotation object.
+
+        Implementing this function is necessary for Plotly/Dash to serialize
+        EEGAnnotationList objects.
+        """
+        return {key: value.to_dict() for key, value in self.annotations.items()}
+
     def __get_series(self, attr):
         return pd.Series(
             {annot.id: getattr(annot, attr) for annot in self.annotations.values}