add fiducials

TruScanEEGpy/montage.py

@@ -2,8 +2,8 @@
 
 """Submodule."""
 import mne
-import pandas as pd
 import numpy as np
+import pandas as pd
 
 
 def montage_mne_128(layout):
@@ -14,16 +14,50 @@ def montage_mne_128(layout):
     >>> import TruScanEEGpy
     >>> import mne
     >>>
-    >>> layout = TruScanEEGpy.layout_128()
+    >>> layout = TruScanEEGpy.layout_128('10-5')
     >>> montage = TruScanEEGpy.montage_mne_128(layout)
     >>> mne.viz.plot_montage(montage)
     >>> mne.viz.plot_montage(montage, kind = "3d")
+    >>>
+    >>> # Compare to other standard montages
+    >>> montage = mne.channels.make_standard_montage('standard_1005')
+    >>> montage.get_positions()
+    >>> montage.get_positions()['ch_pos']["TP9"]
+    >>> mne.viz.plot_montage(montage)
+    >>>
+    >>> montage = mne.channels.make_standard_montage('biosemi128')
+    >>> montage.get_positions()
+    >>> mne.viz.plot_montage(montage)
+    >>>
+    >>> montage = mne.channels.make_standard_montage('GSN-HydroCel-128')
+    >>> montage.get_positions()
+    >>> mne.viz.plot_montage(montage)
     """
     layout["ID"] = layout["Name"]
-    layout = layout.set_index('Name')
-    layout = layout.to_dict(orient = "index")
+    layout = layout.set_index("Name")
+    layout = layout.to_dict(orient="index")
     for channel in layout.keys():
-        yxz = np.array([layout[channel]["Y"], -1*layout[channel]["X"], layout[channel]["Z"]])
-        layout[channel] = yxz
-    montage = mne.channels.make_dig_montage(layout, coord_frame='head')
-    return(montage)
+        yxz = np.array([layout[channel]["Y"], -1 * layout[channel]["X"], layout[channel]["Z"]])
+        layout[channel] = yxz / 1000  # The unit in the deymed layout file is bigger than in MNE
+
+    montage = mne.channels.make_dig_montage(
+        layout,
+        # standard_1005 -----------
+        # nasion=np.array([8.12812462e-06, 8.50133285e-02, -3.91550369e-02]),
+        # lpa=np.array([-0.08429365, -0.01957576, -0.04699231]),
+        # rpa=np.array([0.08401729, -0.01959495, -0.04703638]),
+        # biosemi128 -----------
+        # nasion=np.array([5.27205792e-18, 8.60992398e-02, -4.01487349e-02]),
+        # lpa=np.array([-0.08609924, -0.0, -0.04014873]),
+        # rpa=np.array([0.08609924, 0.0, -0.04014873]),
+        # biosemi128 -----------
+        # nasion=np.array([0.0, 0.09821842, -0.02554916]),
+        # lpa=np.array([-0.07266855, 0.00043744, -0.03520521]),
+        # rpa=np.array([0.07266855, 0.00043744, -0.03520521]),
+        # TruScanEEGpy -----------
+        nasion=np.array([0.0, 0.08116, -0.03279]),
+        lpa=np.array([-0.07685, 0.02609, -0.03279]),
+        rpa=np.array([0.07685, 0.02609, -0.03279]),
+        coord_frame="head",  # "unknown",
+    )
+    return montage