diff --git a/navipy/database/__init__.py b/navipy/database/__init__.py
index fc671ea4cc4f7d1be1f839fc0232df597a90e7e3..91d1d7783ffddaa6e6bf4b5b3b7c2a5f9d6fbab7 100644
--- a/navipy/database/__init__.py
+++ b/navipy/database/__init__.py
@@ -9,7 +9,7 @@ import sqlite3
import io
from navipy.scene import is_numeric_array, check_scene
import navipy.maths.constants as mconst
-from navipy.tools.trajectory import Trajectory
+from navipy.trajectories import Trajectory
from navipy.scene import __spherical_indeces__
import logging
diff --git a/navipy/trajectories/__init__.py b/navipy/trajectories/__init__.py
index 17ce2196e96d1ce8cf0abc53d280957bd8e16b8e..217636e823151be50f0b66169bcf1fb58e3c0593 100644
--- a/navipy/trajectories/__init__.py
+++ b/navipy/trajectories/__init__.py
@@ -67,11 +67,15 @@ class Trajectory(pd.DataFrame):
@rotation_mode.setter
def rotation_mode(self, rotation_mode):
+ """Convert current rotation_mode to a different one
+
+ :param rotation_mode: the new rotation mode to be assigned
+ """
oldrotmod = self.rotation_mode
neworient = pd.DataFrame(index=self.index,
columns=self.__build_columns(rotation_mode),
dtype=float)
- neworient.drop(inpalce=True, labels='location', level=0, axis=1)
+ neworient.drop(inplace=True, labels='location', level=0, axis=1)
for index_i, row in self.iterrows():
if rotation_mode == 'quaternion':
orient = htq.from_euler(row.angle_0,
@@ -79,15 +83,15 @@ class Trajectory(pd.DataFrame):
row.angle_2,
axes=oldrotmod)
else:
- m = hte.matrix(ai=row.loc[(self.rotation_mode, 'angle_0')],
- aj=row.loc[(self.rotation_mode, 'angle_1')],
- ak=row.loc[(self.rotation_mode, 'angle_2')],
+ m = hte.matrix(ai=row.loc[(self.rotation_mode, 'alpha_0')],
+ aj=row.loc[(self.rotation_mode, 'alpha_1')],
+ ak=row.loc[(self.rotation_mode, 'alpha_2')],
axes=oldrotmod)
orient = hte.from_matrix(m, axes=rotation_mode)
- neworient.loc[index_i, rotation_mode] = orient
+ neworient.loc[index_i, rotation_mode] = orient
self.drop(inplace=True, labels=oldrotmod, level=0, axis=1)
for col in neworient.columns:
- self[(rotation_mode, col)] = neworient.loc[:, col]
+ self[col] = neworient.loc[:, col]
self.__rotconv = rotation_mode
def facing_direction(self):
@@ -433,15 +437,29 @@ class Trajectory(pd.DataFrame):
def world2body(self, markers):
""" Transform markers in world coordinate to body coordinate
"""
+ if not isinstance(markers, pd.Series):
+ msg = 'markers should be of type pd.Series and not'
+ msg += ' {}'.format(type(markers))
+ raise TypeError(msg)
+ if not isinstance(markers.index, pd.MultiIndex):
+ msg = 'markers should have a multiIndex index \n'
+ msg += ' (i,"x"), (i,"y"),(i,"z")\n'
+ msg += 'here i is the index of the marker'
+ raise TypeError(msg)
transformed_markers = pd.DataFrame(index=self.index,
columns=markers.index,
dtype=float)
+ # Looping through each time point along the trajectory
+ # to get the homogeneous transformation from the position orientation
+ # and then apply the transformed to the marker position
for index_i, row in self.iterrows():
angles = row.loc[self.rotation_mode].values
translate = row.loc['location'].values
trans_mat = htf.compose_matrix(angles=angles,
translate=translate,
axes=self.rotation_mode)
+ # More than one marker may be transformed
+ # The marker are assume to be a multiIndex dataframe
for marki in markers.index.levels[0]:
markpos = [markers.loc[marki, 'x'],
markers.loc[marki, 'y'],
diff --git a/navipy/trajectories/test_trajectory.py b/navipy/trajectories/test_trajectory.py
index 57ffa76ab01229754f2e7023beb94163c724ff73..d1fd5923504c4d08c88bb2fa17cebe7c27074726 100644
--- a/navipy/trajectories/test_trajectory.py
+++ b/navipy/trajectories/test_trajectory.py
@@ -19,25 +19,30 @@ class TestTrajectoryTransform(unittest.TestCase):
markers.loc[(2, 'x')] = np.cos(np.pi / 3)
markers.index.name = None
# Create a random trajectory
- trajectory = Trajectory(data=np.nan,
- index=np.arange(10),
- rotation_mode='sxyz',
- sampling_rate=100)
- traj_test = Trajectory(data=np.nan,
- index=np.arange(10),
- rotation_mode='sxyz',
- sampling_rate=100)
- trajectory.loc[:, 'position'] = \
- 100 * (np.random.rand(trajectory.shape[0], 3) - 0.5)
- trajectory.loc[:, trajectory.rotation_mode] = \
- 2 * np.pi * (np.random.rand(trajectory.shape[0], 3) - 0.5)
- col = (trajectory.rotation_mode, 'angle_1')
+ trajectory = Trajectory(indeces=np.arange(10),
+ rotconv='sxyz')
+ trajectory.x = 100 * (np.random.rand(trajectory.shape[0]) - 0.5)
+ trajectory.y = 100 * (np.random.rand(trajectory.shape[0]) - 0.5)
+ trajectory.z = 100 * (np.random.rand(trajectory.shape[0]) - 0.5)
+ trajectory.alpha_0 = 2 * np.pi * \
+ (np.random.rand(trajectory.shape[0]) - 0.5)
+ trajectory.alpha_1 = 2 * np.pi * \
+ (np.random.rand(trajectory.shape[0]) - 0.5)
+ trajectory.alpha_2 = 2 * np.pi * \
+ (np.random.rand(trajectory.shape[0]) - 0.5)
+ # Create test trajectory
+ traj_test = Trajectory(indeces=np.arange(10),
+ rotconv='sxyz')
+ # Devide by two the second anle, because of gimbal lock
+ col = (trajectory.rotation_mode, 'alpha_1')
trajectory.loc[:, col] = trajectory.loc[:, col] / 2
+ print(trajectory)
# forward
for euler_axes in list(htconst._AXES2TUPLE.keys()):
trajectory.rotation_mode = euler_axes
traj_test.rotation_mode = euler_axes
transformed_markers = trajectory.world2body(markers)
+ print(transformed_markers)
# reverse
for triangle_mode in ['x-axis=median-from-0',
'y-axis=1-2']: