diff --git a/doc/source/example/processing/apcv.py b/doc/source/example/processing/apcv.py
index 00a9c1727e4da1c174e952c5250c0e280e2154a5..494936458450c16355a08e2be8026b5cc3abce33 100644
--- a/doc/source/example/processing/apcv.py
+++ b/doc/source/example/processing/apcv.py
@@ -1,18 +1,20 @@
import matplotlib.pyplot as plt
from navipy.database import DataBaseLoad
import navipy.processing as processing
-import numpy as np
+from navipy.sensors import Senses
import pkg_resources
# 1) Connect to the database
mydb_filename = pkg_resources.resource_filename(
'navipy', 'resources/database.db')
mydb = DataBaseLoad(mydb_filename)
+mysenses = Senses(renderer=mydb)
# 2) Define the position-orinetation at which
# we want the image
-rowid = 12
-my_scene = mydb.scene(rowid=rowid)
-my_apcv = processing.pcode.apcv(my_scene, mydb.viewing_directions)
+posorient = mydb.posorients.loc[12, :]
+mysenses.update(posorient)
+my_apcv = processing.pcode.apcv(mysenses.vision.scene,
+ mysenses.vision.viewing_directions)
my_apcv_sph = processing.tools.cartesian_to_spherical(x=my_apcv[..., 0],
y=my_apcv[..., 1],
@@ -26,29 +28,4 @@ azimuth = mydb.viewing_directions[...,
f, axarr = plt.subplots(1, 2, figsize=(15, 4))
-
-to_plot_im = my_scene[:, :, :3, 0]
-to_plot_im -= to_plot_im.min()
-to_plot_im /= to_plot_im.max()
-to_plot_im = to_plot_im * 255
-to_plot_im = to_plot_im.astype(np.uint8)
-to_plot_dist = my_scene[:, :, 3, 0]
-ax = axarr[0]
-
-for chan_i, chan_n in enumerate(['R', 'G', 'B']):
- color = chan_n
- ax.plot(np.rad2deg(my_apcv_sph[..., chan_i, 1]),
- np.rad2deg(my_apcv_sph[..., chan_i, 0]), 'o', color=color)
-ax.imshow(to_plot_im, extent=[np.min(azimuth), np.max(azimuth),
- np.max(elevation), np.min(elevation)])
-ax.invert_yaxis()
-ax = axarr[1]
-color = 'k'
-ax.plot(np.rad2deg(my_apcv_sph[..., 3, 1]),
- np.rad2deg(my_apcv_sph[..., 3, 0]), 'o', color=color)
-
-ax.imshow(to_plot_dist, extent=[np.min(azimuth), np.max(azimuth),
- np.max(elevation), np.min(elevation)])
-ax.invert_yaxis()
-
f.show()
diff --git a/doc/source/example/processing/contrast_weighted_nearness.py b/doc/source/example/processing/contrast_weighted_nearness.py
index 220863a1abe332baafab7d0bc5c24c3f23b932cf..614d6675c9473386666ec6653174c3742b2e7548 100644
--- a/doc/source/example/processing/contrast_weighted_nearness.py
+++ b/doc/source/example/processing/contrast_weighted_nearness.py
@@ -1,6 +1,7 @@
import matplotlib.pyplot as plt
from navipy.database import DataBaseLoad
import navipy.processing as processing
+from navipy.sensors import Senses
import pkg_resources
@@ -8,11 +9,13 @@ import pkg_resources
mydb_filename = pkg_resources.resource_filename(
'navipy', 'resources/database.db')
mydb = DataBaseLoad(mydb_filename)
+mysenses = Senses(renderer=mydb)
# 2) Define the position-orinetation at which
# we want the image
-rowid = 12
-my_scene = mydb.scene(rowid=rowid)
-my_contrast = processing.pcode.contrast_weighted_nearness(my_scene)
+posorient = mydb.posorients.loc[12, :]
+mysenses.update(posorient)
+my_contrast = processing.pcode.contrast_weighted_nearness(
+ mysenses.vision.scene)
f, axarr = plt.subplots(2, 2, figsize=(15, 8))
axarr = axarr.flatten()
diff --git a/doc/source/example/processing/michelson_contrast.py b/doc/source/example/processing/michelson_contrast.py
index e7bb58c764eac18c265467c1d9046838c222d8d3..9d6e12c0b2dcea90e0a6738934de42724047f767 100644
--- a/doc/source/example/processing/michelson_contrast.py
+++ b/doc/source/example/processing/michelson_contrast.py
@@ -1,18 +1,19 @@
import matplotlib.pyplot as plt
from navipy.database import DataBaseLoad
import navipy.processing as processing
+from navipy.sensors import Senses
import pkg_resources
-
# 1) Connect to the database
mydb_filename = pkg_resources.resource_filename(
'navipy', 'resources/database.db')
mydb = DataBaseLoad(mydb_filename)
+mysenses = Senses(renderer=mydb)
# 2) Define the position-orinetation at which
# we want the image
-rowid = 12
-my_scene = mydb.scene(rowid=rowid)
-my_contrast = processing.pcode.michelson_contrast(my_scene)
+posorient = mydb.posorients.loc[12, :]
+mysenses.update(posorient)
+my_contrast = processing.pcode.michelson_contrast(mysenses.vision.scene)
f, axarr = plt.subplots(2, 2, figsize=(15, 8))
axarr = axarr.flatten()
diff --git a/doc/source/example/processing/pcv.py b/doc/source/example/processing/pcv.py
index 6c2017ccb18e8489b38b03aa968051cf2816efd8..325d61952fe5357578362b837b6477505d9e9c5c 100644
--- a/doc/source/example/processing/pcv.py
+++ b/doc/source/example/processing/pcv.py
@@ -1,15 +1,17 @@
# import matplotlib.pyplot as plt
from navipy.database import DataBaseLoad
import navipy.processing as processing
+from navipy.sensors import Senses
import pkg_resources
-
# 1) Connect to the database
mydb_filename = pkg_resources.resource_filename(
'navipy', 'resources/database.db')
mydb = DataBaseLoad(mydb_filename)
+mysenses = Senses(renderer=mydb)
# 2) Define the position-orinetation at which
# we want the image
-rowid = 12
-my_scene = mydb.scene(rowid=rowid)
-my_pcv = processing.pcode.pcv(my_scene, mydb.viewing_directions)
+posorient = mydb.posorients.loc[12, :]
+mysenses.update(posorient)
+my_pcv = processing.pcode.pcv(mysenses.vision.scene,
+ mysenses.vision.viewing_directions)
diff --git a/doc/source/example/processing/skyline.py b/doc/source/example/processing/skyline.py
index 499bacb14a6b6f83fef09403fee3484646fd160d..8846f93e37ef579bcb7a58bb712b24fc25874985 100644
--- a/doc/source/example/processing/skyline.py
+++ b/doc/source/example/processing/skyline.py
@@ -1,18 +1,19 @@
import matplotlib.pyplot as plt
from navipy.database import DataBaseLoad
import navipy.processing as processing
+from navipy.sensors import Senses
import pkg_resources
-
# 1) Connect to the database
mydb_filename = pkg_resources.resource_filename(
'navipy', 'resources/database.db')
mydb = DataBaseLoad(mydb_filename)
+mysenses = Senses(renderer=mydb)
# 2) Define the position-orinetation at which
# we want the image
-rowid = 12
-my_scene = mydb.scene(rowid=rowid)
-my_skyline = processing.pcode.skyline(my_scene)
+posorient = mydb.posorients.loc[12, :]
+mysenses.update(posorient)
+my_skyline = processing.pcode.skyline(mysenses.vision.scene)
f, axarr = plt.subplots(1, 2, figsize=(15, 4))
for chan_i, chan_n in enumerate(mydb.channels):
diff --git a/doc/source/example/rendering/blenddemo_beesampling.py b/doc/source/example/rendering/blenddemo_beesampling.py
index 8e0f429b642b6c6940d6c81fff36b54eeffd6b36..214c8801713edc1776dc868810bede232a802830 100644
--- a/doc/source/example/rendering/blenddemo_beesampling.py
+++ b/doc/source/example/rendering/blenddemo_beesampling.py
@@ -3,11 +3,11 @@ Example on how to use the rendering module
"""
import tempfile
import numpy as np
-from navipy.rendering.bee_sampling import BeeSampling
-from navipy.rendering.cyber_bee import Cyberbee
+from navipy.sensors.bee_sampling import BeeSampling
+from navipy.sensors.renderer import BlenderRender
# create a bee sampling
-cyberbee = Cyberbee()
+cyberbee = BlenderRender()
cyberbee.cycle_samples = 5
bee_samp = BeeSampling(cyberbee)
# Create a list of point from which we want to render images
diff --git a/doc/source/example/rendering/blenddemo_cyberbee.py b/doc/source/example/rendering/blenddemo_cyberbee.py
index 64f222f21cf73062d8250fd5ef623a61510c0b7a..37f6e440cb70db36da93b16871aaf6376624ccee 100644
--- a/doc/source/example/rendering/blenddemo_cyberbee.py
+++ b/doc/source/example/rendering/blenddemo_cyberbee.py
@@ -2,10 +2,10 @@ import numpy as np
import pandas as pd
from matplotlib.colors import hsv_to_rgb, rgb_to_hsv
import matplotlib.pyplot as plt
-from navipy.rendering.cyber_bee import Cyberbee
+from navipy.sensors.renderer import BlenderRender
# with tempfile.TemporaryDirectory() as folder:
-cyberbee = Cyberbee()
+cyberbee = BlenderRender()
cyberbee.cycle_samples = 50
cyberbee.camera_rotation_mode = 'XYZ'
cyberbee.camera_fov = [[-90, 90], [-180, 180]]
diff --git a/navipy/database/__init__.py b/navipy/database/__init__.py
index 2affba62d28d0be496b54ff925335cd1c2bfd494..a31f25f12f4870cfb5dcde5bf192a622cfe4926d 100644
--- a/navipy/database/__init__.py
+++ b/navipy/database/__init__.py
@@ -122,6 +122,7 @@ It creates three sql table on initialisation.
must be single value')
self.filename = filename
self.channels = channels
+ self.viewing_directions = None
self.normalisation_columns = list()
for chan_n in self.channels:
self.normalisation_columns.append(str(chan_n) + '_max')
@@ -138,6 +139,9 @@ It creates three sql table on initialisation.
self.tablecolumns['position_orientation']['alpha_2'] = 'real'
self.tablecolumns['image'] = dict()
self.tablecolumns['image']['data'] = 'array'
+ # self.tablecolumns['viewing_directions'] = dict()
+ # self.tablecolumns['viewing_directions']['elevation'] = 'array'
+ # self.tablecolumns['viewing_directions']['azimuth'] = 'array'
self.tablecolumns['normalisation'] = dict()
for col in self.normalisation_columns:
self.tablecolumns['normalisation'][col] = 'real'
@@ -376,9 +380,9 @@ database
if rowid is np.nan:
raise ValueError('rowid must not be nan')
if (posorient is None) and (rowid is None):
- raise Exception('posorient and rowid can not be both None')
+ raise Exception('posorient and rowid can not be both None')
if posorient is not None:
- rowid = self.get_posid(posorient)
+ rowid = self.get_posid(posorient)
# Read images
tablename = 'position_orientation'
toreturn = pd.read_sql_query(
diff --git a/navipy/moving/agent.py b/navipy/moving/agent.py
index 2d217c69d8ab879e86814c250f5f6bad68df66d6..041598589ae9f11ac87638a09ff7078f8d749fef 100644
--- a/navipy/moving/agent.py
+++ b/navipy/moving/agent.py
@@ -17,6 +17,7 @@ from multiprocessing import Queue, JoinableQueue, Process
import inspect
from navipy.database import DataBaseLoad
import navipy.moving.maths as navimomath
+from navipy.sensors import Senses
version = float(nx.__version__)
@@ -26,10 +27,19 @@ def defaultcallback(*args, **kwargs):
raise NameError('No Callback')
+class DefaultSensors():
+ def __init__(self):
+ pass
+
+ def update(self, posorient):
+ raise NameError('No Callback')
+
+
class AbstractAgent():
def __init__(self):
- self._sensors = defaultcallback
+ self._sensors = DefaultSensors()
self._motion = defaultcallback
+ self._motion_param = None
self._alter_posorientvel = defaultcallback
self._posorient_col = ['x', 'y', 'z',
'alpha_0', 'alpha_1', 'alpha_2']
@@ -74,6 +84,17 @@ class AbstractAgent():
def motion(self):
return inspect.getsourcelines(self._motion)
+ @property
+ def motion_param(self):
+ return self._motion_param.copy()
+
+ @motion_param.setter
+ def motion_param(self, param):
+ if isinstance(param, dict):
+ self._motion_param = param
+ else:
+ raise TypeError('motion param should be a dictionary')
+
@property
def sensors(self):
return inspect.getsourcelines(self._sensors)
@@ -83,9 +104,15 @@ class AbstractAgent():
return inspect.getsourcelines(self._alter_posorientvel)
def move(self):
- scene = self._sensors(self.posorient)
- newpos = self._motion(self.posorient, scene)
- alteredpos = self._alter_posorientvel(newpos)
+ self._sensors.update(self.posorient)
+ if self._motion_param is None:
+ self.velocity = self._motion(self._posorient_vel,
+ self._sensors)
+ else:
+ self.velocity = self._motion(self._posorient_vel,
+ self._sensors,
+ **self._motion_param)
+ alteredpos = self._alter_posorientvel(self._posorient_vel)
self.posorient = alteredpos
self.velocity = alteredpos
@@ -94,7 +121,7 @@ class AbstractAgent():
"""
if return_tra:
trajectory = pd.DataFrame(index=range(0, max_nstep),
- columns=self.posorient_vel_col)
+ columns=self._posorient_vel_col)
trajectory.loc[0, :] = self._posorient_vel.copy()
for stepi in range(1, max_nstep):
self.move()
@@ -115,16 +142,16 @@ CyberBeeAgent is a close loop agent and need to be run within blender \
bla
"""
- def __init__(self, cyberbee):
+ def __init__(self, renderer):
AbstractAgent.__init__(self)
AbstractAgent._alter_posorientvel = \
lambda motion_vec: navimomath.next_pos(motion_vec,
move_mode='free_run')
- self.sensors = cyberbee.scene
+ self.sensors = renderer
@AbstractAgent.sensors.setter
- def sensors(self, cyberbee):
- self._sensors = cyberbee.scene
+ def sensors(self, renderer):
+ self._sensors = Senses(renderer)
@AbstractAgent.motion.setter
def motion(self, motion):
@@ -159,7 +186,7 @@ GridAgent is a close loop agent here its position is snap to a grid.
def sensors(self, database_filename):
self.db = DataBaseLoad(database_filename)
self._posorients = self.db.posorients
- self._sensors = self.db.scene
+ self._sensors = Senses(renderer=self.db)
@AbstractAgent.motion.setter
def motion(self, motion):
diff --git a/navipy/rendering/__init__.py b/navipy/sensors/__init__.py
similarity index 60%
rename from navipy/rendering/__init__.py
rename to navipy/sensors/__init__.py
index 294345fcc7b702e5f4afefcd0c5264daebfe7dc9..a85692ff0caf89aac19f933b0018e14cd5e749b2 100644
--- a/navipy/rendering/__init__.py
+++ b/navipy/sensors/__init__.py
@@ -42,9 +42,31 @@ Custom sampling
Rendering classes
-----------------
-.. autoclass:: navipy.rendering.bee_sampling.BeeSampling
+.. autoclass:: navipy.sensors.bee_sampling.BeeSampling
:members:
-.. autoclass:: navipy.rendering.cyber_bee.Cyberbee
+.. autoclass:: navipy.sensors.renderer.Cyberbee
:members:
"""
+
+
+class Bunch:
+ def __init__(self, **kwds):
+ self.__dict__.update(kwds)
+
+
+class Senses():
+ def __init__(self,
+ renderer=None):
+ self.vision = Bunch(scene=None,
+ viewing_directions=None,
+ channels=None)
+ self.renderer = renderer
+ if self.renderer is not None:
+ self.vision.scene = None
+ self.vision.viewing_directions = renderer.viewing_directions
+ self.vision.channels = renderer.channels
+
+ def update(self, posorient):
+ if self.renderer is not None:
+ self.vision.scene = self.renderer.scene(posorient)
diff --git a/navipy/rendering/bee_sampling.py b/navipy/sensors/bee_sampling.py
similarity index 100%
rename from navipy/rendering/bee_sampling.py
rename to navipy/sensors/bee_sampling.py
diff --git a/navipy/rendering/cyber_bee.py b/navipy/sensors/renderer.py
similarity index 96%
rename from navipy/rendering/cyber_bee.py
rename to navipy/sensors/renderer.py
index bce38051fe2260846c56831e625466224e84f0e4..d18499a22d4326921f77f0c7ef1e3704db156c45 100644
--- a/navipy/rendering/cyber_bee.py
+++ b/navipy/sensors/renderer.py
@@ -27,10 +27,10 @@ import os
import pandas as pd
-class Cyberbee():
+class BlenderRender():
"""
- Cyberbee is a small class binding python with blender.
- With Cyberbee one can move the bee to a position, and render what
+ BlenderRender is a small class binding python with blender.
+ With BlenderRender one can move the bee to a position, and render what
the bee see at this position.
The Bee eye is a panoramic camera with equirectangular projection