diff --git a/navipy/arenatools/patterns.py b/navipy/arenatools/patterns.py
new file mode 100644
index 0000000000000000000000000000000000000000..10cc990539ec96cfa4d2672bfae480252cde9233
--- /dev/null
+++ b/navipy/arenatools/patterns.py
@@ -0,0 +1,98 @@
+"""
+Tools to generate patterns
+"""
+import numpy as np
+
+
+def generate_1overf_noise(img_size, beta, noise=None):
+    """
+    Generates the discrete fourier transformation of noise and weights it with weights<0.
+    Where the smallest weights are in the middle columns of the returned noise array and the biggest in the outer columns.
+    First generates the noise and applies the following formula:
+
+    .. math::
+
+            DFT(\\frac{1}{f^{\\beta}} * DFT(noise))
+
+    The noise must be a 2d array.
+
+    :params img_size: size of the output noise dimensions \
+(array dimension e.g. (4,4))
+    :params beta: used to calculate the weights of the noise, \
+the bigger beta the smaller the weights, can have an arbitrary value \
+(weights are always between 0 and 1)
+    :params noise: array with same size as img_size, that is used as \
+the noise (default: random generated noise)
+    """
+    # Calculate image size -> next biggest power of two,
+    # in which the image fits (s>=max(img_size))
+    s = 2**(np.ceil(np.log2(np.max(img_size)))).astype(int)
+    if noise is None:
+        # generate white noise
+        noise = np.random.randn(s, s)
+
+    # calculate filter
+    fx = np.arange(s/2)+1
+    # index from 0-s/2,s/2-0 -> middle highest index
+    fx = np.hstack([fx, fx[-1::-1]])
+    fx = fx[:, np.newaxis]
+    # copy first row s times -> fx=[[0..0],[1..],..,[s/2,..s/2],..[0..0]
+    # fx is a symmetric matrix
+    fx = fx.repeat(s, axis=1)
+    fy = fx.transpose()
+
+    f = np.sqrt(fx**2 + fy**2)  # Euclidian norm
+    f = f**(-beta)
+    # apply filter in frequency domain
+    # calculate disrete furier transformations
+    fnoise = np.fft.ifft2(np.fft.fft2(noise)*f)
+
+    # trim to image size
+    fnoise = fnoise[:img_size[0], :img_size[1]]
+    fnoise = np.real(fnoise)
+    return fnoise
+
+
+def gray2red(img):
+    """ convert a gray image to a red image (black -> red)
+
+    Many bees and flies are not sensitive to red light, and
+    can be better observed on red background than on a black one
+    due to their dark colour.
+
+    :params img: Gray image to be converted into red-white one
+    """
+    img = img[..., np.newaxis]
+    img = img.repeat(3, axis=2)
+    maxval = np.max(img)
+    img[:, :, 1] = maxval-img[:, :, 0]
+    img[:, :, 2] = maxval-img[:, :, 0]
+    img[:, :, 0] = maxval
+    return img
+
+
+def norm_img(img):
+    """ Normalise an 8bit image between 0 and 255
+
+    :params img: Image to be normalised
+    """
+    img = img.astype(np.float)
+    img -= img.min()
+    img /= img.max()
+    img *= 255
+    return img.astype(np.uint8)
+
+
+def rectangular_pattern(width, length, beta=1.4, pixel_per_mm=1):
+    """generate a rectangular pattern
+
+    :param width: width of the pattern in mm
+    :param length: length of the pattern in mm
+    :param beta: beta coef for generating a 1/(f^beta) pattern
+    :param pixel_per_mm: number of pixel per mm
+    :returns: a rectangular random image
+    :rtype: np.ndarray
+    """
+    corridor = np.array([width, length])
+    corridor_px = corridor*pixel_per_mm  # in px
+    return generate_1overf_noise(corridor_px, beta)
diff --git a/navipy/maths/quaternion.py b/navipy/maths/quaternion.py
index 698788bdb86c0c6348eb33038659ef2bc6ac9e6e..6d958afc207494cb23837826ee75d1d31e8d3aab 100644
--- a/navipy/maths/quaternion.py
+++ b/navipy/maths/quaternion.py
@@ -84,7 +84,7 @@ def matrix(quaternion):
         [1.0 - q[2, 2] - q[3, 3],	 q[1, 2] - q[3, 0],	 q[1, 3] + q[2, 0], 0.0],
         [	q[1, 2] + q[3, 0], 1.0 - q[1, 1] - q[3, 3],	 q[2, 3] - q[1, 0], 0.0],
         [	q[1, 3] - q[2, 0],	 q[2, 3] + q[1, 0], 1.0 - q[1, 1] - q[2, 2], 0.0],
-        [				0.0,				 0.0,				 0.0, 1.0]])
+        [0.0,			 0.0,			 0.0, 1.0]])
 
 
 def from_matrix(matrix, isprecise=False):
diff --git a/navipy/scripts/__init__.py b/navipy/scripts/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/navipy/sensors/blend_alongtraj.py b/navipy/scripts/blend_alongtraj.py
similarity index 100%
rename from navipy/sensors/blend_alongtraj.py
rename to navipy/scripts/blend_alongtraj.py
diff --git a/navipy/sensors/blend_ongrid.py b/navipy/scripts/blend_ongrid.py
similarity index 100%
rename from navipy/sensors/blend_ongrid.py
rename to navipy/scripts/blend_ongrid.py
diff --git a/navipy/sensors/blend_overlaytraj.py b/navipy/scripts/blend_overlaytraj.py
similarity index 100%
rename from navipy/sensors/blend_overlaytraj.py
rename to navipy/scripts/blend_overlaytraj.py
diff --git a/navipy/sensors/blendnavipy.py b/navipy/scripts/blendnavipy.py
similarity index 100%
rename from navipy/sensors/blendnavipy.py
rename to navipy/scripts/blendnavipy.py
diff --git a/navipy/sensors/blendunittest.py b/navipy/scripts/blendunittest.py
similarity index 100%
rename from navipy/sensors/blendunittest.py
rename to navipy/scripts/blendunittest.py
diff --git a/navipy/sensors/renderer.py b/navipy/sensors/renderer.py
index 9bd2b39f7f96c0db6619ef95cafacf0da032e699..07d6f1c1f83fa61aa5b7e7be0ba3d13a161c516c 100644
--- a/navipy/sensors/renderer.py
+++ b/navipy/sensors/renderer.py
@@ -15,6 +15,7 @@ import pandas as pd
 import yaml  # Used to load config files
 import pkg_resources
 from navipy.maths.homogeneous_transformations import compose_matrix
+from navipy.maths.quaternion import matrix as quatmatrix
 import navipy.maths.constants as constants
 from navipy.tools.trajectory import Trajectory
 from PIL import Image
@@ -208,6 +209,7 @@ class BlenderRender(AbstractRender):
         ..todo check that TemporaryDirectory is writtable and readable
         """
         super(BlenderRender, self).__init__()
+        self._renderaxis = '+x'
         # Rendering engine needs to be Cycles to support panoramic
         # equirectangular camera
         bpy.context.scene.render.engine = 'CYCLES'
@@ -546,10 +548,14 @@ class BlenderRender(AbstractRender):
             raise TypeError(
                 'posorient must be of type array, list, or pandas Series')
         # Render
-        self.camera.matrix_world = compose_matrix(
-            angles=posorient.loc[convention],
+        rotmat = compose_matrix(
+            angles=[0, 0, 0],  # posorient.loc[convention],
             translate=posorient.loc['location'],
             axes=convention)
+        if self._renderaxis == '+x':
+            initrot = quatmatrix([0.5, 0.5, -0.5, -0.5])
+            rotmat[:3, :3] = rotmat[:3, :3].dot(initrot[:3, :3])
+        self.camera.matrix_world = rotmat
         bpy.ops.render.render()
 
     def scene(self, posorient):
diff --git a/setup.py b/setup.py
index 4019e585586f490fbd709876e61ed380fa2a0411..4068f783e699c11cfb09204abcceef1f5a4cdf28 100644
--- a/setup.py
+++ b/setup.py
@@ -57,11 +57,11 @@ setup_dict = {'name': 'navipy',
               'include_package_data': True,
               'entry_points': {
                   'console_scripts': [
-                      'blendnavipy=navipy.sensors.blendnavipy:main',
-                      'blendunittest=navipy.sensors.blendunittest:main',
-                      'blendongrid=navipy.sensors.blend_ongrid:main',
-                      'blendoverlaytraj=navipy.sensors.blend_overlaytraj:main',
-                      'blendalongtraj=navipy.sensors.blend_alongtraj:main'
+                      'blendnavipy=navipy.scripts.blendnavipy:main',
+                      'blendunittest=navipy.scripts.blendunittest:main',
+                      'blendongrid=navipy.scripts.blend_ongrid:main',
+                      'blendoverlaytraj=navipy.scripts.blend_overlaytraj:main',
+                      'blendalongtraj=navipy.scripts.blend_alongtraj:main'
                   ]},
               }
 
diff --git a/tutorials/02-recording-animal-trajectory.ipynb b/tutorials/02-recording-animal-trajectory.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..2fd64429bf421126b7000c94ce0f6fd186fbd01f
--- /dev/null
+++ b/tutorials/02-recording-animal-trajectory.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tutorials/03-rendering-along-trajectory.ipynb b/tutorials/03-rendering-along-trajectory.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..26342672efc821a8f46f2e516604d50d117d9624
--- /dev/null
+++ b/tutorials/03-rendering-along-trajectory.ipynb
@@ -0,0 +1,118 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Recording along a trajectory\n",
+    "\n",
+    "In this tutorial, you will learn to take advantage of navipy and the rendering modules (blender) to render what has been seen by the animal along its trajectory. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "```bash\n",
+    "blendalongtraj --output-file='pathtodatabase' --blenderworld=''\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Database to videos"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from navipy.database import DataBaseLoad\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline \n",
+    "database = '../render_body.db'\n",
+    "mydb = DataBaseLoad(database)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "my_scene = mydb.scene(rowid=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/bolirev/.virtualenvs/toolbox-navigation/lib/python3.6/site-packages/matplotlib-2.2.2-py3.6-linux-x86_64.egg/matplotlib/figure.py:459: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
+      "  \"matplotlib is currently using a non-GUI backend, \"\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "f, axarr = plt.subplots(1, 2, figsize=(15, 4))\n",
+    "\n",
+    "to_plot_im = my_scene[:, :, :3, 0]\n",
+    "to_plot_im -= to_plot_im.min()\n",
+    "to_plot_im /= to_plot_im.max()\n",
+    "to_plot_im = to_plot_im * 255\n",
+    "to_plot_im = to_plot_im.astype(np.uint8)\n",
+    "to_plot_dist = my_scene[:, :, 3, 0]\n",
+    "\n",
+    "ax = axarr[0]\n",
+    "ax.imshow(to_plot_im)\n",
+    "ax.invert_yaxis()\n",
+    "\n",
+    "ax = axarr[1]\n",
+    "ax.imshow(to_plot_dist)\n",
+    "ax.invert_yaxis()\n",
+    "\n",
+    "f.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}