def __init__(self, size=None, position=None, lambda_=None, theta=None,
sigma=None, phase=None, trim=None, contrast=0.5, width=1, hide_dot=False):
if not isinstance(np, ModuleType):
message = """GaborPatch can not be initialized.
The Python package 'Numpy' is not installed."""
raise ImportError(message)
if not isinstance(pyplot, ModuleType):
message = """GaborPatch can not be initialized.
The Python package 'Matplotlib' is not installed."""
raise ImportError(message)
fid, filename = tempfile.mkstemp(
dir=stimuli.defaults.tempdir,
suffix=".png")
os.close(fid)
Picture.__init__(self, filename, position)
size = 200
diameter = 50
line_width = 20 * width
inner_diameter = 5 * (int(hide_dot)-1)
fig = plt.figure(frameon=False, figsize=(1, 1))
ax = plt.Axes(fig, [0., 0., 1., 1.])
ax.set_axis_off()
fig.add_axes(ax)
pixel_map = np.zeros((size, size))
ax.imshow(pixel_map, cmap=plt.get_cmap('gray'))
ax.add_patch(plt.Circle((size / 2, size / 2), diameter, color='w'))
ax.add_patch(plt.Rectangle((size / 2 - line_width / 2, 0), line_width, size, color='k'))
ax.add_patch(plt.Rectangle((0, size / 2 - line_width / 2), size, line_width, color='k'))
ax.add_patch(plt.Circle((size / 2, size / 2), inner_diameter, color='w'))
fig.canvas.draw()
# Now we can save it to a numpy array.
data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
#plt.show()
self._pixel_array = data
#save stimulus
color_map = pyplot.get_cmap('gray')
color_map.set_over(color="y")
pyplot.imsave(fname = filename,
arr = self._pixel_array,
cmap = color_map, format="png", vmin=0, vmax=1)
#plt.savefig(filename = filename, cmap = color_map, format="png")
self._background_colour = [0, 0, 0]
def __init__(self, size, position=None, dot_size=(5,5),
background_colour=None, dot_colour=None,
dot_percentage=50, smoothing=3):
"""Create a visual mask.
Parameters
----------
size : (int, int)
size (x, y) of the mask
position : (int, int), optional
position of the mask stimulus
dot_size : (int, int), optional
size (x, y) of the dots (default=(5,5))
background_colour : (int, int), optional
dot_colour : (int, int), optional
dot_percentage : int, optional
percentage of covered area by the dots (1 to 100) (default=50)
smoothing : int, optional
smoothing (default=3)
"""
if not isinstance(Image, ModuleType):
message = """VisualMask can not be initialized.
The Python package 'Python Imaging Library (PIL)' is not installed."""
raise ImportError(message)
fid, filename = tempfile.mkstemp(
dir=stimuli.defaults.tempdir,
suffix=".png")
os.close(fid)
Picture.__init__(self, filename, position)
self._size = size
self.dot_size = dot_size
if background_colour is not None:
self.background_colour = background_colour
else:
self.background_colour = _internals.active_exp.background_colour
if dot_colour is not None:
self.dot_colour = dot_colour
else:
self.dot_colour = _internals.active_exp.foreground_colour
self.dot_percentage = dot_percentage
self.smoothing = smoothing
self.create_mask()
def __init__(self,
size=None,
position=None,
lambda_=None,
theta=None,
sigma=None,
phase=None,
trim=None):
"""Create a Gabor Patch.
Parameters
----------
size : (int, int), optional
size (x, y) of the mask
position : (int, int), optional
position of the mask stimulus
lambda_ : int, optional
Spatial frequency (pixel per cycle)
theta : int or float, optional
Grating orientation in degrees
sigma : int or float, optional
gaussian standard deviation (in pixels)
phase : float
0 to 1 inclusive
Notes
-----
The background colour of the stimulus depends of the parameters of
the Gabor patch and can be determined (e.g. for plotting) with the
property `GaborPatch.background_colour`.
"""
# Parts of the code has be ported from http://www.icn.ucl.ac.uk/courses/MATLAB-Tutorials/Elliot_Freeman/html/gabor_tutorial.html
import types
if type(np) is not types.ModuleType:
message = """GaborPatch can not be initialized.
The Python package 'Numpy' is not installed."""
raise ImportError(message)
if type(pyplot) is not types.ModuleType:
message = """GaborPatch can not be initialized.
The Python package 'Matplotlib' is not installed."""
raise ImportError(message)
if size is None:
size = defaults.gaborpatch_size
if position is None:
position = defaults.gaborpatch_position
if lambda_ is None:
lambda_ = defaults.gaborpatch_lambda_
if theta is None:
theta = defaults.gaborpatch_theta
if sigma is None:
sigma = defaults.gaborpatch_sigma
if phase is None:
phase = defaults.gaborpatch_phase
fid, filename = tempfile.mkstemp(
dir=expyriment.stimuli.defaults.tempdir, suffix=".png")
os.close(fid)
Picture.__init__(self, filename, position)
# make linear ramp
X0 = (np.linspace(1, size, size) / size) - .5
# Set wavelength and phase
freq = size / float(lambda_)
phaseRad = phase * 2 * np.pi
# Make 2D grating
Xm, Ym = np.meshgrid(X0, X0)
# Change orientation by adding Xm and Ym together in different proportions
thetaRad = (theta / 360.) * 2 * np.pi
Xt = Xm * np.cos(thetaRad)
Yt = Ym * np.sin(thetaRad)
grating = np.sin(((Xt + Yt) * freq * 2 * np.pi) + phaseRad)
# 2D Gaussian distribution
gauss = np.exp(-((Xm**2) + (Ym**2)) / (2 * (sigma / float(size))**2))
# Trim
gauss[gauss < trim] = 0
self._pixel_array = grating * gauss
#save stimulus
color_map = pyplot.get_cmap('gray')
color_map.set_over(color="y")
pyplot.imsave(fname=filename,
arr=self._pixel_array,
cmap=color_map,
format="png")
# determine background color
norm = pyplot.normalize(vmin=np.min(self._pixel_array),
vmax=np.max(self._pixel_array))
bgc = color_map(norm(0))
self._background_colour = map(lambda x: int(x * 255), bgc[:3])
def __init__(self, size=None, position=None, lambda_=None, theta=None,
sigma=None, phase=None, trim=None):
"""Create a Gabor Patch.
Parameters
----------
size : (int, int), optional
size (x, y) of the mask
position : (int, int), optional
position of the mask stimulus
lambda_ : int, optional
Spatial frequency (pixel per cycle)
theta : int or float, optional
Grating orientation in degrees
sigma : int or float, optional
gaussian standard deviation (in pixels)
phase : float
0 to 1 inclusive
Notes
-----
The background colour of the stimulus depends of the parameters of
the Gabor patch and can be determined (e.g. for plotting) with the
property `GaborPatch.background_colour`.
"""
# Parts of the code has be ported from http://www.icn.ucl.ac.uk/courses/MATLAB-Tutorials/Elliot_Freeman/html/gabor_tutorial.html
import types
if type(np) is not types.ModuleType:
message = """GaborPatch can not be initialized.
The Python package 'Numpy' is not installed."""
raise ImportError(message)
if type(pyplot) is not types.ModuleType:
message = """GaborPatch can not be initialized.
The Python package 'Matplotlib' is not installed."""
raise ImportError(message)
if size is None:
size = defaults.gaborpatch_size
if position is None:
position = defaults.gaborpatch_position
if lambda_ is None:
lambda_ = defaults.gaborpatch_lambda_
if theta is None:
theta = defaults.gaborpatch_theta
if sigma is None:
sigma = defaults.gaborpatch_sigma
if phase is None:
phase = defaults.gaborpatch_phase
fid, filename = tempfile.mkstemp(
dir=expyriment.stimuli.defaults.tempdir,
suffix=".png")
os.close(fid)
Picture.__init__(self, filename, position)
# make linear ramp
X0 = (np.linspace(1, size, size) / size) - .5
# Set wavelength and phase
freq = size / float(lambda_)
phaseRad = phase * 2 * np.pi
# Make 2D grating
Xm, Ym = np.meshgrid(X0, X0)
# Change orientation by adding Xm and Ym together in different proportions
thetaRad = (theta / 360.) * 2 * np.pi
Xt = Xm * np.cos(thetaRad)
Yt = Ym * np.sin(thetaRad)
grating = np.sin(((Xt + Yt) * freq * 2 * np.pi) + phaseRad)
# 2D Gaussian distribution
gauss = np.exp(-((Xm ** 2) + (Ym ** 2)) / (2 * (sigma / float(size)) ** 2))
# Trim
gauss[gauss < trim] = 0
self._pixel_array = grating * gauss
#save stimulus
color_map = pyplot.get_cmap('gray')
color_map.set_over(color="y")
pyplot.imsave(fname = filename,
arr = self._pixel_array,
cmap = color_map, format="png")
# determine background color
norm = pyplot.normalize(vmin = np.min(self._pixel_array),
vmax = np.max(self._pixel_array))
bgc = color_map(norm(0))
self._background_colour = map(lambda x:int(x*255), bgc[:3])
