pulse2percept.utils.geometry¶
Grid2D
, RetinalCoordTransform
, Curcio1990Transform
,
Watson2014Transform
, Watson2014DisplaceTransform
, cart2pol
, pol2cart
, ‘delta_angle’
Functions
cart2pol (x, y) |
Convert Cartesian to polar coordinates |
delta_angle (source_angle, target_angle[, hi]) |
Returns the signed difference between two angles (rad) |
pol2cart (theta, rho) |
Convert polar to Cartesian coordinates |
Classes
Curcio1990Transform |
Converts between visual angle and retinal eccentricity [Curcio1990] |
Grid2D (x_range, y_range[, step, grid_type]) |
2D spatial grid |
RetinalCoordTransform |
Base class for a retinal coordinate transform |
Watson2014DisplaceTransform |
Converts between visual angle and retinal eccentricity using RGC |
Watson2014Transform |
Converts between visual angle and retinal eccentricity [Watson2014] |
-
class
pulse2percept.utils.geometry.
Curcio1990Transform
[source]¶ Converts between visual angle and retinal eccentricity [Curcio1990]
-
static
dva2ret
(xdva)[source]¶ Convert degrees of visual angle (dva) to retinal eccentricity (um)
Assumes that one degree of visual angle is equal to 280 um on the retina [Curcio1990].
-
static
ret2dva
(xret)[source]¶ Convert retinal eccentricity (um) to degrees of visual angle (dva)
Assumes that one degree of visual angle is equal to 280 um on the retina [Curcio1990]
-
static
-
class
pulse2percept.utils.geometry.
Grid2D
(x_range, y_range, step=1, grid_type='rectangular')[source]¶ 2D spatial grid
This class generates a two-dimensional mesh grid from a range of x, y values and provides an iterator to loop over elements.
New in version 0.6.
Parameters: - x_range ((x_min, x_max)) – A tuple indicating the range of x values (includes end points)
- y_range (tuple, (y_min, y_max)) – A tuple indicating the range of y values (includes end points)
- step (int, double, tuple) – Step size. If int or double, the same step will apply to both x and y ranges. If a tuple, it is interpreted as (x_step, y_step).
- grid_type ({'rectangular', 'hexagonal'}) – The grid type
Notes
- The grid uses Cartesian indexing (
indexing='xy'
for NumPy’smeshgrid
function). This implies that the grid’s shape will be (number of y coordinates) x (number of x coordinates). - If a range is zero, the step size is irrelevant.
Examples
You can iterate through a grid as if it were a list:
>>> grid = Grid2D((0, 1), (2, 3)) >>> for x, y in grid: ... print(x, y) 0.0 2.0 1.0 2.0 0.0 3.0 1.0 3.0
-
plot
(transform=None, autoscale=True, zorder=None, ax=None)[source]¶ Plot the extension of the grid
Parameters: - transform (function, optional) – A coordinate transform to be applied to the (x,y) coordinates of
the grid (e.g.,
Curcio1990Transform.dva2ret
) - autoscale (bool, optional) – Whether to adjust the x,y limits of the plot to fit the implant
- zorder (int, optional) – The Matplotlib zorder at which to plot the grid
- ax (matplotlib.axes._subplots.AxesSubplot, optional) – A Matplotlib axes object. If None, will either use the current axes (if exists) or create a new Axes object
- transform (function, optional) – A coordinate transform to be applied to the (x,y) coordinates of
the grid (e.g.,
-
class
pulse2percept.utils.geometry.
RetinalCoordTransform
[source]¶ Base class for a retinal coordinate transform
A template
-
class
pulse2percept.utils.geometry.
Watson2014DisplaceTransform
[source]¶ - Converts between visual angle and retinal eccentricity using RGC
- displacement [Watson2014]
Converts from eccentricity (defined as distance from a visual center) in degrees of visual angle (dva) to microns on the retina using Eqs. 5, A5, and A6 in [Watson2014].
In a central retinal zone, the retinal ganglion cell (RGC) bodies are displaced centrifugally some distance from the inner segments of the cones to which they are connected through the bipolar cells, and thus from their receptive field. The displacement function is described in Eq. 5 of [Watson2014].
-
dva2ret
(xdva, ydva)[source]¶ Converts dva to retinal coords
Parameters: ydva (xdva,) – x,y coordinates in dva Returns: xret, yret (double or array-like) – Corresponding x,y coordinates in microns
-
static
watson_displacement
(r, meridian='temporal')[source]¶ Ganglion cell displacement function
Implements the ganglion cell displacement function described in Eq. 5 of [Watson2014].
Parameters: - r (double|array-like) – Eccentricity in degrees of visual angle (dva)
- meridian ('temporal' or 'nasal') –
Returns: - The displacement in dva experienced by ganglion cells at eccentricity
r
.
-
class
pulse2percept.utils.geometry.
Watson2014Transform
[source]¶ Converts between visual angle and retinal eccentricity [Watson2014]
-
static
dva2ret
(r_deg)[source]¶ Converts visual angles (deg) into retinal distances (um)
This function converts degrees of visual angle into a retinal distance from the optic axis (um) using Eq. A5 in [Watson2014].
Parameters: r_dva (double or array-like) – Eccentricity in degrees of visual angle (dva) Returns: r_um (double or array-like) – Eccentricity in microns
-
static
ret2dva
(r_um)[source]¶ Converts retinal distances (um) to visual angles (deg)
This function converts an eccentricity measurement on the retinal surface(in micrometers), measured from the optic axis, into degrees of visual angle using Eq. A6 in [Watson2014].
Parameters: r_um (double or array-like) – Eccentricity in microns Returns: r_dva (double or array-like) – Eccentricity in degrees of visual angle (dva)
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static
-
pulse2percept.utils.geometry.
delta_angle
(source_angle, target_angle, hi=6.283185307179586)[source]¶ Returns the signed difference between two angles (rad)
The difference is calculated as target_angle - source_angle. The difference will thus be positive if target_angle > source_angle.
New in version 0.7.
Parameters: - target_angle (source_angle,) – Input arrays with circular data in the range [0, hi]
- hi (float, optional) – Sets the upper bounds of the range (e.g., 2*np.pi or 360). Lower bound is always 0
Returns: The signed difference target_angle - source_angle in [0, hi]