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cartopy.util.add_cyclic#

cartopy.util.add_cyclic(data, x=None, y=None, axis=-1, cyclic=360, precision=0.0001)[source]#

Add a cyclic point to an array and optionally corresponding x/longitude and y/latitude coordinates.

Checks all differences between the first and last x-coordinates along axis to be less than precision.

Parameters:

  • data (ndarray) – An n-dimensional array of data to add a cyclic point to.

  • x (ndarray, optional) –

    An n-dimensional array which specifies the x-coordinate values for the dimension the cyclic point is to be added to, i.e. normally the longitudes. Defaults to None.

    If x is given then add_cyclic checks if a cyclic point is already present by checking all differences between the first and last coordinates to be less than precision. No point is added if a cyclic point was detected.

    If x is 1- or 2-dimensional, x.shape[-1] must equal data.shape[axis], otherwise x.shape[axis] must equal data.shape[axis].

  • y (ndarray, optional) –

    An n-dimensional array with the values of the y-coordinate, i.e. normally the latitudes. The cyclic point simply copies the last column. Defaults to None.

    No cyclic point is added if y is 1-dimensional. If y is 2-dimensional, y.shape[-1] must equal data.shape[axis], otherwise y.shape[axis] must equal data.shape[axis].

  • axis (int, optional) – Specifies the axis of the arrays to add the cyclic point to, i.e. axis with changing x-coordinates. Defaults to the right-most axis.

  • cyclic (int or float, optional) – Width of periodic domain (default: 360).

  • precision (float, optional) – Maximal difference between first and last x-coordinate to detect cyclic point (default: 1e-4).

Returns:

  • cyclic_data – The data array with a cyclic point added.

  • cyclic_x – The x-coordinate with a cyclic point, only returned if the x keyword was supplied.

  • cyclic_y – The y-coordinate with the last column of the cyclic axis duplicated, only returned if x was 2- or n-dimensional and the y keyword was supplied.

Examples

Adding a cyclic point to a data array, where the cyclic dimension is the right-most dimension.

>>> import numpy as np
>>> data = np.ones([5, 6]) * np.arange(6)
>>> cyclic_data = add_cyclic(data)
>>> print(cyclic_data)  
[[0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]]

Adding a cyclic point to a data array and an associated x-coordinate.

>>> lons = np.arange(0, 360, 60)
>>> cyclic_data, cyclic_lons = add_cyclic(data, x=lons)
>>> print(cyclic_data)  
[[0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]]
>>> print(cyclic_lons)
[  0  60 120 180 240 300 360]

Adding a cyclic point to a data array and an associated 2-dimensional x-coordinate.

>>> lons = np.arange(0, 360, 60)
>>> lats = np.arange(-90, 90, 180/5)
>>> lon2d, lat2d = np.meshgrid(lons, lats)
>>> cyclic_data, cyclic_lon2d = add_cyclic(data, x=lon2d)
>>> print(cyclic_data)  
[[0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]]
>>> print(cyclic_lon2d)
[[  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]]

Adding a cyclic point to a data array and the associated 2-dimensional x- and y-coordinates.

>>> lons = np.arange(0, 360, 60)
>>> lats = np.arange(-90, 90, 180/5)
>>> lon2d, lat2d = np.meshgrid(lons, lats)
>>> cyclic_data, cyclic_lon2d, cyclic_lat2d = add_cyclic(
...     data, x=lon2d, y=lat2d)
>>> print(cyclic_data)  
[[0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]
 [0. 1. 2. 3. 4. 5. 0.]]
>>> print(cyclic_lon2d)
[[  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]
 [  0  60 120 180 240 300 360]]
>>> print(cyclic_lat2d)
[[-90. -90. -90. -90. -90. -90. -90.]
 [-54. -54. -54. -54. -54. -54. -54.]
 [-18. -18. -18. -18. -18. -18. -18.]
 [ 18.  18.  18.  18.  18.  18.  18.]
 [ 54.  54.  54.  54.  54.  54.  54.]]

Not adding a cyclic point if cyclic point detected in x.

>>> lons = np.arange(0, 361, 72)
>>> lats = np.arange(-90, 90, 180/5)
>>> lon2d, lat2d = np.meshgrid(lons, lats)
>>> cyclic_data, cyclic_lon2d, cyclic_lat2d = add_cyclic(
...     data, x=lon2d, y=lat2d)
>>> print(cyclic_data)  
[[0. 1. 2. 3. 4. 5.]
 [0. 1. 2. 3. 4. 5.]
 [0. 1. 2. 3. 4. 5.]
 [0. 1. 2. 3. 4. 5.]
 [0. 1. 2. 3. 4. 5.]]
>>> print(cyclic_lon2d)
[[  0  72 144 216 288 360]
 [  0  72 144 216 288 360]
 [  0  72 144 216 288 360]
 [  0  72 144 216 288 360]
 [  0  72 144 216 288 360]]
>>> print(cyclic_lat2d)
[[-90. -90. -90. -90. -90. -90.]
 [-54. -54. -54. -54. -54. -54.]
 [-18. -18. -18. -18. -18. -18.]
 [ 18.  18.  18.  18.  18.  18.]
 [ 54.  54.  54.  54.  54.  54.]]
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