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| -rw-r--r-- | fg21sim/utils/draw.py | 63 |
1 files changed, 62 insertions, 1 deletions
diff --git a/fg21sim/utils/draw.py b/fg21sim/utils/draw.py index 25d83c9..47c9c08 100644 --- a/fg21sim/utils/draw.py +++ b/fg21sim/utils/draw.py @@ -1,4 +1,4 @@ -# Copyright (c) 2016 Weitian LI <liweitianux@live.com> +# Copyright (c) 2016-2017 Weitian LI <weitian@aaronly.me> # MIT license @@ -6,9 +6,70 @@ Generic drawers (a.k.a. painters) that draw some commonly used shapes. """ +import logging import numpy as np import numba as nb +from scipy import interpolate + + +logger = logging.getLogger(__name__) + + +def circle(radius=None, rprofile=None, fill_value=0.0): + """ + Draw a (filled) circle at the center of the output grid. + If ``rprofile`` is supplied, then it is used as the radial values + for the circle. + + Parameters + ---------- + radius : int + The radius of the circle to draw + rprofile : 1D `~numpy.ndarray`, optional + The radial values for the circle, and ``radius`` will be ignored + if specified. + If not provided, then fill the circle with ones. + fill_value : float, optional + Value to be filled to the empty pixels, default 0.0 + + Returns + ------- + img : 2D `~numpy.ndarray` + Image of size ``(2*radius+1, 2*radius+1)`` with the circle drawn + at the center. + + NOTE + ---- + Using a rotational formulation to create the 2D window/image from the + 1D window/profile gives more circular contours, than using the + "outer product." + + Credit + ------ + [1] MATLAB - creating 2D convolution filters + https://cn.mathworks.com/matlabcentral/newsreader/view_thread/23588 + """ + if rprofile is not None: + if radius is not None: + logger.warning("circle(): Ignored parameter radius.") + rprofile = np.asarray(rprofile) + radius = len(rprofile) - 1 + + xsize = 2 * radius + 1 + x = np.arange(xsize) - radius + xg, yg = np.meshgrid(x, x) + r = np.sqrt(xg**2 + yg**2) + ridx = (r <= radius) + img = np.zeros(shape=(xsize, xsize)) + img.fill(fill_value) + if rprofile is None: + img[ridx] = 1.0 + else: + finterp = interpolate.interp1d(x=np.arange(len(rprofile)), + y=rprofile, kind="linear") + img[ridx] = finterp(r[ridx]) + return img @nb.jit(nb.types.UniTuple(nb.int64[:], 2)(nb.types.UniTuple(nb.int64, 2), |