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Diffstat (limited to 'fg21sim/utils/grid.py')
| -rw-r--r-- | fg21sim/utils/grid.py | 157 |
1 files changed, 157 insertions, 0 deletions
diff --git a/fg21sim/utils/grid.py b/fg21sim/utils/grid.py new file mode 100644 index 0000000..cc99407 --- /dev/null +++ b/fg21sim/utils/grid.py @@ -0,0 +1,157 @@ +# Copyright (c) 2016 Weitian LI <liweitianux@live.com> +# MIT license + +""" +Grid utilities. +""" + + +import numpy as np +from scipy import ndimage + +from .draw import ellipse + + +def _wrap_longitudes(lon): + """Wrap the longitudes for values that beyond the valid range [0, 360)""" + lon[lon < 0] += 360 + lon[lon >= 360] -= 360 + return lon + + +def _wrap_latitudes(lat): + """Wrap the latitudes for values that beyond the valid range [-90, 90]""" + lat[lat < -90] = -lat[lat < -90] - 180 + lat[lat > 90] = -lat[lat > 90] + 180 + return lat + + +def make_coordinate_grid(center, size, resolution): + """Make a rectangle, Cartesian coordinate grid. + + Parameters + ---------- + center : 2-float tuple + Center coordinate (longitude, latitude) of the grid, + with longitude [0, 360) degree, latitude [-90, 90] degree. + size : float, or 2-float tuple + The sizes (size_lon, size_lat) of the grid along the longitude + and latitude directions. If only one float specified, then the + grid is square. + resolution : float + The grid resolution, unit [ degree ]. + + Returns + ------- + lon : 2D `~numpy.ndarray` + The array with elements representing the longitudes of each grid + pixel. The array is odd-sized, with the input center locating at + the exact grid central pixel. + Also, the longitudes are fixed to be in the valid range [0, 360). + lat : 2D `~numpy.ndarray` + The array with elements representing the latitudes of each grid + pixel. + Also, the latitudes are fixed to be in the valid range [-90, 90]. + """ + lon0, lat0 = center + try: + size_lon, size_lat = size + except (TypeError, ValueError): + size_lon = size_lat = size + # Half number of pixels (excluding the center) + hn_lon = np.ceil(0.5*size_lon / resolution).astype(np.int) + hn_lat = np.ceil(0.5*size_lat / resolution).astype(np.int) + idx_lon = lon0 + np.arange(-hn_lon, hn_lon+1) * resolution + idx_lat = lat0 + np.arange(-hn_lat, hn_lat+1) * resolution + # Fix the longitudes and latitudes to be in the valid ranges + idx_lon = _wrap_longitudes(idx_lon) + idx_lat = _wrap_latitudes(idx_lat) + lon, lat = np.meshgrid(idx_lon, idx_lat) + return lon, lat + + +def make_grid_ellipse(center, size, resolution, rotation=None): + """Make a square coordinate grid just containing the specified + (rotated) ellipse. + + Parameters + ---------- + center : 2-float tuple + Center coordinate (longitude, latitude) of the grid, + with longitude [0, 360) degree, latitude [-90, 90] degree. + size : 2-float tuple + The (major, minor) axes of the filling ellipse, unit [ degree ]. + resolution : float + The grid resolution, unit [ degree ]. + rotation : float, optional + The rotation angle (unit [ degree ]) of the filling ellipse. + + Returns + ------- + lon : 2D `~numpy.ndarray` + The array with elements representing the longitudes of each grid + pixel. The array is odd-sized and square, with the input center + locating at the exact grid central pixel. + Also, the longitudes are fixed to be in the valid range [0, 360). + lat : 2D `~numpy.ndarray` + The array with elements representing the latitudes of each grid + pixel. + Also, the latitudes are fixed to be in the valid range [-90, 90]. + grid : 2D float `~numpy.ndarray` + The array containing the specified ellipse, where the pixels + corresponding to the ellipse with positive values, while other pixels + are zeros. + This array is rotated from the nominal ellipse of value ones, + therefore the edges of the rotated ellipse is in fraction (0-1), + which can be regarded as similar to the sub-pixel rendering. + + NOTE + ---- + The generated grid is square, determined by the major axis of the ellipse, + therefore, we can simply rotate the ellipse without reshaping. + """ + major = max(size) + size_square = (major, major) + lon, lat = make_coordinate_grid(center, size_square, resolution) + shape = lon.shape + # Fill the ellipse into the grid + r0, c0 = np.floor(np.array(shape) / 2.0).astype(np.int) + r_radius, c_radius = np.ceil(0.5*np.array(size)/resolution).astype(np.int) + rr, cc = ellipse(r0, c0, r_radius, c_radius, shape=shape) + grid = np.zeros(shape) + grid[rr, cc] = 1.0 + if rotation is not None: + # Rotate the ellipse + grid = ndimage.rotate(grid, angle=rotation, order=1, reshape=False) + return (lon, lat, grid) + + +def map_grid_to_healpix(grid, nside): + """Map the filled coordinate grid to the HEALPix map (RING ordering). + + Parameters + ---------- + grid : 3-element tuple + A 3-element tuple `(lon, lat, gridmap)` that specifies the coordinate + grid to be mapped, where `lon` and `lat` are the longitudes and + latitudes of the grid pixels, and `gridmap` is the image to be + mapped to the HEALPix map. + nside : int + Nside of the output HEALPix map. + + Returns + ------- + hpmap : 1D `~numpy.ndarray` + Mapped HEALPix map in *RING* ordering. + + NOTE + ---- + Generally, the input coordinate grid has higher resolution than the + output HEALPix map, so down-sampling is performed. + However, note that the total flux is *NOT PRESERVED* for the mapping + (or reprojection) procedure. + + XXX/TODO: + - Implement the flux-preserving algorithm (reference ???) + """ + raise NotImplementedError("TODO") |