def CartesianToEquatorial(pos, observer=[0,0,0]): """ Convert Cartesian position coordinates to equatorial right ascension and declination, using the specified observer location. .. note:: RA and DEC will be returned in degrees, with RA in the range [0,360] and DEC in the range [-90, 90]. Parameters ---------- pos : array_like a N x 3 array holding the Cartesian position coordinates observer : array_like a length 3 array holding the observer location Returns ------- ra, dec : array_like the right ascension and declination coordinates, in degrees. RA will be in the range [0,360] and DEC in the range [-90, 90] """ # recenter based on observer pos = pos - observer s = da.hypot(pos[:,0], pos[:,1]) lon = da.arctan2(pos[:,1], pos[:,0]) lat = da.arctan2(pos[:,2], s) # convert to degrees lon = da.rad2deg(lon) lat = da.rad2deg(lat) # wrap lon to [0,360] lon = da.mod(lon-360., 360.) return lon, lat
ints = np.array([int(i) for i in str_n]) coeffs = get_coeffs_streams(len(str_n)) return ''.join(map(str, mod_abs((ints * coeffs).sum(1)))) def calc(str_n: str, times: int) -> str: for _ in tqdm.trange(times): print(str_n) str_n = calc_next(str_n) return str_n # ====================================================================================================================== # DASK # ====================================================================================================================== mod_abs_dask = comp(lambda a: da.mod(a, 10), np.abs) @memoize def get_coeffs_streams_dask(length: int): start = time.time() arrays = [] for i in tqdm.trange(1, length + 1): arrays.append(da.from_array(coefficients(length, i))) res = da.stack(arrays) print(time.time() - start) return res def calc_next_dask(str_n: str) -> str: ints = da.from_array([int(i) for i in str_n])
def _initialize_clusters(n_el, n_clusters, chunks=None): """ Initialize cluster array """ cluster_idx = da.mod(da.arange(n_el, chunks=(chunks or n_el)), n_clusters) return da.random.permutation(cluster_idx)
def CartesianToEquatorial(pos, observer=[0,0,0], frame='icrs'): """ Convert Cartesian position coordinates to equatorial right ascension and declination, using the specified observer location. .. note:: RA and DEC will be returned in degrees, with RA in the range [0,360] and DEC in the range [-90, 90]. Parameters ---------- pos : array_like a N x 3 array holding the Cartesian position coordinates observer : array_like a length 3 array holding the observer location frame : string A string, 'icrs' or 'galactic'. The frame of the input position. Use 'icrs' if the cartesian position is already in Equatorial. Returns ------- ra, dec : array_like the right ascension and declination coordinates, in degrees. RA will be in the range [0,360] and DEC in the range [-90, 90] """ # split x, y, z to signify that we do not need to have pos # as a full chunk in the last dimension. # this is useful when we use apply_gufunc. x, y, z = [pos[..., i] - observer[i] for i in range(3)] if frame == 'icrs': # FIXME: Convert these to a gufunc that uses astropy? # might be a step backward. # from equatorial to equatorial s = da.hypot(x, y) lon = da.arctan2(y, x) lat = da.arctan2(z, s) # convert to degrees lon = da.rad2deg(lon) lat = da.rad2deg(lat) # wrap lon to [0,360] lon = da.mod(lon-360., 360.) ra, dec = lon, lat else: from astropy.coordinates import SkyCoord def cart_to_eq(x, y, z): try: sc = SkyCoord(x, y, z, representation_type='cartesian', frame=frame) scg = sc.transform_to(frame='icrs') scg.representation_type = 'unitspherical' except: sc = SkyCoord(x, y, z, representation='cartesian', frame=frame) scg = sc.transform_to(frame='icrs') scg.representation = 'unitspherical' ra, dec = scg.ra.value, scg.dec.value return ra, dec dtype = pos.dtype ra, dec = da.apply_gufunc(cart_to_eq, '(),(),()->(),()', x, y, z, output_dtypes=[dtype, dtype]) return da.stack((ra, dec), axis=0)
def _initialize_clusters(n_el, n_clusters): """ Initialize cluster array """ cluster_idx = da.mod(da.arange(n_el), n_clusters) return da.random.permutation(cluster_idx)