def get_centroids(cube): p = progbar(15, "computing centroids") tot = cube.shape[0] s = tot / 15 im = cube[0] x0 = y0 = 12 x1 = y1 = 19 mask = np.repeat(True, im.size).reshape(im.shape) mask[x0:x1,y0:y1] = False centroid = [] for k,im in enumerate(cube): ma = np.ma.masked_array(im, mask) masked = ma.filled(0) centroid.append(centroid_com(masked)) if (k+1) % s == 0: p.write() p.close() centroid = np.array(centroid) return centroid
def subtract_bg(cube): p = progbar(15, "subtracting background") tot = cube.shape[0] s = tot / 15 mask = np.zeros(cube[0].shape).astype(bool) mask[6:-6, 6:-6] = True mask[12:16,:] = True mask[:,13:15] = True mask[:,31] = True unc = [] for k,im in enumerate(cube): good = ~np.isnan(im) & ~mask fit = stats.norm.fit(im[good]) unc.append(fit[1]) im -= fit[0] if (k+1) % s == 0: p.write() p.close() unc = np.array(unc) return cube, unc
def read_data(data_dir): search_str = "*I2*_bcd.fits" files = list(find_files(data_dir, search_str)) hdr = fits.getheader(files[0]).copy() if hdr['NAXIS1'] == 256: subarray = False else: subarray = True # read data and header keyword values p = progbar(15, "reading data") tot = len(files) s = tot / 15 data, time_bmjd, obs_length_s = [], [], [] for i,fp in enumerate(files): hdr = fits.getheader(fp).copy() im = fits.getdata(fp).copy() # hdulist = fits.open(fp) # hdr, im = hdulist[0].header.copy(), hdulist[0].data.copy() # hdulist.close() data.append(im) time_bmjd.append(hdr['BMJD_OBS']) obs_length_s.append(hdr['ATIMEEND'] - hdr['AINTBEG']) if (i+1) % s == 0: p.write() p.close() # make into arrays and sort by start time data, time_bmjd, obs_length_s = map(np.array, [data, time_bmjd, obs_length_s]) time_bjd = time_bmjd + 2400000.5 # assert np.all(idx == np.arange(idx.size)) # ensure already time-sorted idx = np.argsort(time_bmjd) time_bmjd = time_bmjd[idx] time_bjd = time_bjd[idx] obs_length_s = obs_length_s[idx] data = data[idx] assert np.all(np.argsort(time_bmjd) == np.arange(idx.size)) # calculate times for each individual frame p = progbar(15, "calculating timestamps") tot = len(time_bjd) s = tot / 15 k = 0 time = [] for t, length_s in zip(time_bjd, obs_length_s): length_d = length_s * (1./60) * (1./60) * (1./24) if subarray: frame_length = length_d / 64. for i in range(64): time.append(t + frame_length * i) else: time.append(t + length_d / 2.) if (k+1) % s == 0: p.write() k += 1 p.close() time = np.array(time) assert all([time[i] < time[i+1] for i in range(time.size-1)]) # another paranoid check # create data cube if subarray: cube = data.reshape(data.shape[0] * data.shape[1], data.shape[2], data.shape[3]) else: cube = np.array([i[-40:-8,8:40] for i in data]) return time, cube
