patch pseudo metrology for GUIDE3 and GUIDE7 into fp-metrology.csv

bin/write_focal_plane_metrology

@@ -7,7 +7,7 @@ import numpy as np
 import yaml
 from desimeter.log import get_logger
 from pkg_resources import resource_filename
-from astropy.table import Table
+from astropy.table import Table, vstack
 from desimeter.transform.ptl2fp import apply_ptl2fp
 
 parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter,
@@ -75,6 +75,12 @@ for i in range(patch["X_FP"].size) :
             log.info("Replacing LOCATION={} PINHOLE_ID={}".format(patch["LOCATION"][i],patch["PINHOLE_ID"][i]))
             spots[:][j] = patch[:][i]
 
+log.info("applying GUIDE3/GUIDE7 patch")
+filename = resource_filename('desimeter',"data/fp-metrology-gfa_patch.csv")
+log.info(" from {}".format(filename))
+gfa_patch = Table.read(filename, format="csv")
+spots = vstack([spots, gfa_patch])
+
 
 spots.write(args.outfile,format='csv',overwrite=True)
 

bin/write_guide3_guide7_patch

@@ -0,0 +1,265 @@
+#!/usr/bin/env python
+
+from astropy.table import Table
+from astropy.io import ascii
+from pkg_resources import resource_filename
+from desimeter.transform.ptl2fp import fp2ptl, ptl2fp
+import numpy as np
+
+pinhole_ids = [1, 2, 3, 4]
+
+def _get_pinhole_gfa_coords(pinhole_id):
+    """
+    get x_gfa, y_gfa pinhole coordinates at which to evaluate planar model
+
+    Args:
+        pinhole_id : int, should be one of (1, 2, 3, 4)
+
+    Returns:
+        coords : tuple, (x_gfa, y_gfa) pixel coordinates
+    """
+
+    assert(pinhole_id in pinhole_ids)
+
+    szx = 2048
+    szy = 1032
+
+    xy_gfa_dict = {1 : (0.0, 0.0),
+                   2 : (szx-1.0, 0.0),
+                   3 : (szx-1.0, szy-1.0),
+                   4 : (0.0, szy-1.0)}
+
+    coords = xy_gfa_dict[pinhole_id]
+
+    return coords
+
+def _get_plane_coeff(petal_loc, coord='X'):
+    """
+    get coefficients of planar surface mapping from x_gfa, y_gfa to x_fp, y_fp
+
+    Args:
+        petal_loc : guide camera petal location in focal plane (0,2,3,5,7,8)
+        coord : string, should be either 'X' (for X_FP), or 'Y' (for Y_FP)
+
+    Returns:
+        coeff : list of three coefficients specifying planar model
+    """
+
+    assert(petal_loc in [0, 2, 3, 5, 7, 8])
+    assert(coord in ['X', 'Y'])
+
+    coeff_x_fp = {0: [91.8290008897, 0.0142564754, -0.0046540723],
+                  2: [405.7272754413, 0.0000436514, -0.0149327409], 
+                  3: [348.8824487879, -0.0088595464, -0.0120471442], 
+                  5: [-91.8627781345, -0.0142609354, 0.0046420089], 
+                  7: [-405.7801509760, -0.0000106187, 0.0149351226], 
+                  8: [-349.3793836387, 0.0087573071, 0.0121231345]}
+
+    coeff_y_fp = {0: [-396.9957752088, 0.0046691204, 0.0141891317],
+                  2: [-35.2976124185, 0.0150007008, 0.0000343108],
+                  3: [210.2297400065, 0.0121055754, -0.0088252019],
+                  5: [396.8617645949, -0.0046561284, -0.0141934371],
+                  7: [35.4811212256, -0.0150023601, -0.0000019735],
+                  8: [-209.8801602520, -0.0121796381, 0.0087240329]}
+
+    coeff = coeff_x_fp[petal_loc] if coord == 'X' else coeff_y_fp[petal_loc]
+
+    return coeff
+
+def _get_pinhole_xy_fp(petal_loc, pinhole_id):
+    """
+    get pinhole focal plane coordinates according to planar models
+
+    Args:
+        petal_loc : int, one of (0,2,3,5,7,8)
+        pinhole_id : int, one of (1,2,3,4)
+
+    Returns:
+        fp_coords : tuple, (X_FP, Y_FP)
+    """
+
+    x_gfa, y_gfa = _get_pinhole_gfa_coords(pinhole_id)
+
+    fp_coords = []
+    for coord in ['X', 'Y']:
+        coeff = _get_plane_coeff(petal_loc, coord=coord)
+        coord = coeff[0] + coeff[1]*x_gfa + coeff[2]*y_gfa
+        fp_coords.append(coord)
+
+    return tuple(fp_coords)
+
+def get_ptl_avg(pinhole_id, coord='Z'):
+    """
+    Get petal coordinate by averaging across petals with real metrology
+
+    Args:
+        pinhole_id : int, one of (1,2,3,4)
+        coord : string, one of 'X', 'Y', 'Z'
+
+    Returns:
+        ptl : float, average petal coordinate for this pinhole_id
+    """
+
+    assert((coord == 'X') or (coord == 'Y') or (coord == 'Z'))
+
+    fname = resource_filename('desimeter',"data/fp-metrology.csv")
+
+    tab = ascii.read(fname, format='csv')
+
+    tab = tab[(tab['PINHOLE_ID'] == pinhole_id) & (tab['DEVICE_TYPE'] == 'GFA')]
+
+    assert(len(tab) == 8)
+
+    ptl = np.mean(tab[coord + '_PTL'])
+
+    return ptl
+
+def get_fp_avg_guess(petal_loc, pinhole_id):
+    """
+    Retrieve a guess for a pinhole's focal plane coords
+
+    Args:
+        petal_loc: int
+        pinhole_id: int, one of (1,2,3,4)
+
+    Returns:
+        xyz_fp: tuple
+    """
+    assert(pinhole_id in pinhole_ids)
+
+    coords = ['X', 'Y', 'Z']
+
+    xyz_ptl = [get_ptl_avg(pinhole_id, coord=coord) for coord in coords]
+
+    x_fp, y_fp, _ = ptl2fp(petal_loc, xyz_ptl[0], xyz_ptl[1])
+
+    xyz_fp = x_fp[0], y_fp[0], xyz_ptl[2]
+
+    return xyz_fp
+
+def _ccd_to_fs_offs(xfp, yfp, zfp):
+    """ partial copy of fit_gfa2fp """
+
+    x01 =  np.array( [ xfp[1]-xfp[0], yfp[1]-yfp[0], zfp[1]-zfp[0] ] )
+    x01 /= np.sqrt(np.sum(x01**2))
+    x12 =  np.array( [ xfp[2]-xfp[1], yfp[2]-yfp[1], zfp[2]-zfp[1] ] )
+    x12 /= np.sqrt(np.sum(x12**2))
+    norm_vector= np.cross(x01,x12)
+
+    delta_z = 2.23 # mm
+    delta_x = delta_z*norm_vector[0]/norm_vector[2]
+    delta_y = delta_z*norm_vector[1]/norm_vector[2]
+
+    return delta_x, delta_y
+
+def _derive_ccd_fp_coords(petal_loc=3):
+
+    # get initial guess for X_FP, Y_FP, Z_FP of corners by
+    # averaging the petals with realmetrology
+
+    x_fp_guess = []
+    y_fp_guess = []
+    z_fp_guess = []
+
+    for pinhole_id in pinhole_ids:
+        xyz_guess = get_fp_avg_guess(petal_loc, pinhole_id)
+        x_fp_guess.append(xyz_guess[0])
+        y_fp_guess.append(xyz_guess[1])
+        z_fp_guess.append(xyz_guess[2])
+
+    x_fp_guess = np.array(x_fp_guess)
+    y_fp_guess = np.array(y_fp_guess)
+    z_fp_guess = np.array(z_fp_guess)
+
+    # evaluate the polynomial at the corner GFA pixel coordinates to 
+    # get FP coords at the focal surface
+
+    x_fp_planar = np.array([_get_pinhole_xy_fp(petal_loc, pinhole_id)[0] for pinhole_id in pinhole_ids])
+    y_fp_planar = np.array([_get_pinhole_xy_fp(petal_loc, pinhole_id)[1] for pinhole_id in pinhole_ids])
+
+    n_iter = 10
+    for i in range(n_iter):
+        # use the guessed coordinates to derive offsets
+        delta_x, delta_y = _ccd_to_fs_offs(x_fp_guess, y_fp_guess, z_fp_guess)
+
+        # the offsets should be SUBTRACTED from the focal surface FP coords
+        x_fp_physical = x_fp_planar - delta_x
+        y_fp_physical = y_fp_planar - delta_y
+
+        x_fp_guess = x_fp_physical
+        y_fp_guess = y_fp_physical
+
+    return x_fp_physical, y_fp_physical
+
+def _get_petal_id(petal_loc):
+    """convert from petal_loc to petal_id"""
+
+    petal_loc2id = {0: 1,
+                    1: 5,
+                    2: 6,
+		    3: 3,
+		    4: 8,
+		    5: 10,
+		    6: 11,
+		    7: 2,
+		    8: 7,
+		    9: 9}
+
+    return petal_loc2id[petal_loc]
+
+def _get_gfa_device(petal_loc):
+    """convert from petal_loc to GFA device number"""
+
+    petal2device = {0: 10,
+                    1: 5,
+                    2: 6,
+                    3: 2,
+                    4: 7,
+                    5: 8,
+                    6: 13,
+                    7: 1,
+                    8: 4,
+                    9: 3}
+
+    return petal2device[petal_loc]
+
+
+results = []
+for petal_loc in [3, 7]:
+    x_fp, y_fp = _derive_ccd_fp_coords(petal_loc=petal_loc)
+
+    x_ptl, y_ptl, _ = fp2ptl(petal_loc, x_fp, y_fp)
+    for pinhole_id in pinhole_ids:
+        z_ptl = get_ptl_avg(pinhole_id, coord='Z')
+
+        petal_id = _get_petal_id(petal_loc)
+        result = (petal_id, petal_loc, pinhole_id,
+                  x_fp[pinhole_id-1], y_fp[pinhole_id-1],
+                  x_ptl[pinhole_id-1], y_ptl[pinhole_id-1],
+                  z_ptl)
+
+        results.append(result)
+
+t = Table()
+t['PETAL_ID'] = [r[0] for r in results]
+t['PETAL_LOC'] = [r[1] for r in results]
+t['DEVICE_LOC'] = ''
+t['DEVICE_TYPE'] = 'GFA'
+t['PINHOLE_ID'] = [r[2] for r in results]
+t['X_PTL'] = [r[5] for r in results]
+t['Y_PTL'] = [r[6] for r in results]
+t['Z_PTL'] = [r[7] for r in results]
+t['X_MNT'] = ''
+t['Y_MNT'] = ''
+t['Z_MNT'] = ''
+t['PTL_SOURCE'] = 'Calculated'
+t['PROJ_DISTANCE'] = ''
+t['PROVENANCE'] = 'DESI-5784'
+t['NOTES'] = [('GFA ' + str(_get_gfa_device(r[1])).zfill(2)) for r in results]
+t['X_FP'] = [r[3] for r in results]
+t['Y_FP'] = [r[4] for r in results]
+t['Z_FP'] = t['Z_PTL'] # this is true in existing fp-metrology.csv file
+t['LOCATION'] = ''
+
+outname = resource_filename('desimeter',"data/fp-metrology-gfa_patch.csv")
+ascii.write(t, outname, format='csv', fast_writer=False, overwrite=True)

py/desimeter/data/fp-metrology-gfa_patch.csv

@@ -0,0 +1,9 @@
+PETAL_ID,PETAL_LOC,DEVICE_LOC,DEVICE_TYPE,PINHOLE_ID,X_PTL,Y_PTL,Z_PTL,X_MNT,Y_MNT,Z_MNT,PTL_SOURCE,PROJ_DISTANCE,PROVENANCE,NOTES,X_FP,Y_FP,Z_FP,LOCATION
+3,3,,GFA,1,348.76444805487927,210.07005017983633,-20.952542536599914,,,,Calculated,,DESI-5784,GFA 02,348.70679491687133,210.11786897613584,-20.952542536599914,
+3,3,,GFA,2,330.6341880103817,234.8539908374583,-20.767164722593968,,,,Calculated,,DESI-5784,GFA 02,330.57130343607133,234.89798181993584,-20.767164722593968,
+3,3,,GFA,3,318.2116618820145,225.75782984628623,-19.332358573025797,,,,Calculated,,DESI-5784,GFA 02,318.1506977658713,225.79919866103583,-19.332358573025797,
+3,3,,GFA,4,336.34192192651204,200.9738891886643,-19.51773638703174,,,,Calculated,,DESI-5784,GFA 02,336.2861892466713,201.01908581723583,-19.51773638703174,
+2,7,,GFA,1,349.04407428852346,209.67266701045628,-20.952542536599914,,,,Calculated,,DESI-5784,GFA 01,-405.57235990722916,35.467512906826826,-20.952542536599914,
+2,7,,GFA,2,331.0072885205292,234.52761740955359,-20.767164722593968,,,,Calculated,,DESI-5784,GFA 01,-405.59409638612914,4.7576817821268245,-20.767164722593968,
+2,7,,GFA,3,318.55006408375885,225.47668385675718,-19.332358573025797,,,,Calculated,,DESI-5784,GFA 01,-390.19598498552915,4.755647103626824,-19.332358573025797,
+2,7,,GFA,4,336.58684985175313,200.62173345765987,-19.51773638703174,,,,Calculated,,DESI-5784,GFA 01,-390.17424850662917,35.46547822832682,-19.51773638703174,

py/desimeter/data/fp-metrology.csv

@@ -5586,3 +5586,11 @@ PETAL_ID,PETAL_LOC,DEVICE_LOC,DEVICE_TYPE,PINHOLE_ID,X_PTL,Y_PTL,Z_PTL,X_MNT,Y_M
 11,6,,GIF-T,0,356.9507287827308,202.45975508907802,-19.379952041040358,,,,Calculated,,DESI-4886,Transformed from GFA Metrology,-302.9746945891407,276.83750986418437,-19.379952041040358,
 8,4,321,FIF,5,0.0,0.0,0.0,0.0,0.0,0.0,interp,0.0,none,none,194.68450753637484,248.41179725484267,0.0,4321
 11,6,541,GIF,3,295.6316672,207.6472784,-14.7505573,0.0,0.0,0.0,interp,0.0,none,0.0,-289.7276321654746,217.54445741827737,-14.7505573,6541
+3,3,,GFA,1,348.76444805487927,210.07005017983633,-20.952542536599914,,,,Calculated,,DESI-5784,GFA 02,348.70679491687133,210.11786897613584,-20.952542536599914,
+3,3,,GFA,2,330.6341880103817,234.8539908374583,-20.767164722593968,,,,Calculated,,DESI-5784,GFA 02,330.57130343607133,234.89798181993584,-20.767164722593968,
+3,3,,GFA,3,318.2116618820145,225.75782984628623,-19.332358573025797,,,,Calculated,,DESI-5784,GFA 02,318.1506977658713,225.79919866103583,-19.332358573025797,
+3,3,,GFA,4,336.34192192651204,200.9738891886643,-19.51773638703174,,,,Calculated,,DESI-5784,GFA 02,336.2861892466713,201.01908581723583,-19.51773638703174,
+2,7,,GFA,1,349.04407428852346,209.67266701045628,-20.952542536599914,,,,Calculated,,DESI-5784,GFA 01,-405.57235990722916,35.467512906826826,-20.952542536599914,
+2,7,,GFA,2,331.0072885205292,234.52761740955359,-20.767164722593968,,,,Calculated,,DESI-5784,GFA 01,-405.59409638612914,4.7576817821268245,-20.767164722593968,
+2,7,,GFA,3,318.55006408375885,225.47668385675718,-19.332358573025797,,,,Calculated,,DESI-5784,GFA 01,-390.19598498552915,4.755647103626824,-19.332358573025797,
+2,7,,GFA,4,336.58684985175313,200.62173345765987,-19.51773638703174,,,,Calculated,,DESI-5784,GFA 01,-390.17424850662917,35.46547822832682,-19.51773638703174,