Index: trunk/tools/heather/pv3slicer/p2.txt =================================================================== --- trunk/tools/heather/pv3slicer/p2.txt (revision 39571) +++ trunk/tools/heather/pv3slicer/p2.txt (revision 39571) @@ -0,0 +1,244 @@ +4.58492550068 2.80745729282e-16 +13.6796279736 0.238742418442 +10.8391192313 0.378279793251 +19.8584310114 1.0393099566 +34.931723142 2.43671371485 +34.9796734415 3.04867947893 +36.2269319929 3.78674557433 +37.8729416579 4.61555042863 +36.6888790652 5.10610523541 +37.1260665581 5.80779623892 +38.3503117785 6.65946179349 +36.872783836 7.03565887734 +37.4916752465 7.79495738726 +38.8884392902 8.74799559172 +39.7346667238 9.61268613674 +40.905766841 10.5871914546 +42.8955348246 11.8236119039 +44.126353845 12.9012966659 +45.6479189908 14.1059831183 +47.4576201122 15.4506904921 +49.7103320817 17.0019354909 +50.917928824 18.2473537753 +53.1132462793 19.8965715619 +56.7632275592 22.1791598211 +60.7543923517 24.7110375514 +63.6767450124 26.9109558184 +67.6161640771 29.6409756951 +69.8704082668 31.7205007486 +71.4163824096 33.5279613826 +71.7004339565 34.7610592404 +70.2644325048 35.1322162524 +68.2079486288 35.1296903603 +65.4970372207 34.7081418689 +63.4093219116 34.5351928901 +61.9476003945 34.640657993 +60.9936048388 34.9844954144 +60.2292363644 35.4018563908 +58.5007734559 35.2066456117 +56.6058670171 34.8500529937 +55.4337381609 34.8855813388 +54.1935202461 34.8349248059 +53.8235348463 35.3114159573 +53.5995264314 35.865084637 +52.0357920248 35.4883254934 +51.5580211421 35.8152124491 +50.8351811543 35.9459007047 +50.1131211361 36.048361877 +49.6500963364 36.3117817212 +48.7818695121 36.2519932836 +47.7879379205 36.0660155658 +48.0166363837 36.7828772692 +48.4486543983 37.6516770124 +48.1213647015 37.9201539792 +56.3841645066 45.0303944871 +133.952705595 108.370016727 +256.508483143 210.119451493 +366.571028495 303.901147048 +428.62810606 359.477769809 +803.224559752 681.173059482 +2823.99809512 2420.63883705 +5305.82107784 4594.9757576 +6666.51790023 5830.66806473 +6501.22527652 5740.24098396 +6415.73223967 5716.45930104 +6274.39844611 5639.3919895 +6159.7488071 5582.62850965 +6342.5785668 5794.23360729 +6149.84086318 5660.95846331 +5916.02678919 5485.24460979 +5684.59738289 5307.02869165 +5553.02604008 5218.13757356 +5539.40063526 5237.60607938 +5462.95364487 5195.57779275 +5243.29100192 5014.18399775 +5115.69087875 4917.5176582 +4910.27777459 4742.96406446 +4720.34232202 4580.12798408 +4613.56000834 4495.31475767 +4452.23445456 4354.94256644 +4457.32360833 4375.42994928 +4487.65639604 4419.47871217 +4490.90829192 4435.61785883 +4399.87081736 4357.05149815 +4435.10208131 4402.04345186 +4350.45756095 4326.62537725 +4071.28881288 4055.79641247 +3920.78394292 3911.23320965 +4002.12203685 3996.63717469 +4088.12653875 4085.6362083 +4266.64419055 4265.99442148 +4058.87609982 4058.87609982 +4066.62658644 4066.00727391 +4188.05774689 4185.506567 +4249.02605867 4243.20282555 +4109.54536772 4099.53482199 +4089.60755372 4074.04545307 +4147.30297303 4124.58370113 +4133.00896287 4102.20209479 +4090.76923275 4050.95807362 +4129.47138238 4078.63082218 +4092.82352138 4030.64424777 +4132.10278988 4056.18435121 +4037.80894232 3949.5732255 +4045.48069978 3941.79529524 +4054.4527297 3934.01817679 +3971.48343539 3836.15837646 +3945.75188708 3792.90012693 +3956.24013209 3783.37114596 +3991.77464104 3796.40338826 +4039.38444686 3819.31292105 +3936.32250571 3698.93319225 +3873.5319221 3616.25348401 +3810.2019465 3532.75777555 +3816.53167701 3513.13599706 +3841.26025867 3509.16575193 +3858.68095469 3497.15272665 +3924.97437716 3527.74362993 +3987.52624011 3552.9119184 +4068.5993371 3592.35987258 +4031.79142284 3526.28430152 +4034.63867331 3494.09951162 +3934.50787711 3372.53151917 +3922.04076815 3326.07918835 +4024.07798886 3374.87570596 +4002.49604201 3318.2194984 +4082.0914681 3343.853616 +4095.93965459 3313.68482971 +3994.98529673 3190.53700829 +3983.58463383 3139.10763073 +3933.20709991 3056.67609477 +3971.77754283 3042.55809355 +3917.40256429 2956.50132322 +3969.16988754 2949.66800904 +3929.49009442 2873.84712505 +3980.40115285 2863.26092482 +4127.74604225 2918.7571671 +4191.92971063 2911.95917749 +4210.33449888 2871.44127059 +4256.72370386 2848.30418444 +4327.91890287 2839.37026834 +4260.57636499 2738.6458087 +4282.43553066 2695.02396917 +4280.0468035 2635.0600367 +4375.22144532 2633.07408655 +4465.36536527 2624.67587447 +4396.78621817 2521.89303279 +4339.0727253 2426.37864685 +4276.0659883 2328.91251707 +4162.32332397 2205.69531882 +4124.32559729 2124.18471599 +4084.38326967 2042.19163483 +3974.13304687 1926.69788575 +3929.25066638 1844.67149282 +3881.65167081 1762.23294473 +3696.93570459 1620.6299606 +3440.90952814 1454.1912297 +3192.99944806 1298.70987386 +3060.81585729 1195.95602643 +2993.61381292 1121.42743105 +2895.93548322 1037.81046048 +2842.7788589 972.287660718 +2757.01094735 897.595006436 +2636.3766464 814.685208887 +2536.2607043 741.530829166 +2458.93639189 677.774732023 +2387.85125196 618.021376312 +2359.04857832 570.705516353 +2300.77575445 517.561940789 +2289.39969653 475.992949069 +2199.63868117 419.710849822 +2188.11907369 379.962892145 +2114.79287815 330.82648468 +2035.11272621 283.232958198 +1970.492064 240.142568678 +1842.80440378 192.625514567 +1765.48538876 153.872193396 +1548.28138804 108.002645195 +1340.68785238 70.1661793962 +932.492465019 32.5435166582 +242.916385412 4.2394753173 +277 360 -35 -26 PSPS_PV3_P2_SLICE_0 6740.16396051 ipp100.0 +263 277 -35 -26 PSPS_PV3_P2_SLICE_1 6493.73772466 ipp100.1 +161 263 -35 -26 PSPS_PV3_P2_SLICE_2 6476.44614946 ipp101.0 +0 161 -35 -26 PSPS_PV3_P2_SLICE_3 6147.30653759 ipp101.1 +275 360 -26 -21 PSPS_PV3_P2_SLICE_4 7248.08059501 ipp102.0 +261 275 -26 -21 PSPS_PV3_P2_SLICE_5 7368.77213287 ipp102.1 +157 261 -26 -21 PSPS_PV3_P2_SLICE_6 7055.64291716 ipp103.0 +0 157 -26 -21 PSPS_PV3_P2_SLICE_7 6489.9615345 ipp103.1 +274 360 -21 -17 PSPS_PV3_P2_SLICE_8 5307.57097422 ipp104.0 +258 274 -21 -17 PSPS_PV3_P2_SLICE_9 5503.72396469 ipp104.1 +154 258 -21 -17 PSPS_PV3_P2_SLICE_10 5241.01318765 ipp100.0 +0 154 -21 -17 PSPS_PV3_P2_SLICE_11 4906.04201078 ipp100.1 +271 360 -17 -12 PSPS_PV3_P2_SLICE_12 6240.38892037 ipp101.0 +254 271 -17 -12 PSPS_PV3_P2_SLICE_13 6244.03386307 ipp101.1 +124 254 -17 -12 PSPS_PV3_P2_SLICE_14 5947.18009043 ipp102.0 +0 124 -17 -12 PSPS_PV3_P2_SLICE_15 5318.50558829 ipp102.1 +266 360 -12 -7 PSPS_PV3_P2_SLICE_16 5651.84031514 ipp103.0 +251 266 -12 -7 PSPS_PV3_P2_SLICE_17 5646.0561142 ipp103.1 +128 251 -12 -7 PSPS_PV3_P2_SLICE_18 5501.19907856 ipp104.0 +0 128 -12 -7 PSPS_PV3_P2_SLICE_19 5143.42507696 ipp104.1 +263 360 -7 -1 PSPS_PV3_P2_SLICE_20 6217.20369795 ipp100.0 +248 263 -7 -1 PSPS_PV3_P2_SLICE_21 6222.74501514 ipp100.1 +127 248 -7 -1 PSPS_PV3_P2_SLICE_22 6215.82623529 ipp101.0 +0 127 -7 -1 PSPS_PV3_P2_SLICE_23 6122.19688582 ipp101.1 +263 360 -1 4 PSPS_PV3_P2_SLICE_24 5271.930264 ipp102.0 +244 263 -1 4 PSPS_PV3_P2_SLICE_25 5408.21640873 ipp102.1 +122 244 -1 4 PSPS_PV3_P2_SLICE_26 5214.37824249 ipp103.0 +0 122 -1 4 PSPS_PV3_P2_SLICE_27 4925.06227255 ipp103.1 +262 360 4 9 PSPS_PV3_P2_SLICE_28 5137.93326807 ipp104.0 +243 262 4 9 PSPS_PV3_P2_SLICE_29 5136.61160564 ipp104.1 +126 243 4 9 PSPS_PV3_P2_SLICE_30 5127.23534274 ipp100.0 +0 126 4 9 PSPS_PV3_P2_SLICE_31 5049.54392815 ipp100.1 +258 360 9 15 PSPS_PV3_P2_SLICE_32 6159.23766446 ipp101.0 +243 258 9 15 PSPS_PV3_P2_SLICE_33 6028.55503082 ipp101.1 +127 243 9 15 PSPS_PV3_P2_SLICE_34 6004.94591403 ipp102.0 +0 127 9 15 PSPS_PV3_P2_SLICE_35 5798.10750937 ipp102.1 +255 360 15 21 PSPS_PV3_P2_SLICE_36 5758.51058722 ipp103.0 +240 255 15 21 PSPS_PV3_P2_SLICE_37 5793.04980469 ipp103.1 +122 240 15 21 PSPS_PV3_P2_SLICE_38 5697.71941209 ipp104.0 +0 122 15 21 PSPS_PV3_P2_SLICE_39 5477.79934692 ipp104.1 +251 360 21 28 PSPS_PV3_P2_SLICE_40 6424.79206586 ipp100.0 +233 251 21 28 PSPS_PV3_P2_SLICE_41 6323.19407272 ipp100.1 +113 233 21 28 PSPS_PV3_P2_SLICE_42 6188.67031217 ipp101.0 +0 113 21 28 PSPS_PV3_P2_SLICE_43 5812.46483278 ipp101.1 +248 360 28 35 PSPS_PV3_P2_SLICE_44 6272.04837203 ipp102.0 +228 248 28 35 PSPS_PV3_P2_SLICE_45 6022.45598221 ipp102.1 +114 228 28 35 PSPS_PV3_P2_SLICE_46 6030.8351295 ipp103.0 +0 114 28 35 PSPS_PV3_P2_SLICE_47 5679.11011386 ipp103.1 +247 360 35 42 PSPS_PV3_P2_SLICE_48 5511.00540519 ipp104.0 +217 247 35 42 PSPS_PV3_P2_SLICE_49 5617.67864275 ipp104.1 +114 217 35 42 PSPS_PV3_P2_SLICE_50 5528.62885427 ipp100.0 +0 114 35 42 PSPS_PV3_P2_SLICE_51 5385.60569406 ipp100.1 +239 360 42 50 PSPS_PV3_P2_SLICE_52 5837.38097978 ipp101.0 +205 239 42 50 PSPS_PV3_P2_SLICE_53 5872.25277996 ipp101.1 +117 205 42 50 PSPS_PV3_P2_SLICE_54 5777.10199976 ipp102.0 +0 117 42 50 PSPS_PV3_P2_SLICE_55 5589.87236738 ipp102.1 +228 360 50 60 PSPS_PV3_P2_SLICE_56 6325.26457886 ipp103.0 +191 228 50 60 PSPS_PV3_P2_SLICE_57 6363.57689428 ipp103.1 +126 191 50 60 PSPS_PV3_P2_SLICE_58 6244.51773024 ipp104.0 +0 126 50 60 PSPS_PV3_P2_SLICE_59 6000.18480372 ipp104.1 +236 360 60 90 PSPS_PV3_P2_SLICE_60 5986.83767 ipp100.0 +179 236 60 90 PSPS_PV3_P2_SLICE_61 5963.32087529 ipp100.1 +120 179 60 90 PSPS_PV3_P2_SLICE_62 5984.41789492 ipp101.0 +0 120 60 90 PSPS_PV3_P2_SLICE_63 5871.42299783 ipp101.1 Index: trunk/tools/heather/pv3slicer/slicebatch_FO.py =================================================================== --- trunk/tools/heather/pv3slicer/slicebatch_FO.py (revision 39571) +++ trunk/tools/heather/pv3slicer/slicebatch_FO.py (revision 39571) @@ -0,0 +1,148 @@ +import astropy +import math +import numpy as np +from astropy.io import fits +hdu_list = fits.open('grid.cam.obj.fits') +image_data = hdu_list[0].data + +# these are all FITS images with very simple coordinates: RA = X - 180, DEC = Y - 90, with pixels of +# first [ ] is the dec +# second [ ] is the ra + +total = np.nansum(image_data) + +decslice = np.nansum(image_data,1, dtype='double') +#print decslice.shape +#for i in range(0,180): +# print i, decslice[i] + +datamachines = ['ipp100.0','ipp100.1' , 'ipp101.0', 'ipp101.1','ipp102.0','ipp102.1','ipp103.0','ipp103.1','ipp104.0','ipp104.1'] +numdata = len(datamachines) +dmlen = len(datamachines) +dmcnt =0 +#decboundaries from email (see end) + +decboundaries=[-28,-26,-24,-21,-19,-17,-14,-12,-9,-7,-4,-1,1,4,6,9,12,15,18,21,25,28,31,35,38,42,46,50,55,60,67,90] + +image_data_decfix = np.empty_like (image_data) +image_data_decfix[:] = image_data + +for d in range (0,180): + conv = math.cos((d-90)*math.pi/180.) + image_data_decfix[d,:]=image_data[d,:]*conv + + +decslice2 = np.nansum(image_data_decfix,1,dtype='double') +for i in range (0,180): + print decslice[i], decslice2[i] + + +image_data [:] = image_data_decfix + +decmin = -55 +xmin = decmin + 90 +#print "full total", np.nansum(image_data,dtype='double') +actualtotal = np.nansum(image_data[xmin:180,0:360], dtype='double') +#ok! I figured it out: np.nansum[x:x] gives 0, so to get a 1 pixel slice, need [x:x+1] +#print "total between -55 and 90 dec " , actualtotal +#print "other total between -55 and 90dec ", np.nansum(decslice[decmin:180],dtype='double') +j = 0 +sumtotal = 0 +slicecnt =0 +for dec in decboundaries: + i = dec+90 + if dec == 90: + j = 1 + if j == 0: + imin = decmin+90 + j = 1 + else: + j = 0 + sumcheck = np.nansum(image_data[imin:i],dtype='double') + #print imin, i, decmin, dec, sumcheck + decmin = dec + sumtotal = sumtotal + sumcheck + segsize = sumcheck/2. + jj =0 + sumtotalra = 0 + sumcheckra = 0 + armin = 0 + armax = 0 + newsumcheckra = 0 + for ar in range (1,361): + #note, this is not how gene defined it, however, he's completely wrong I think... + oldsumcheckra = newsumcheckra + newsumcheckra = np.nansum(image_data[imin:i,armin:ar],dtype='double') + # print "check",imin, i, armin, ar, armax, sumcheckra, newsumcheckra, segsize +# if ar == 360: +# print newsumcheckra + if (newsumcheckra > segsize or ar == 360): + # print the previous one + + armax = ar +# print imin, i, armin, armax, newsumcheckra, "here" +# print 360-armax, 360-armin, imin-90, i-90 + ramin= 360-armax + ramax = 360-armin + decccmin=imin-90 + decccmax = i-90 + PSPS = "PSPS_PV3_OB_ra"+str(360-armax)+"to"+str(360-armin)+"dec"+str(imin-90)+"to"+str(i-90) + PSPS2 = "PSPS_PV3_OB_SLICE_"+str(slicecnt) + + print str(ramin).ljust(5), str(ramax).ljust(5),str(decccmin).ljust(5), str(decccmax).ljust(5),PSPS2,newsumcheckra, datamachines[dmcnt] + dmcnt = ( dmcnt + 1 ) % dmlen + sumtotalra = newsumcheckra + sumtotalra +# sumtotalra = newsumcheckra + armin = ar + sumcheckra = 0 + slicecnt=slicecnt+1 +# sumcheckra = np.nansum(image_data[imin:i][armin:ar],dtype='double') + #calnew + else: + + sumcheckra = newsumcheckra + # print "total ra sizes for decmin: " + str(decccmin)+", decmax: "+str(decccmax)+" expected: " + str(sumcheck)+" sum of slices: "+ str(sumtotalra) + #print "--------" +#print "these should match" ,sumtotal, actualtotal + +#decd +for i in range(0,180): + for j in range(0,360): + ra = j - 180 + dec = i - 90 + #print ra, dec, image_data[i][j] + +#Dec Boundaries from email: +#-54.82 3.02e+12 +#-28.68 3.44e+12 +#-26.41 3.45e+12 +#-24.12 3.47e+12 +#-21.88 3.47e+12 +#-19.55 3.45e+12 +#-17.20 3.47e+12 +#-14.78 3.45e+12 +#-12.24 3.44e+12 +# -9.64 3.49e+12 +# -7.00 3.45e+12 +# -4.29 3.44e+12 +# -1.40 3.47e+12 +# +1.38 3.47e+12 +# +4.13 3.45e+12 +# +6.91 3.48e+12 +# +9.78 3.46e+12 +#+12.70 3.48e+12 +#+15.72 3.43e+12 +#+18.79 3.44e+12 +#+21.93 3.44e+12 +#+25.24 3.45e+12 +#+28.59 3.42e+12 +#+31.95 3.46e+12 +#+35.44 3.44e+12 +#+38.98 3.46e+12 +#+42.73 3.45e+12 +#+46.73 3.46e+12 +#+50.90 3.45e+12 +#+55.41 3.48e+12 +#+60.62 3.46e+12 +#+67.83 3.42e+12 +#+90.00 nan Index: trunk/tools/heather/pv3slicer/slicebatch_FW.py =================================================================== --- trunk/tools/heather/pv3slicer/slicebatch_FW.py (revision 39571) +++ trunk/tools/heather/pv3slicer/slicebatch_FW.py (revision 39571) @@ -0,0 +1,148 @@ +import astropy +import math +import numpy as np +from astropy.io import fits +hdu_list = fits.open('grid.ff.obj.fits') +image_data = hdu_list[0].data + +# these are all FITS images with very simple coordinates: RA = X - 180, DEC = Y - 90, with pixels of +# first [ ] is the dec +# second [ ] is the ra + +total = np.nansum(image_data) + +decslice = np.nansum(image_data,1, dtype='double') +#print decslice.shape +#for i in range(0,180): +# print i, decslice[i] + +datamachines = ['ipp100.0','ipp100.1' , 'ipp101.0', 'ipp101.1','ipp102.0','ipp102.1','ipp103.0','ipp103.1','ipp104.0','ipp104.1'] +numdata = len(datamachines) +dmlen = len(datamachines) +dmcnt =0 +#decboundaries from email (see end) + +decboundaries=[-28,-26,-24,-21,-19,-17,-14,-12,-9,-7,-4,-1,1,4,6,9,12,15,18,21,25,28,31,35,38,42,46,50,55,60,67,90] + +image_data_decfix = np.empty_like (image_data) +image_data_decfix[:] = image_data + +for d in range (0,180): + conv = math.cos((d-90)*math.pi/180.) + image_data_decfix[d,:]=image_data[d,:]*conv + + +decslice2 = np.nansum(image_data_decfix,1,dtype='double') +for i in range (0,180): + print decslice[i], decslice2[i] + + +image_data [:] = image_data_decfix + +decmin = -55 +xmin = decmin + 90 +#print "full total", np.nansum(image_data,dtype='double') +actualtotal = np.nansum(image_data[xmin:180,0:360], dtype='double') +#ok! I figured it out: np.nansum[x:x] gives 0, so to get a 1 pixel slice, need [x:x+1] +#print "total between -55 and 90 dec " , actualtotal +#print "other total between -55 and 90dec ", np.nansum(decslice[decmin:180],dtype='double') +j = 0 +sumtotal = 0 +slicecnt =0 +for dec in decboundaries: + i = dec+90 + if dec == 90: + j = 1 + if j == 0: + imin = decmin+90 + j = 1 + else: + j = 0 + sumcheck = np.nansum(image_data[imin:i],dtype='double') + #print imin, i, decmin, dec, sumcheck + decmin = dec + sumtotal = sumtotal + sumcheck + segsize = sumcheck/2. + jj =0 + sumtotalra = 0 + sumcheckra = 0 + armin = 0 + armax = 0 + newsumcheckra = 0 + for ar in range (1,361): + #note, this is not how gene defined it, however, he's completely wrong I think... + oldsumcheckra = newsumcheckra + newsumcheckra = np.nansum(image_data[imin:i,armin:ar],dtype='double') + # print "check",imin, i, armin, ar, armax, sumcheckra, newsumcheckra, segsize +# if ar == 360: +# print newsumcheckra + if (newsumcheckra > segsize or ar == 360): + # print the previous one + + armax = ar +# print imin, i, armin, armax, newsumcheckra, "here" +# print 360-armax, 360-armin, imin-90, i-90 + ramin= 360-armax + ramax = 360-armin + decccmin=imin-90 + decccmax = i-90 + PSPS = "PSPS_PV3_OB_ra"+str(360-armax)+"to"+str(360-armin)+"dec"+str(imin-90)+"to"+str(i-90) + PSPS2 = "PSPS_PV3_OB_SLICE_"+str(slicecnt) + + print str(ramin).ljust(5), str(ramax).ljust(5),str(decccmin).ljust(5), str(decccmax).ljust(5),PSPS2,newsumcheckra, datamachines[dmcnt] + dmcnt = ( dmcnt + 1 ) % dmlen + sumtotalra = newsumcheckra + sumtotalra +# sumtotalra = newsumcheckra + armin = ar + sumcheckra = 0 + slicecnt=slicecnt+1 +# sumcheckra = np.nansum(image_data[imin:i][armin:ar],dtype='double') + #calnew + else: + + sumcheckra = newsumcheckra + # print "total ra sizes for decmin: " + str(decccmin)+", decmax: "+str(decccmax)+" expected: " + str(sumcheck)+" sum of slices: "+ str(sumtotalra) + #print "--------" +#print "these should match" ,sumtotal, actualtotal + +#decd +for i in range(0,180): + for j in range(0,360): + ra = j - 180 + dec = i - 90 + #print ra, dec, image_data[i][j] + +#Dec Boundaries from email: +#-54.82 3.02e+12 +#-28.68 3.44e+12 +#-26.41 3.45e+12 +#-24.12 3.47e+12 +#-21.88 3.47e+12 +#-19.55 3.45e+12 +#-17.20 3.47e+12 +#-14.78 3.45e+12 +#-12.24 3.44e+12 +# -9.64 3.49e+12 +# -7.00 3.45e+12 +# -4.29 3.44e+12 +# -1.40 3.47e+12 +# +1.38 3.47e+12 +# +4.13 3.45e+12 +# +6.91 3.48e+12 +# +9.78 3.46e+12 +#+12.70 3.48e+12 +#+15.72 3.43e+12 +#+18.79 3.44e+12 +#+21.93 3.44e+12 +#+25.24 3.45e+12 +#+28.59 3.42e+12 +#+31.95 3.46e+12 +#+35.44 3.44e+12 +#+38.98 3.46e+12 +#+42.73 3.45e+12 +#+46.73 3.46e+12 +#+50.90 3.45e+12 +#+55.41 3.48e+12 +#+60.62 3.46e+12 +#+67.83 3.42e+12 +#+90.00 nan Index: trunk/tools/heather/pv3slicer/slicebatch_P2.py =================================================================== --- trunk/tools/heather/pv3slicer/slicebatch_P2.py (revision 39571) +++ trunk/tools/heather/pv3slicer/slicebatch_P2.py (revision 39571) @@ -0,0 +1,148 @@ +import astropy +import math +import numpy as np +from astropy.io import fits +hdu_list = fits.open('grid.cam.meas.fits') +image_data = hdu_list[0].data + +# these are all FITS images with very simple coordinates: RA = X - 180, DEC = Y - 90, with pixels of +# first [ ] is the dec +# second [ ] is the ra + +total = np.nansum(image_data) + +decslice = np.nansum(image_data,1, dtype='double') +#print decslice.shape +#for i in range(0,180): +# print i, decslice[i] + +datamachines = ['ipp100.0','ipp100.1' , 'ipp101.0', 'ipp101.1','ipp102.0','ipp102.1','ipp103.0','ipp103.1','ipp104.0','ipp104.1'] +numdata = len(datamachines) +dmlen = len(datamachines) +dmcnt =0 +#decboundaries from email (see end) + +decboundaries=[-28,-26,-24,-21,-19,-17,-14,-12,-9,-7,-4,-1,1,4,6,9,12,15,18,21,25,28,31,35,38,42,46,50,55,60,67,90] + +image_data_decfix = np.empty_like (image_data) +image_data_decfix[:] = image_data + +for d in range (0,180): + conv = math.cos((d-90)*math.pi/180.) + image_data_decfix[d,:]=image_data[d,:]*conv + + +decslice2 = np.nansum(image_data_decfix,1,dtype='double') +for i in range (0,180): + print decslice[i], decslice2[i] + + +image_data [:] = image_data_decfix + +decmin = -35 +xmin = decmin + 90 +#print "full total", np.nansum(image_data,dtype='double') +actualtotal = np.nansum(image_data[xmin:180,0:360], dtype='double') +#ok! I figured it out: np.nansum[x:x] gives 0, so to get a 1 pixel slice, need [x:x+1] +#print "total between -55 and 90 dec " , actualtotal +#print "other total between -55 and 90dec ", np.nansum(decslice[decmin:180],dtype='double') +j = 0 +sumtotal = 0 +slicecnt =0 +for dec in decboundaries: + i = dec+90 + if dec == 90: + j = 1 + if j == 0: + imin = decmin+90 + j = 1 + else: + j = 0 + sumcheck = np.nansum(image_data[imin:i],dtype='double') + #print imin, i, decmin, dec, sumcheck + decmin = dec + sumtotal = sumtotal + sumcheck + segsize = sumcheck/4. + jj =0 + sumtotalra = 0 + sumcheckra = 0 + armin = 0 + armax = 0 + newsumcheckra = 0 + for ar in range (1,361): + #note, this is not how gene defined it, however, he's completely wrong I think... + oldsumcheckra = newsumcheckra + newsumcheckra = np.nansum(image_data[imin:i,armin:ar],dtype='double') + # print "check",imin, i, armin, ar, armax, sumcheckra, newsumcheckra, segsize +# if ar == 360: +# print newsumcheckra + if (newsumcheckra > segsize or ar == 360): + # print the previous one + + armax = ar +# print imin, i, armin, armax, newsumcheckra, "here" +# print 360-armax, 360-armin, imin-90, i-90 + ramin= 360-armax + ramax = 360-armin + decccmin=imin-90 + decccmax = i-90 + PSPS = "PSPS_PV3_OB_ra"+str(360-armax)+"to"+str(360-armin)+"dec"+str(imin-90)+"to"+str(i-90) + PSPS2 = "PSPS_PV3_P2_SLICE_"+str(slicecnt) + + print str(ramin).ljust(5), str(ramax).ljust(5),str(decccmin).ljust(5), str(decccmax).ljust(5),PSPS2,newsumcheckra, datamachines[dmcnt] + dmcnt = ( dmcnt + 1 ) % dmlen + sumtotalra = newsumcheckra + sumtotalra +# sumtotalra = newsumcheckra + armin = ar + sumcheckra = 0 + slicecnt=slicecnt+1 +# sumcheckra = np.nansum(image_data[imin:i][armin:ar],dtype='double') + #calnew + else: + + sumcheckra = newsumcheckra + # print "total ra sizes for decmin: " + str(decccmin)+", decmax: "+str(decccmax)+" expected: " + str(sumcheck)+" sum of slices: "+ str(sumtotalra) + #print "--------" +#print "these should match" ,sumtotal, actualtotal + +#decd +for i in range(0,180): + for j in range(0,360): + ra = j - 180 + dec = i - 90 + #print ra, dec, image_data[i][j] + +#Dec Boundaries from email: +#-54.82 3.02e+12 +#-28.68 3.44e+12 +#-26.41 3.45e+12 +#-24.12 3.47e+12 +#-21.88 3.47e+12 +#-19.55 3.45e+12 +#-17.20 3.47e+12 +#-14.78 3.45e+12 +#-12.24 3.44e+12 +# -9.64 3.49e+12 +# -7.00 3.45e+12 +# -4.29 3.44e+12 +# -1.40 3.47e+12 +# +1.38 3.47e+12 +# +4.13 3.45e+12 +# +6.91 3.48e+12 +# +9.78 3.46e+12 +#+12.70 3.48e+12 +#+15.72 3.43e+12 +#+18.79 3.44e+12 +#+21.93 3.44e+12 +#+25.24 3.45e+12 +#+28.59 3.42e+12 +#+31.95 3.46e+12 +#+35.44 3.44e+12 +#+38.98 3.46e+12 +#+42.73 3.45e+12 +#+46.73 3.46e+12 +#+50.90 3.45e+12 +#+55.41 3.48e+12 +#+60.62 3.46e+12 +#+67.83 3.42e+12 +#+90.00 nan Index: trunk/tools/heather/pv3slicer/slicebatch_ST.py =================================================================== --- trunk/tools/heather/pv3slicer/slicebatch_ST.py (revision 39571) +++ trunk/tools/heather/pv3slicer/slicebatch_ST.py (revision 39571) @@ -0,0 +1,148 @@ +import astropy +import math +import numpy as np +from astropy.io import fits +hdu_list = fits.open('grid.ff.obj.fits') +image_data = hdu_list[0].data + +# these are all FITS images with very simple coordinates: RA = X - 180, DEC = Y - 90, with pixels of +# first [ ] is the dec +# second [ ] is the ra + +total = np.nansum(image_data) + +decslice = np.nansum(image_data,1, dtype='double') +#print decslice.shape +#for i in range(0,180): +# print i, decslice[i] + +datamachines = ['ipp100.0','ipp100.1' , 'ipp101.0', 'ipp101.1','ipp102.0','ipp102.1','ipp103.0','ipp103.1','ipp104.0','ipp104.1'] +numdata = len(datamachines) +dmlen = len(datamachines) +dmcnt =0 +#decboundaries from email (see end) + +decboundaries=[-28,-26,-24,-21,-19,-17,-14,-12,-9,-7,-4,-1,1,4,6,9,12,15,18,21,25,28,31,35,38,42,46,50,55,60,67,90] + +image_data_decfix = np.empty_like (image_data) +image_data_decfix[:] = image_data + +for d in range (0,180): + conv = math.cos((d-90)*math.pi/180.) + image_data_decfix[d,:]=image_data[d,:]*conv + + +decslice2 = np.nansum(image_data_decfix,1,dtype='double') +for i in range (0,180): + print decslice[i], decslice2[i] + + +image_data [:] = image_data_decfix + +decmin = -55 +xmin = decmin + 90 +#print "full total", np.nansum(image_data,dtype='double') +actualtotal = np.nansum(image_data[xmin:180,0:360], dtype='double') +#ok! I figured it out: np.nansum[x:x] gives 0, so to get a 1 pixel slice, need [x:x+1] +#print "total between -55 and 90 dec " , actualtotal +#print "other total between -55 and 90dec ", np.nansum(decslice[decmin:180],dtype='double') +j = 0 +sumtotal = 0 +slicecnt =0 +for dec in decboundaries: + i = dec+90 + if dec == 90: + j = 1 + if j == 0: + imin = decmin+90 + j = 1 + else: + j = 0 + sumcheck = np.nansum(image_data[imin:i],dtype='double') + #print imin, i, decmin, dec, sumcheck + decmin = dec + sumtotal = sumtotal + sumcheck + segsize = sumcheck/2. + jj =0 + sumtotalra = 0 + sumcheckra = 0 + armin = 0 + armax = 0 + newsumcheckra = 0 + for ar in range (1,361): + #note, this is not how gene defined it, however, he's completely wrong I think... + oldsumcheckra = newsumcheckra + newsumcheckra = np.nansum(image_data[imin:i,armin:ar],dtype='double') + # print "check",imin, i, armin, ar, armax, sumcheckra, newsumcheckra, segsize +# if ar == 360: +# print newsumcheckra + if (newsumcheckra > segsize or ar == 360): + # print the previous one + + armax = ar +# print imin, i, armin, armax, newsumcheckra, "here" +# print 360-armax, 360-armin, imin-90, i-90 + ramin= 360-armax + ramax = 360-armin + decccmin=imin-90 + decccmax = i-90 + PSPS = "PSPS_PV3_OB_ra"+str(360-armax)+"to"+str(360-armin)+"dec"+str(imin-90)+"to"+str(i-90) + PSPS2 = "PSPS_PV3_OB_SLICE_"+str(slicecnt) + + print str(ramin).ljust(5), str(ramax).ljust(5),str(decccmin).ljust(5), str(decccmax).ljust(5),PSPS2,newsumcheckra, datamachines[dmcnt] + dmcnt = ( dmcnt + 1 ) % dmlen + sumtotalra = newsumcheckra + sumtotalra +# sumtotalra = newsumcheckra + armin = ar + sumcheckra = 0 + slicecnt=slicecnt+1 +# sumcheckra = np.nansum(image_data[imin:i][armin:ar],dtype='double') + #calnew + else: + + sumcheckra = newsumcheckra + # print "total ra sizes for decmin: " + str(decccmin)+", decmax: "+str(decccmax)+" expected: " + str(sumcheck)+" sum of slices: "+ str(sumtotalra) + #print "--------" +#print "these should match" ,sumtotal, actualtotal + +#decd +for i in range(0,180): + for j in range(0,360): + ra = j - 180 + dec = i - 90 + #print ra, dec, image_data[i][j] + +#Dec Boundaries from email: +#-54.82 3.02e+12 +#-28.68 3.44e+12 +#-26.41 3.45e+12 +#-24.12 3.47e+12 +#-21.88 3.47e+12 +#-19.55 3.45e+12 +#-17.20 3.47e+12 +#-14.78 3.45e+12 +#-12.24 3.44e+12 +# -9.64 3.49e+12 +# -7.00 3.45e+12 +# -4.29 3.44e+12 +# -1.40 3.47e+12 +# +1.38 3.47e+12 +# +4.13 3.45e+12 +# +6.91 3.48e+12 +# +9.78 3.46e+12 +#+12.70 3.48e+12 +#+15.72 3.43e+12 +#+18.79 3.44e+12 +#+21.93 3.44e+12 +#+25.24 3.45e+12 +#+28.59 3.42e+12 +#+31.95 3.46e+12 +#+35.44 3.44e+12 +#+38.98 3.46e+12 +#+42.73 3.45e+12 +#+46.73 3.46e+12 +#+50.90 3.45e+12 +#+55.41 3.48e+12 +#+60.62 3.46e+12 +#+67.83 3.42e+12 +#+90.00 nan