def mag_plots(gmin=16.0, gmax=22.5):
path = "/home/mnewby/Desktop/"
#path="/home/newbym/Desktop/FTO-stars/"
#files = [path+"MSTO_North_plus20.csv", path+"MSTO_South_minus20.csv"]
#files = [path+"MSTO_North.csv", path+"MSTO_South.csv"]
files = [path + "blue_all.csv"]
out = []
for f in files:
data = np.loadtxt(f, delimiter=",", skiprows=1)
print "Loaded:", f
pb = pr.Progressbar(steps=data.shape[0],
prefix="Loading Stars:",
suffix=None,
symbol="#",
active="=",
brackets="[]",
percent=True,
size=40)
for i in range(data.shape[0]):
#if data[i,2] < ac.getr(16.0): continue
#if data[i,2] > ac.getr(22.5): continue
gmag = data[i, 3] # for BHB data
#gmag = data[i,2] #for MSTO data
if gmag < gmin: continue
if gmag > gmax: continue
lam, bet = (ac.lb2sgr(data[i, 0], data[i, 1], 30.0))[3:5]
if lam > 170.0:
#if bet > 10.0: continue
#if bet < 2.5: continue
if bet > -2.5: continue
if bet < -10.0: continue
else:
#if bet < -2.5: continue
#if bet > 5.0: continue
if bet > -5.0: continue
if bet < -12.5: continue
out.append([lam, bet, gmag])
if i % 10000 == 0: pb.updatebar(float(i) / float(data.shape[0]))
pb.endbar()
print "Transformed coordinates:", f
out = np.array(out)
hist = pp.HistMaker(out[:, 0],
out[:, 2],
0.5,
0.1,
yarea=(16.0, 22.5),
xarea=(0.0, 360.0))
hist.savehist(outfile="blue_faint_faint_hist.csv", fmt='%.1f')
hist.yflip = 0
hist.xflip = 1
hist.labels = (r"$\Lambda$", r"$g_0$")
hist.ticks = (sc.arange(20.0, 321.0, 20.0), sc.arange(16.0, 22.6, 0.5))
#hist.ticklabels = (None, ["16.0", "16.5", "17.0", "17.5", "18.0", "18.5", "19.0", "19.5", "20.0",
# "20.5", "21.0", "21.5", "22.0", "22.5"])
hist.varea = (0.0, 30.0)
pp.PlotHist(hist, imfile="blue_faint_faint.png", cbarO='horizontal')
pp.PlotHist(hist, imfile="blue_faint_faint.ps", cbarO='horizontal')
def make_total_plot(path="/home/newbym2/Desktop/starfiles", RGB=0, imfile=None,
rcut=None, vrange=None, outfile=None):
""" Makes a 2D histogram """
files = glob.glob(path+"/stars*")
print files
data=[]
pb = pr.Progressbar(steps=len(files), prefix="Loading Stars:", suffix=None,
symbol="#", active="=", brackets="[]", percent=True, size=40)
for f in files:
wedge = int(f.split("-")[1].split(".")[0])
count=0
stripedata = open(f, "r")
for line in stripedata:
count = count + 1
if count==1: continue
if line.strip()=="": continue
temp = line.split()
for i in range(len(temp)): temp[i] = float(temp[i])
if rcut != None:
if temp[2] < rcut[0]: continue
if temp[2] > rcut[1]: continue
if ac.SDSS_primary(temp[0],temp[1],wedge,fmt="lb",low=9,high=27)==0: continue
data.append(temp)
stripedata.close()
pb.updatebar(float(files.index(f)+1)/float(len(files)) )
data = np.array(data)
count, nStars, pb2 = 0, float(len(data[:,0])), pr.Progressbar(steps=100,
prefix="Changing Coordinates:", suffix=None, symbol="#", active="=",
brackets="[]", percent=True, size=40)
for i in range(len(data[:,0])):
count = count + 1
#data[i,0], data[i,1] = ac.lb2GC(data[i,0], data[i,1], 15)
#data[i,0], data[i,1] = ac.lbToEq(data[i,0], data[i,1])
data[i,0], data[i,1] = (ac.lb2sgr(data[i,0], data[i,1], 10.0))[3:5]
data[i,2] = ac.getg(data[i,2], 4.2)
if count % 100 == 0: pb2.updatebar(float(count)/nStars)
pb2.endbar()
if RGB==1: RGB_plot(data, imfile=imfile)
else:
allsky = pp.HistMaker(data[:,0], data[:,1], xsize=0.5, ysize=0.5,
#xarea=(200.0, 300.0), yarea=(-40.0, 30.0))
xarea=(230.0, 255.0), yarea=(-10.0, 15.0))
#allsky.scale = 'sqrt'
allsky.cmap="bw"
allsky.yflip = 1
if vrange != None: allsky.varea = (vrange[0], vrange[1])
if outfile==None: pp.PlotHist(allsky, "sgrall_GC.png")
else: pp.PlotHist(allsky, outfile)
#allsky.savehist("SDSSnorthGC.csv")
print "Ended Successfully"
def make_diff_hist():
""" Subtracts the simulated streams from the real data """
folder = "/home/newbym2/Dropbox/Research/sgrLetter/"
data = np.loadtxt("SDSSnorth.csv", delimiter=",")
sims = ["streamgen_bifGood.csv", "streamgen_bif50Good.csv", "streamgen_bifExtra.csv", "streamgen_bifShift.csv"]
outs = ["streamgen_ccdiff.png", "streamgen_cc50good.png", "streamgen_ccExtra.png", "streamgen_ccShift.png"]
#sim = np.loadtxt("simtotbif50m30_radec.csv", delimiter=",")
#sim = np.loadtxt("simtotbifm2_radec.csv", delimiter=",")
#sim = np.loadtxt("streamgen_bifExtra.csv", delimiter=",")
#sim = np.loadtxt("streamgen_bifGood.csv", delimiter=",")
#sim = np.loadtxt("streamgen_bif50Good.csv", delimiter=",")
for z in range(len(sims)):
sim = np.loadtxt(folder+sims[z], delimiter=",")
for i in range(sim.shape[0]):
for j in range(sim.shape[1]):
if data[i,j] < 1.0: sim[i,j] = 0.0
sky = pp.HistMaker([1,2], [1,2], xsize=0.5, ysize=0.5,
xarea=(120.0, 250.0), yarea=(-10.0, 50.0))
#new = sim #data - sim
new = data - sim
sky.H = new
sky.cmap = 'color'
sky.varea = (0.0,200.0)
pp.PlotHist(sky, "sim_"+outs[z])
#pp.PlotHist(sky, "data.png"); break
#pp.PlotHist(sky, "streamgen_bif50Good_bwdiff.png")
print "All done"
def plot_from_file(
infile="/home/newbym2/Newby-tools/paper-tools/FTO_All_hist.csv",
outfile="FTO_All.png"):
""" creates a image plot from a file """
#indata = np.loadtxt(infile, delimiter=",")
#hist = pp.HistMaker([0.0, 1.0], [0.0, 1.0], 0.5, 0.5, yarea=(-70.0, 40.0), xarea=(20.0, 320.0))
#hist = pp.HistMaker([0.0, 1.0], [0.0, 1.0], 1.0, 1.0, yarea=(-70.0, 40.0), xarea=(20.0, 320.0))
hist = pp.HistFromFile(infile,
0.5,
0.5,
yarea=(-70.0, 40.0),
xarea=(20.0, 320.0))
#hist.H = indata
hist.yflip = 1
hist.xflip = 1
hist.cmap = "bw"
hist.labels = (r"$\Lambda$", r"${\rm B}$")
hist.ticks = (range(20, 321, 20), [-60, -40, -20, 0, 20, 40])
#hist.varea=(0.0, 200.0) # FTOs, color
hist.varea = (0.0, 120.0) # FTOs, bw
#hist.varea=(0.0, 45.0) # BHBs
pp.PlotHist(hist,
imfile=outfile,
cbarO='horizontal',
cax=[0.1, 0.75, 0.8, 0.02])
def bhb_tools(infile="/home/newbym2/Desktop/sdssN-stars/sgr_bhbs_all.csv",
out=[],
gmin=15.0,
gmax=22.5,
suffix="All"):
""" bhb stuff """
data = np.loadtxt(infile, delimiter=",", skiprows=1)
ff = 1
if "c-c" in out:
ug0 = data[:, 2] - data[:, 3]
gr0 = data[:, 3] - data[:, 4]
plt.figure(ff)
ff += 1
plt.scatter(gr0, ug0, c="k", s=2)
plt.xlabel(r"$(g-r)_0$")
plt.ylabel(r"$(u-g)_0$")
plt.xlim(-0.5, 1.5)
plt.ylim(3.0, 0.0)
if "c-mag" in out:
#rr = ac.getr(data[:,3], 0.7) ## BHB M #Not working right?
gr0 = data[:, 3] - data[:, 4]
cmag = pp.HistMaker(gr0, data[:, 3], 0.01, 0.1)
cmag.yflip = 1
cmag.scale = 'sqrt'
cmag.varea = (0.0, 2000.0)
cmag.plot()
plt.show()
if "sgrplot" in out:
# use only primaries
sgr = []
for i in range(data.shape[0]):
#if ac.SDSS_primary(data[i,0],data[i,1],wedge,fmt="lb",low=9,high=27)==0: continue
if data[i, 3] > gmax: continue
if data[i, 3] < gmin: continue
sgr.append([data[i, 0], data[i, 1]])
sgr = np.array(sgr)
lam, bet = (ac.lb2sgr(sgr[:, 0], sgr[:, 1], 30.0))[3:5]
hist = pp.HistMaker(lam,
bet,
1.0,
1.0,
xarea=(20.0, 320.0),
yarea=(-70.0, 40.0))
hist.xflip = 1
hist.yflip = 1
hist.varea = (0.0, 6.0)
hist.savehist("sgr_bhbs.csv", fmt='%.1f')
#hist.ticks= [[20.0, 40.0, 60.0, 80.0, 100.0, 120.0, 140.0],[-40.0, -20.0, 0.0, 20.0]]
# mask the data
if "mask" in out:
mask = np.loadtxt("Rhist_sgr.csv", delimiter=",")
for i in range(len(mask[:, 0])):
for j in range(len(mask[0, :])):
if mask[i, j] == 0.0: hist.H[i, j] = 0.0
hist.savehist("bhb" + suffix + "_hist.csv", fmt='%.1f')
pp.PlotHist(hist,
imfile="BHB_" + suffix + ".png",
cbarO='horizontal',
cax=[0.1, 0.75, 0.8, 0.02])
def Mgiant_hist():
data = np.loadtxt("/home/newbym/Desktop/Mgiant_wise_sgr.csv",
delimiter=",",
skiprows=1)
print data.shape
#data[:,9] = -1.0*data[:,9]
hist = pp.HistMaker(data[:, 8], data[:, 9], 1.0, 1.0,
yarea=(-90.0, 90.0)) #, xarea=(20.0, 320.0) )
#lam, bet = ac.lb2sgr(data[:,2], data[:,3], 100.0 )[3:5] # use the proxy distance that is same as MSTOs
#hist = pp.HistMaker(lam, bet, 1.0, 1.0, yarea=(-90, 90))
hist.savehist(outfile="Mgiant_test3.csv", fmt='%.1f')
hist.yflip = 1
hist.xflip = 1
hist.labels = (r"$\Lambda$", r"$B$")
#hist.ticks = (None, [-40.0, -20.0, 0.0, 20.0, 40.0, 60.0, 80.0])
hist.varea = (0.0, 200.0)
pp.PlotHist(hist, imfile="Mgiant_sgr.png", cbarO='horizontal')
def make_sim_stream_plot(filein="stream_50shift.txt", RGB=0, imfile=None):
""" Makes the plot for the simulated streams
/home/newbym2/Dropbox/Research/sgrnorth_paper/sgr_separated_stars_MRT.txt"""
folder = "/home/newbym2/Dropbox/Research/sgrLetter/"
filename=folder + filein
#file2="/home/newbym2/Dropbox/Research/sgrnorth_paper/sgr_separated_stars_MRT.txt"
#file2="streamgen_sgr_sim.txt"
#file2="streamgen_sgrfidprim.txt"
file2 = folder+"streamgen_sfp2.txt"
data = np.loadtxt(filename)
data2 = []
datasgr = np.loadtxt(file2)
for i in range(len(data[:,0])):
#data[i,0], data[i,1] = ac.lbToEq(data[i,0], data[i,1])
#if ac.SDSS_primary(temp[0],temp[1],wedge,fmt="lb",low=9,high=27)==0: continue
data[i,0], data[i,1], data[i,2] = (ac.lb2sgr(data[i,0], data[i,1], data[i,2]))[3:]
lam, bet = new_shift_sgr(data[i,0], data[i,1]) #move 2nd stream to new position
data2.append([lam, bet, ac.getg(data[i,2], M=4.2)])
data2 = sc.array(data2)
for i in range(len(datasgr[:,0])):
datasgr[i,0], datasgr[i,1] = (ac.lb2sgr(datasgr[i,0], datasgr[i,1], 10.0))[3:5]
datasgr[i,2] = ac.getg(data[i,2], M=4.2)
"""
data2 = np.loadtxt(file2)
for i in range(len(data2[:,0])):
#data2[i,0], data2[i,1] = ac.lbToEq(data2[i,0], data2[i,1])
data2[i,0], data2[i,1] = (ac.lb2sgr(data2[i,0], data2[i,1], 10.0))[3:5]
"""
if RGB==1:
data3 = np.concatenate((data2,datasgr), axis=0)
#data3 = np.concatenate((data2,data), axis=0)
RGB_plot(data3, imfile=imfile, mask_data="Bhist_sgr.csv", muddle=0)
else:
sky = pp.HistMaker(np.concatenate([data[:,0],data2[:,0]]), np.concatenate([data[:,1],data2[:,1]]),
xsize=0.5, ysize=0.5, xarea=(120.0, 250.0), yarea=(-10.0, 50.0))
sky.varea = (0.0,200.0)
sky.H = sky.H + np.random.normal(60.0, 15.0, sky.H.shape)
#for i in range(sky.H.shape[0]):
# if i < 14: sky.H[i,:] = sky.H[i,:]*0.0; continue
# sky.H[i,:] = sky.H[i,:] + 45.0 - (0.5/1.0)*i
pp.PlotHist(sky, "streamgen_bifExtra_radec.png")
sky.savehist("streamgen_bifExtra.csv")
print "Ended Successfully"
def crotus_cut(path="/home/newbym2/Desktop/starfiles", cdata=None):
if cdata == None:
files = glob.glob(path+"/stars*")
data=[]
r_cut_low, r_cut_high = ac.getr(16.0), ac.getr(23.5) #30.0, 45.0
pb = pr.Progressbar(steps=len(files), prefix="Loading Stars:", suffix=None,
symbol="#", active="=", brackets="[]", percent=True, size=40)
for f in files:
wedge = int(f.split("-")[1].split(".")[0])
sdata = np.loadtxt(f, skiprows=1)
for i in range(sdata.shape[0]):
if (sdata[i,2] < r_cut_low) or (sdata[i,2] > r_cut_high): continue
if ac.SDSS_primary(sdata[i,0],sdata[i,1],wedge,fmt="lb",low=9,high=27)==0: continue
lam, bet = (ac.lb2sgr(sdata[i,0], sdata[i,1], 10.0))[3:5]
if (lam <230.0) or (lam > 255.0): continue
data.append([sdata[i,0], sdata[i,1], sdata[i,2], lam, bet])
pb.updatebar(float(files.index(f)+1)/float(len(files)) )
pb.endbar()
data = np.array(data)
np.savetxt("crotus_data.txt", data, fmt='%.6f')
else:
data = []
rdata = np.loadtxt(cdata)
rlim0 = 28.5 #ac.getr(22.5)
rlim1 = 45.0
for i in range(rdata.shape[0]):
if rdata[i,2] < rlim0: continue
if rdata[i,2] > rlim1: continue
data.append(rdata[i,:])
data = np.array(data)
#Now do analysis
sky = pp.HistMaker(data[:,3], data[:,4], xsize=0.25, ysize=0.25,
xarea=(230.0, 255.0), yarea=(-10.0, 15.0))
sky.varea = (0.0, 60.0)
sky.cmap="color"
#sky.scale = 'sqrt'
sky.yflip = 1
pp.PlotHist(sky, "crotus_cut.png")
#sky.savehist("streamgen_bifExtra.csv")
print "### - Done"
def FTO_skyplot(path="/home/mnewby/Desktop/",
gmin=16.0,
gmax=22.5,
multistep=None):
"""Make a skyplot with updated MSTO stars from SDSS """
#files = glob.glob(path+"stars*")
#files.append(path+"South/stars-79-new.txt")
#files.append(path+"South/stars-82-new.txt")
#files.append(path+"South/stars-86-new.txt")
#files = glob.glob(path+"FTO_All*")
#files.append(path+"FTO_south_dirty.csv")
#files = glob.glob(path+"*dirty*")
#files = [path+"MSTO_North_plus20.csv", path+"MSTO_South_minus20.csv"]
files = [path + "blue_all.csv"]
out = []
for f in files:
#data = np.loadtxt(f, skiprows=1)
data = np.loadtxt(f, delimiter=",", skiprows=1)
print "Loaded:", f
for i in range(data.shape[0]):
#if data[i,2] < ac.getr(16.0): continue
#if data[i,2] > ac.getr(22.5): continue
gmag = data[i, 3] # for FTO data
#gmag = data[i,2] #for MSTO data
if gmag < gmin: continue
if gmag > gmax: continue
#Distance is ambiguous for blue stars
#lam, bet = (ac.lb2sgr(data[i,0], data[i,1], ac.getr(data[i,3]) ) )[3:5]
lam, bet = (ac.lb2sgr(data[i, 0], data[i, 1], 10000.0))[3:5]
out.append([lam, bet, gmag])
print "Transformed coordinates:", f
out = np.array(out)
if multistep != None:
#runs = np.arange(10.0, 50.0, 5.0) #for distance
runs = np.arange(gmin, gmax, multistep)
runs = [
20.0 + 0.25, 20.66 + 0.25, 21.33 + 0.25, 22.0 + 0.25, 23.0 + 0.25
] #Belokurov 2006 + g-r=0.25
for run in runs:
print "Starting run", run
gslice = []
for i in range(out.shape[0]):
if out[i, 2] < run: continue
if out[i, 2] >= (run + multistep): continue
gslice.append(out[i, :])
gslice = np.array(gslice)
hist = pp.HistMaker(gslice[:, 0],
gslice[:, 1],
0.5,
0.5,
yarea=(-70.0, 40.0),
xarea=(20.0, 320.0))
hist.savehist(outfile="FTO_" + str(run) + "_hist.csv", fmt='%.1f')
hist.yflip = 1
hist.xflip = 1
hist.ticks = (None, [-60, -40.0, -20.0, 0.0, 20.0, 40.0])
hist.varea = (0.0, 12.0)
pp.PlotHist(hist,
imfile="FTO_" + str(run) + ".png",
cbarO='horizontal')
else:
hist = pp.HistMaker(out[:, 0],
out[:, 1],
1.0,
1.0,
yarea=(-70.0, 40.0),
xarea=(20.0, 320.0))
hist.savehist(outfile="BLUE_all_hist.csv", fmt='%.1f')
hist.yflip = 1
hist.xflip = 1
hist.labels = (r"$\Lambda$", "B")
hist.ticks = (None, [-40.0, -20.0, 0.0, 20.0, 40.0, 60.0, 80.0])
hist.varea = (0.0, 30.0)
pp.PlotHist(hist, imfile="BLUE_all.png", cbarO='horizontal')