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 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 controlLoop():
print("Computing control...")
controller = PID.PID(model.kP, model.kI, model.kD)
progress_bar = progress.Progressbar(len(model.t) - 2)
for i in range(len(model.t) - 1):
progress_bar.printProgress(i)
if i >= 1: # calculate starting on second cycle
model.u[i + 1] = controller.update(model.x0[model.REFERENCE],
model.sp[i], model.t[i + 1])
ts = [model.t[i], model.t[i + 1]]
y = odeint(model.model, model.x0, ts, args=(model.u[i + 1], ))
for j in range(len(model.VARS)):
model.observables[j][i + 1] = y[-1][j]
model.x0[j] = y[-1][j]
print()
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 plot_profiles(path="/home/newbym2/Desktop/starfiles", savewedge=False, suffix=""):
files = glob.glob(path+"/stars*")
print files
suffix = "_rcut_IV"
data=[]
r_cut_low, r_cut_high = 40.0, ac.getr(22.5) #ac.getr(16.0), ac.getr(22.5) #20.0 OR 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])
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 (temp[2] < r_cut_low) or (temp[2] > r_cut_high): 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)) )
datar = np.array(data)
data = np.zeros(datar.shape, float)
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(datar[i,0], datar[i,1], 30.0))[3:5]
data[i,2] = ac.getg(datar[i,2], 4.2)
if count % 100 == 0: pb2.updatebar(float(count)/nStars)
pb2.endbar()
# loop over Lambda slices and plot Beta histograms
pb3 = pr.Progressbar(steps=len(files), prefix="Making Slices:", suffix=None,
symbol="#", active="=", brackets="[]", percent=True, size=40)
Ls = (200.0, 300.0, 2.5)
Lsteps = int((Ls[1]-Ls[0])/Ls[2])
for i in range(Lsteps):
Lname = str(Ls[0]+(Ls[2]*i) )[:6]+suffix
new = []
for j in range(len(data[:,0])):
if data[j,0] < Ls[0]+(Ls[2]*i): continue
if data[j,0] > Ls[0]+(Ls[2]*(i+1)): continue
if savewedge:
new.append([datar[j,0], datar[j,1], data[j,2]])
continue
new.append(data[j,1])
new = np.array(new)
if savewedge:
np.savetxt("stars-lambda-"+("00"+str(i))[-2:]+".txt", new, fmt='%.6f')
else:
Lhist, Ledges = np.histogram(new, 140, (-30.0, 40.0))
#output to file
outstuff = sc.array(zip(Ledges+0.25, Lhist))
np.savetxt(Lname+".out", outstuff)
#plot
plt.figure(1)
plt.bar(Ledges[:-1], Lhist, 0.5)
plt.title(Lname)
plt.xlabel("B")
plt.savefig(Lname+".png")
plt.close('all')
pb3.updatebar(float(i)/float(Lsteps))
print "Ended Successfully"
def stream_into_stripe(params,
sn,
N_stars,
batch=1000,
fileout="streamgen82.txt",
detection=1,
convolve=1,
append=0,
progbar=1,
primary=0):
""" sn is stream number"""
# Initialize file
if append == 0:
out = open(fileout, 'w')
out.write("# " + str(N_stars) + " stars, l,b,r \n")
out.close()
# Get constants
mu,R,theta,phi,sigma,wedge = \
params.mu[sn],params.R[sn],params.theta[sn],params.phi[sn],params.sigma[sn], params.wedge
print("Stream Parameters", mu, R, theta, phi, sigma, wedge)
u_min, u_max = get_stream_length(params, sn, accuracy=0.0001)
nu_min, nu_max = params.nu_lim[0], params.nu_lim[1]
mu_min, mu_max = params.mu_lim[0], params.mu_lim[1]
g_min, g_max = params.stripe[2][0], params.stripe[2][1]
#print "# - Generating Stream {0}, using parameters {1}, {2}, {3}, {4}, {5}".format(
# sn, mu, R, theta, phi, sigma)
N_out = 0
pb = pr.Progressbar(steps=N_stars,
prefix="Stream {0} progress:".format(sn),
suffix="Generating {0} Stars".format(N_stars),
symbol="#",
active="=",
brackets="[]",
percent=True,
size=40)
while N_out < N_stars:
mu_killed, nu_killed, mu_saved = 0, 0, 0
u, v, w = generate_stream(batch, u_min, u_max, sigma)
holder = []
for i in range(len(u)):
mu1, nu1, r1 = co.streamToGC(u[i], v[i], w[i], mu, R, theta * deg,
phi * deg, wedge)
if (nu1 < nu_min) or (nu1 > nu_max):
nu_killed = nu_killed + 1
continue
if (mu_max > 360.0):
if (mu1 > (mu_max - 360.0)) and (mu1 < mu_min):
mu_killed = mu_killed + 1
continue
else:
if (mu1 < mu_min) or (mu1 > mu_max):
mu_killed = mu_killed + 1
continue
if primary == 1:
if co.SDSS_primary(mu1, nu1, wedge, low=9, high=25) == 0:
continue
# Convolve
if convolve == 1:
r1 = star_convolution(r1, params.modfit)
# Detection
if detection == 1:
m_g = co.getg(r1)
if np.random.uniform() > sigmoid_error(m_g, params.modfit):
continue
if (co.getg(r1) < g_min) or (co.getg(r1) > g_max): continue
# When a point passes all the testsm add it to the set
l, b, r1 = co.GC2lbr(mu1, nu1, r1, wedge)
#co.stream2xyz(u[i],v[i],w[i],mu,R,theta,phi,wedge)
holder.append([round(l, 6), round(b, 6), round(r1, 6)])
N_out = N_out + 1
if N_out > N_stars:
slice = -1 * (N_out - N_stars)
holder = holder[:slice]
#print "#---Sliced {0} stars to make quota".format(str(-1*slice))
N_out = N_out + slice #Slice is negative
#append to file
if len(holder) != 0:
if fi.append_data(sc.array(holder), fileout, delimiter=" ") == 1:
#print "#---Stream Progress: {0} stars of {1} total stars generated".format(N_out, N_stars)
#print "# !!! - mu killed: {0}, mu_saved: {1}, nu_killed: {2}".format(mu_killed, mu_saved, nu_killed)
pb.updatebar(float(N_out) / float(N_stars))
print("#---Stream {0} generation succeeded, written as {1}".format(
sn, fileout))
return fileout
def sky_map(infile="/home/newbym2/Desktop/sdssN-stars/sgr_sky_data.csv",
dumb=1):
"""Map a variable in Lambda, Beta """
if dumb == 1:
data = np.loadtxt(infile, delimiter=",", skiprows=1)
l, b = data[:, 0], data[:, 1]
g_ext, r_ext = data[:, 4], data[:, 5]
g_sky, r_sky = data[:, 6], data[:, 7]
print np.ma.min(g_ext), np.ma.max(g_ext)
lam, bet = ac.lb2sgr(l, b, 30.0)[3:5]
plt.figure()
sc = plt.scatter(lam,
bet,
c=g_ext,
cmap=pp.spectral_wb,
edgecolors='none',
s=3,
alpha=0.3,
vmin=0,
vmax=0.4)
plt.colorbar(sc)
plt.xlim(320, 20.0)
plt.ylim(40.0, -70.0)
else:
path = "/home/newbym2/Desktop/FTO-stars/"
files = glob.glob(path + "FTO_All*")
files.append(path + "FTO_south_dirty.csv")
x_range, y_range = (20, 320), (-70, 40)
x_step, y_step = 0.5, 0.5
x_bins, y_bins = (x_range[1] - x_range[0]) / x_step, (
y_range[1] - y_range[0]) / y_step
try:
grid = np.loadtxt("reddening_out.txt")
except IOError:
grid = np.zeros((y_bins + 1, x_bins + 1), float)
for f in files:
data = np.loadtxt(f, delimiter=",", skiprows=1)
pb = pr.Progressbar(steps=data.shape[0],
prefix="Loading {0}".format(
f.split("/")[-1]),
suffix=None,
symbol="#",
active="=",
brackets="[]",
percent=True,
size=40)
for i in range(data.shape[0]):
lam, bet = (ac.lb2sgr(data[i, 0], data[i, 1], 30.0))[3:5]
gridx = (lam - x_range[0]) / x_step
gridy = (bet - y_range[0]) / y_step
if (gridx < 0) or (gridy < 0): continue
if (gridx > x_bins + 1) or (gridy > y_bins + 1): continue
if grid[gridy, gridx] < data[i, 13]:
grid[gridy, gridx] = data[i, 13]
if i % 1000 == 0:
pb.updatebar(float(i) / float(data.shape[0]))
pb.endbar()
np.savetxt("reddening_out.txt", grid, fmt="%.2f")
""" plot stuff """
grid = grid[:, ::-1]
grid = grid[::-1, :]
fig = plt.figure(dpi=120)
ax1 = fig.add_subplot(111)
im = ax1.imshow(grid,
cmap=pp.spectral_wb,
norm=None,
aspect=None,
interpolation='nearest',
alpha=None,
origin='lower',
extent=None,
vmin=0.0,
vmax=2.0)
cbar = plt.colorbar(mappable=im, aspect=30, orientation="horizontal")
xpos = np.arange(0.0, 601.0, 20.0)
xlab = []
for i in range(len(xpos)):
if i % 3 == 0:
xx = (xpos[i] * x_step) + x_range[0]
xlab.append(str(xx).split(".")[0])
else:
xlab.append("")
plt.xticks(xpos, xlab[::-1])
ypos = np.arange(0.0, 221.0, 20.0)
ylab = []
for i in range(len(ypos)):
if i % 2 == 0:
yy = (ypos[i] * y_step) + y_range[0]
ylab.append(str(yy).split(".")[0])
else:
ylab.append("")
plt.yticks(ypos, ylab[::-1])
plt.show()
def lambet_profiles(path="/home/newbym2/Desktop/sdssN-stars/",
glb="*bhbs_all*",
lj=0,
bj=1,
gj=2,
lbins=2.5,
bbins=0.5,
suffix="_bhbs",
coords="sgr"):
""" remixed from plot_profiles in utilities1 """
files = glob.glob(path + glb)
print files
data = []
g_cut_low, g_cut_high = 16.0, 22.5
pb = pr.Progressbar(steps=len(files),
prefix="Loading Stars:",
suffix=None,
symbol="#",
active="=",
brackets="[]",
percent=True,
size=40)
for f in files:
count = 0
stripedata = np.loadtxt(f, delimiter=",", skiprows=1)
for i in range(stripedata.shape[0]):
if stripedata[i, gj] < g_cut_low: continue
if stripedata[i, gj] > g_cut_high: continue
#if ac.SDSS_primary(temp[0],temp[1],wedge,fmt="lb",low=9,high=27)==0: continue
data.append(
[stripedata[i, lj], stripedata[i, bj], stripedata[i, gj]])
pb.updatebar(float(files.index(f) + 1) / float(len(files)))
data = np.array(data)
if coords == "sgr":
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(data.shape[0]):
count += 1
data[i, 0], data[i, 1] = ac.lb2sgr(data[i, 0], data[i, 1],
50.0)[3:5]
#data[i,2] = data[i,2]
if count % 1000 == 0: pb2.updatebar(float(count) / nStars)
elif coords == "lbr":
pass
#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])
else:
print "!!! Coordinate system not recognized !!!"
sys.exit(2)
pb2.endbar()
# loop over Lambda slices and plot Beta histograms
pb3 = pr.Progressbar(steps=len(files),
prefix="Making Slices:",
suffix=None,
symbol="#",
active="=",
brackets="[]",
percent=True,
size=40)
#Ls = (40.0, 130.0, lbins)
#Ls = (200.0, 300.0, lbins)
Ls = (201.25, 301.25, lbins) #for wedges offset by half a wedge
Lsteps = int((Ls[1] - Ls[0]) / Ls[2])
for i in range(Lsteps):
Lname = str(Ls[0] + (Ls[2] * i))[:6] + suffix
new = []
for j in range(len(data[:, 0])):
if data[j, 0] < Ls[0] + (Ls[2] * i): continue
if data[j, 0] > Ls[0] + (Ls[2] * (i + 1)): continue
new.append([data[j, 0], data[j, 1], data[j, 2]])
if len(new) < 1: continue
new = np.array(new)
#np.savetxt("stars-lambda-"+("00"+str(i))[-2:]+".txt", new, fmt='%.6f')
pb3.updatebar(float(i) / float(Lsteps))
Lhist, Ledges = np.histogram(new[:, 1], int(100 / bbins),
(-60.0, 40.0))
#output to file
outstuff = sc.array(zip(Ledges + (bbins / 2.0), Lhist))
np.savetxt(Lname + ".out", outstuff, fmt='%.2f')
pb3.endbar()
print "Ended Successfully"