def plot_double_mur(data,
wedge=82,
mu_min=310.0,
mu_max=419.0,
name="out",
mag=0,
rsize=2.0,
musize=2.0):
""" !!! TAKE INTO ACOUNT mu WRAPAROUND AT 360.0 !!!"""
ra, dec = coor.lbToEq(data[:, 0], data[:, 1])
mu, nu = coor.EqToGC(ra, dec, wedge)
r_min, r_max = int(sc.ma.min(data[:, 2])), int(sc.ma.max(data[:, 2])) + 1
r_hist = np.histogram(data[:, 2], int((r_max - r_min) / rsize),
(r_min, r_max))
mu_hist = np.histogram(mu, int((mu_max - mu_min) / musize),
(mu_min, mu_max))
# plot r hist
fig = plt.figure(1)
plt.subplot(211)
plt.bar(r_hist[1][:-1], r_hist[0], rsize)
plt.xlabel("r, kpc")
# plot mu hist
plt.subplot(212)
plt.bar(mu_hist[1][:-1], mu_hist[0], musize)
plt.xlabel("mu")
plt.show()
plt.close('all')
def shift_sgr(filein="streamgen_bif50Good.txt", fileout="stream_50shift.txt"):
prime = [ -5.25124491e-03, 1.57254414e+00, -1.00216868e+02]
second = [ -7.76551199e-03, 2.31737724e+00, -1.41690141e+02]
#file1="/home/newbym2/Dropbox/Research/sgrLetter/"+filein
file1="/home/newbym2/Dropbox/Research/sgrLetter/"+filein
data = np.loadtxt(file1)
for i in range(len(data[:,0])):
data[i,0], data[i,1] = ac.lbToEq(data[i,0], data[i,1])
deldel = data[i,1] - (data[i,0]*data[i,0]*prime[0] + data[i,0]*prime[1] + prime[2])
data[i,1] = deldel + (data[i,0]*data[i,0]*second[0] + data[i,0]*second[1] + second[2])
data[i,0], data[i,1] = ac.EqTolb(data[i,0], data[i,1])
np.savetxt(fileout, data, delimiter=" ")
def get_stripe(wedge, filein):
stripe_data = []
skymap = sc.zeros((180, 360), float)
for line in fileinput.input(filein):
# Get Data
if line.strip()[0] == '': continue
if line.strip()[0] == '#': continue
holder = line.split(',')
l, b, g = eval(holder[0].strip()), eval(holder[1].strip()), eval(
holder[2].strip())
ra, dec = coor.lbToEq(l, b)
mu, nu = coor.EqToGC(ra, dec, wedge)
if abs(nu) < 1.25:
stripe_data.append([l, b, g])
# now build the histogram
l_i = int(ra)
b_i = int(dec) + 90
skymap[-b_i][l_i] = skymap[-b_i][l_i] + 1.0
if fileinput.filelineno() % 100000 == 0:
print "Line {0} complete".format(fileinput.filelineno())
return sc.array(stripe_data), skymap
def plot_stripe_mug(data, wedge, name="out", mag=0):
""" SPREAD OUT MORE!!! """
#l, b = data[:,0], data[:,1]
if mag == 1: g = data[:, 2]
else: g = coor.getg(data[:, 2])
ra, dec = coor.lbToEq(data[:, 0], data[:, 1])
mu, nu = coor.EqToGC(ra, dec, wedge)
x, y = g * sc.cos(mu * rad), g * sc.sin(mu * rad)
x_bins = int((np.ma.max(x) - np.ma.min(x)) / 0.5) + 1
y_bins = int((np.ma.max(y) - np.ma.min(y)) / 0.5) + 1
H, x, y = np.histogram2d(x, y, [x_bins, y_bins])
extent = [np.ma.min(y), np.ma.max(y), np.ma.max(x), np.ma.min(x)]
plt.figure(1)
sp = plt.subplot(111)
#plt.polar([0.0, np.ma.min(mu)*rad, np.ma.max(mu)*rad, 0.0], [0.0, 60.0, 60.0, 0.0])
plt.imshow(H, extent=extent, interpolation='nearest')
plt.colorbar(orientation='horizontal')
#plt.plot(x1,y1,'r-')
plt.setp(sp.get_xticklabels(), visible=False)
plt.setp(sp.get_yticklabels(), visible=False)
plt.savefig((name + ".ps"), papertype='letter')
plt.close('all')
def field_of_streams(xa = (0.0,360.0), ya=(-90.0, 90.0), normed=1, file=None, hname=""):
#xa = (110.0,230.0), ya=(-5.0, 60.0), normed=1):
path = "/usr/home/f/081/tug08879/Desktop/"
#file = "MSTO_North.csv"
hname = "_sgrtweaked"
if file != None:
data = np.loadtxt(path+file, delimiter=",", skiprows=1)
print "Loaded data"
# change coordinates
for i in range(data.shape[0]):
ra, dec = ac.lbToEq(data[i,0], data[i,1])
data[i,0], data[i,1] = ra, dec
print "Changed Coordinates"
#Wr, Br, Gr, Rr, Kr = 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
Wr, Br, Gr, Rr, Kr = 19.0, 21.0, 21.75, 22.5, 23.0
# bins for each color
W, B, G, R, K = [], [], [], [], []
for i in range(len(data[:,0])):
if data[i,2] < Wr: W.append(data[i,:])
elif data[i,2] < Br: B.append(data[i,:])
elif data[i,2] < Gr: G.append(data[i,:])
elif data[i,2] < Rr: R.append(data[i,:])
else: pass
if R == []: R = [[0.0,0.0,0.0]] #failsafe
if G == []: G = [[0.0,0.0,0.0]] #failsafe
if B == []: B = [[0.0,0.0,0.0]] #failsafe
B = np.array(B)
Bhist = pp.HistMaker(B[:,0], B[:,1], xsize=0.25, ysize=0.25, xarea=xa, yarea=ya)
Bhist.varea = (0.0,200.0)
Bhist.savehist("Bhist.csv")
G = np.array(G)
Ghist = pp.HistMaker(G[:,0], G[:,1], xsize=0.25, ysize=0.25, xarea=xa, yarea=ya)
Ghist.varea = (0.0,200.0)
Ghist.savehist("Ghist.csv")
R = np.array(R)
Rhist = pp.HistMaker(R[:,0], R[:,1], xsize=0.25, ysize=0.25, xarea=xa, yarea=ya)
Rhist.varea = (0.0,200.0)
Rhist.savehist("Rhist.csv")
else:
Bhist = pp.HistFromFile("Bhist"+hname+".csv")
Ghist = pp.HistFromFile("Ghist"+hname+".csv")
Rhist = pp.HistFromFile("Rhist"+hname+".csv")
#print np.ma.max(Bhist.H), np.ma.max(Ghist.H), np.ma.max(Rhist.H)
# Now correct for bin size changes due to declination
for j in range(Bhist.H.shape[0]):
decl = (j - 360)*0.25
mod = 1.0 / np.cos(decl*ma.pi/180.0)
Bhist.H[j,:] = Bhist.H[j,:]*mod
Ghist.H[j,:] = Ghist.H[j,:]*mod
Rhist.H[j,:] = Rhist.H[j,:]*mod
if normed == 1:
Bhist.H = Bhist.H / 25.0 #np.ma.max(Bhist.H) #Normalize individually
Ghist.H = Ghist.H / 12.0 #np.ma.max(Ghist.H)
Rhist.H = Rhist.H / 12.0 #np.ma.max(Rhist.H)
else:
#norm = max(np.ma.max(Bhist.H), np.ma.max(Ghist.H), np.ma.max(Rhist.H))
norm = 100.0
Bhist.H = norm_hist(Bhist.H, norm)
Ghist.H = norm_hist(Ghist.H, norm)
Rhist.H = norm_hist(Rhist.H, norm)
RGB = np.dstack( (Rhist.H, Ghist.H, Bhist.H) )
fig = plt.figure(dpi=300, figsize=(5.0,4.0) )
sp = plt.subplot(111)
plt.imshow(RGB, origin='lower')
plt.setp(sp.get_xticklabels(), visible=False)
plt.setp(sp.get_yticklabels(), visible=False)
plt.xlim(1075.0, 425.0)
plt.ylim(340.0, 640.0)
plt.savefig("FoS_smallbins.png", dpi=300)
def single_stripe_mur(data,
wedge,
mag=0,
scale=0,
color=1,
position=111,
mu_lim=None,
r_lim=None,
vm=None,
nu_flatten=0,
bar=1,
ring=1,
raw_coords=0):
""" change 'scale' to a string tag: None, sqrt, flatten, log? """
#l, b = data[:,0], data[:,1]
x_size, y_size = 0.5, 0.5
if mag == 1: r = coor.getr(data[:, 2])
else: r = data[:, 2]
print len(r)
if r_lim == None: r_lim = (np.ma.min(r), np.ma.max(r))
if raw_coords == 0:
ra, dec = coor.lbToEq(data[:, 0], data[:, 1])
mu, nu = coor.EqToGC(ra, dec, wedge)
else:
mu, nu = data[:, 0], data[:, 1]
if mu_lim == None: mu_lim = [np.ma.min(mu), np.ma.max(mu)]
#Checks if limits straddle mu=0.0
if (mu_lim[0] < 1.0) and (mu_lim[1] > 359.0):
mu_lim[0], mu_lim[1] = 0.0, 360.0
for i in mu:
if (i > 180.0) and (i < mu_lim[1]): mu_lim[1] = i
if (i < 180.0) and (i > mu_lim[0]): mu_lim[0] = i
mu_lim[0] = mu_lim[0] - 360.0
x, y = r * sc.cos(mu * rad), r * sc.sin(mu * rad)
x_bins = int((np.ma.max(x) - np.ma.min(x)) / x_size) + 1
y_bins = int((np.ma.max(y) - np.ma.min(y)) / y_size) + 1
H, x, y = np.histogram2d(
y, x, [y_bins, x_bins]) #, range=[[-155.0, 110.0],[-190.0, 0.0]])
extent = [np.ma.min(y), np.ma.max(y), np.ma.max(x), np.ma.min(x)]
if nu_flatten == 1:
print "!!! DOUBLE-CHECK NU FLATTENING! {0}".format(H.shape)
for i in range(H.shape[0]):
for j in range(H.shape[1]):
dist = ma.sqrt(((i - (H.shape[0] / 2.0)) * y_size)**2 +
(j * x_size)**2)
H[i, j] = H[i, j] / (dist * 2.5)
H = sc.sqrt(H) #sc.log10(H)
vm = 1.5
elif scale == 1:
H = sc.sqrt(H)
if vm == None: vm = 16.0
else:
if vm == None: vm = 300.0
""" Begin Figure """
#fig = plt.figure(frameon=False)
sp = plt.subplot(position)
if color == 1: cmap = spectral_wb
else: cmap = 'gist_yarg'
plt.imshow(H,
extent=extent,
interpolation='nearest',
vmin=0.0,
vmax=vm,
cmap=cmap)
if bar == 1:
bar = plt.colorbar(orientation='vertical')
if scale == 1:
bar_ticks = sc.arange(0.0, vm + 1.0, 2.0)
bar_labels = []
for i in range(len(bar_ticks)):
bar_labels.append(str(int(bar_ticks[i]**2)))
bar.set_ticks(bar_ticks)
bar.set_ticklabels(bar_labels, update_ticks=True)
""" Draw axes - mu """
mu_axis = gen_mu_axis(mu_lim, r_lim[1], ring)
plt.plot(mu_axis[0], mu_axis[1], 'k-') # Draws main axis
for i in range(len(mu_axis[2])):
x0 = [
1.0 * r_lim[1] * sc.cos(mu_axis[2][i] * rad),
1.1 * r_lim[1] * sc.cos(mu_axis[2][i] * rad)
]
y0 = [
1.0 * r_lim[1] * sc.sin(mu_axis[2][i] * rad),
1.1 * r_lim[1] * sc.sin(mu_axis[2][i] * rad)
]
plt.plot(x0, y0, 'k-') # Draws mu ticks
if mu_axis[3][i] <= 180.0: rot = -90.0 + mu_axis[3][i]
else: rot = -360.0 + mu_axis[3][i] - 90.0
if wedge < 40:
offset = 1.12 #This accounts for different whitespace on each side of 180
else:
offset = 1.14
x00, y00 = offset * r_lim[1] * sc.cos(
mu_axis[2][i] * rad), offset * r_lim[1] * sc.sin(
mu_axis[2][i] * rad)
#Format tick labels - this part adds whitespace to center labels on ticks
pre, mulbl = "$", str(mu_axis[3][i])
if len(mulbl) < 3:
for k in range(3 - len(mulbl)):
pre = " " + pre
if i == (len(mu_axis[2])) - 1:
plt.text(x00,
y00,
"$\mu=" + str(mu_axis[3][i]) + "^{\circ}$",
rotation=rot,
fontsize=12,
horizontalalignment='center') #float(mu_axis[3][i]) )
else:
plt.text(x00,
y00,
pre + str(mu_axis[3][i]) + "^{\circ}$",
rotation=rot,
fontsize=12,
horizontalalignment='center') #float(mu_axis[3][i]) )
""" Draw axes - r """
r_axis = gen_r_axis(mu_lim, r_lim)
plt.plot(r_axis[0], r_axis[1], 'k-')
mu1 = sc.arange(mu_lim[0] - 6.0, mu_lim[1] + 7.0, 1.0)
for tick in r_axis[2]:
x1, y1 = tick * sc.cos(mu1 * rad), tick * sc.sin(mu1 * rad)
if mu1[-1] < 90.0 or mu1[-1] > 360.0:
x2, y2 = tick * sc.cos((mu1[-1]) * rad), tick * sc.sin(
(mu1[-1]) * rad)
hl = 'right'
else:
x2, y2 = tick * sc.cos((mu1[1]) * rad), tick * sc.sin(
(mu1[1]) * rad)
hl = 'left'
plt.plot(x1[:7], y1[:7], "k-")
plt.plot(x1[-7:], y1[-7:], "k-")
if tick == r_axis[2][-1]:
plt.text(x2,
y2,
"$r=" + str(int(tick)) + "$",
rotation=0.0,
fontsize=12,
horizontalalignment=hl,
verticalalignment='bottom')
else:
plt.text(x2,
y2,
"$" + str(int(tick)) + "$",
rotation=0.0,
fontsize=12,
horizontalalignment=hl,
verticalalignment='bottom')
# Draw axes - g (TO BE DONE)
""" Clean up output """
y_lim = plt.ylim()
plt.ylim(y_lim[1], y_lim[0])
plt.setp(sp.get_xticklabels(), visible=False)
plt.setp(sp.get_yticklabels(), visible=False)
plt.setp(sp.get_xticklines(), visible=False)
plt.setp(sp.get_yticklines(), visible=False)
#ax = fig.add_axes([0, 0, 1, 1]) #These two lines supress the axes... supposedly
#ax.axis('off')
return sp
def field_of_streams(
xa=(0.0, 360.0), ya=(-90.0, 90.0), normed=1, file=None, hname=""):
#xa = (110.0,230.0), ya=(-5.0, 60.0), normed=1):
path = "/usr/home/f/081/tug08879/Desktop/"
#file = "MSTO_North.csv"
hname = "_sgrtweaked"
if file != None:
data = np.loadtxt(path + file, delimiter=",", skiprows=1)
print "Loaded data"
# change coordinates
for i in range(data.shape[0]):
ra, dec = ac.lbToEq(data[i, 0], data[i, 1])
data[i, 0], data[i, 1] = ra, dec
print "Changed Coordinates"
#Wr, Br, Gr, Rr, Kr = 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
Wr, Br, Gr, Rr, Kr = 19.0, 21.0, 21.75, 22.5, 23.0
# bins for each color
W, B, G, R, K = [], [], [], [], []
for i in range(len(data[:, 0])):
if data[i, 2] < Wr: W.append(data[i, :])
elif data[i, 2] < Br: B.append(data[i, :])
elif data[i, 2] < Gr: G.append(data[i, :])
elif data[i, 2] < Rr: R.append(data[i, :])
else: pass
if R == []: R = [[0.0, 0.0, 0.0]] #failsafe
if G == []: G = [[0.0, 0.0, 0.0]] #failsafe
if B == []: B = [[0.0, 0.0, 0.0]] #failsafe
B = np.array(B)
Bhist = pp.HistMaker(B[:, 0],
B[:, 1],
xsize=0.25,
ysize=0.25,
xarea=xa,
yarea=ya)
Bhist.varea = (0.0, 200.0)
Bhist.savehist("Bhist.csv")
G = np.array(G)
Ghist = pp.HistMaker(G[:, 0],
G[:, 1],
xsize=0.25,
ysize=0.25,
xarea=xa,
yarea=ya)
Ghist.varea = (0.0, 200.0)
Ghist.savehist("Ghist.csv")
R = np.array(R)
Rhist = pp.HistMaker(R[:, 0],
R[:, 1],
xsize=0.25,
ysize=0.25,
xarea=xa,
yarea=ya)
Rhist.varea = (0.0, 200.0)
Rhist.savehist("Rhist.csv")
else:
Bhist = pp.HistFromFile("Bhist" + hname + ".csv")
Ghist = pp.HistFromFile("Ghist" + hname + ".csv")
Rhist = pp.HistFromFile("Rhist" + hname + ".csv")
#print np.ma.max(Bhist.H), np.ma.max(Ghist.H), np.ma.max(Rhist.H)
# Now correct for bin size changes due to declination
for j in range(Bhist.H.shape[0]):
decl = (j - 360) * 0.25
mod = 1.0 / np.cos(decl * ma.pi / 180.0)
Bhist.H[j, :] = Bhist.H[j, :] * mod
Ghist.H[j, :] = Ghist.H[j, :] * mod
Rhist.H[j, :] = Rhist.H[j, :] * mod
if normed == 1:
Bhist.H = Bhist.H / 25.0 #np.ma.max(Bhist.H) #Normalize individually
Ghist.H = Ghist.H / 12.0 #np.ma.max(Ghist.H)
Rhist.H = Rhist.H / 12.0 #np.ma.max(Rhist.H)
else:
#norm = max(np.ma.max(Bhist.H), np.ma.max(Ghist.H), np.ma.max(Rhist.H))
norm = 100.0
Bhist.H = norm_hist(Bhist.H, norm)
Ghist.H = norm_hist(Ghist.H, norm)
Rhist.H = norm_hist(Rhist.H, norm)
RGB = np.dstack((Rhist.H, Ghist.H, Bhist.H))
fig = plt.figure(dpi=300, figsize=(5.0, 4.0))
sp = plt.subplot(111)
plt.imshow(RGB, origin='lower')
plt.setp(sp.get_xticklabels(), visible=False)
plt.setp(sp.get_yticklabels(), visible=False)
plt.xlim(1075.0, 425.0)
plt.ylim(340.0, 640.0)
plt.savefig("FoS_smallbins.png", dpi=300)