def make_temperature_plots(s, output, cr):
pynbody.analysis.angmom.faceon(s.g)
sph.image(s.g,
qty="temp",
units="K",
width=100,
cmap="afmhot",
vmin=1e4,
vmax=1e6)
if cr:
plt.savefig('pioneer.%06d_temperature_faceon.png' % (output))
else:
plt.savefig('pioneer.%06d_temperature_faceon_nocr.png' % (output))
plt.clf()
pynbody.analysis.angmom.sideon(s.s)
sph.image(s.g,
qty="temp",
units="K",
width=100,
cmap="afmhot",
vmin=1e4,
vmax=1e6)
if cr:
plt.savefig('pioneer.%06d_temperature_sideon.png' % (output))
else:
plt.savefig('pioneer.%06d_temperature_sideon_nocr.png' % (output))
plt.clf()
def plots(property='rho', firsthalo=0, nhalos=1):
for halonum in xrange(firsthalo, nhalos):
halo = h.load_copy(halonum)
print "Halo %i loaded" % halonum
halo.physical_units()
halomass = sum(halo['mass'])
halo.g['rhosq'] = halo.g['rho'] * halo.g['rho']
print "Density squared computed"
#plot density profiles
#bin by position
pb.analysis.angmom.faceon(halo) #orient faceon wrt angular momentum
print "Orientation complete"
#skipping centering leads to IndexError in next steps
volproj = sph.image(halo.g,
qty=property,
units='g cm^-3',
av_z=True,
width=100,
cmap='RdYlBu',
title=r"%e $M_\odot$" % halomass,
filename='%i_volproj.png' % halonum) #slice
print "Volume weighted projection complete"
rhoproj = sph.image(halo.g,
qty=property,
units='g cm^-3',
av_z='rhosq',
width=100,
cmap='RdYlBu',
title=r"%e $M_\odot$" % halomass,
filename='%i_emsnproj.png' %
halonum) #integrated along z by default
print "Emission weighted projection complete"
def make_density_plots(s, output, cr):
pynbody.analysis.angmom.faceon(s.g)
sph.image(s.g,
qty="rho",
units="g cm^-3",
width=60,
cmap="magma",
vmin=5e-27,
vmax=1e-23)
if cr:
plt.savefig('pioneer.%06d_density_faceon.png' % (output))
else:
plt.savefig('pioneer.%06d_density_faceon_nocr.png' % (output))
plt.clf()
pynbody.analysis.angmom.sideon(s.s)
sph.image(s.g,
qty="rho",
units="g cm^-3",
width=60,
cmap="magma",
vmin=5e-27,
vmax=1e-23)
if cr:
plt.savefig('pioneer.%06d_density_sideon.png' % (output))
else:
plt.savefig('pioneer.%06d_density_sideon_nocr.png' % (output))
plt.clf()
def rho_proj(sim,
resolution=1000,
cmap="inferno",
units="Msol kpc^-2",
show_cbar=False,
**kwargs):
redshift = sim.properties['Redshift']
boxsize = sim.properties["boxsize"]
im = sph.image(sim.g,
width=boxsize,
resolution=resolution,
cmap=cmap,
units=units,
show_cbar=show_cbar,
**kwargs)
if not show_cbar:
cbar = plt.colorbar()
cbar.set_label(label=r"$\rho\ (\mathrm{M_\odot\ kpc^{-2}})$",
fontsize=20)
plt.ylabel(r"$y\ (\mathrm{cMpc})$", fontsize=20)
plt.xlabel(r"$x\ (\mathrm{cMpc})$", fontsize=20)
plt.title(r"$z = {0: .3f}$".format(redshift), fontsize=20)
return (im)
def metal_map(sim, metal, **kwargs):
redshift = sim.properties["Redshift"]
metal_arr = sim.g[metal]
metal_tot = np.sum(metal_arr)
metallicity = "{0}XH".format(metal)
if metal_tot != 0:
im = sph.image(sim.g,
qty=metallicity,
width=sim.properties["boxsize"],
cmap="RdPu",
show_cbar=False,
approximate_fast=False,
**kwargs)
cbar = plt.colorbar()
cbar.set_label(label="[{0}/{1}]".format(metal, "H"), fontsize=16)
plt.title("z = {1: .3f}".format(metal, redshift), fontsize=18)
plt.ylabel(r"$y\ (\mathrm{cMpc})$", fontsize=16)
plt.xlabel(r"$x\ (\mathrm{cMpc})$", fontsize=16)
return (im)
else:
print("Zero metals found! Can not make metallicity \
plot for: {0}".format(sim))
impData = s[pynbody.filt.Cuboid(str((rx-sbox/2.0)) + " kpc", str((ry-sbox/2.0)) + " kpc",str((rz-sbox/4.0)) + " kpc",
str((rx+sbox/2.0)) + " kpc", str((ry+sbox/2.0)) + " kpc",str((rz+sbox/4.0)) + " kpc")]
rect = [0.15,0.15,0.85,0.9]
coords= [-rx,-ry,-rz] # Translation requires negative of the coord
with pynbody.transformation.translate(impData,coords):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.yaxis.set_visible(False)
#ax.set_xlabel(fontsize=40)
fileOut="img_log_ax_Z-z=%.1lf-%i.pdf"% (z,i)
titleStr = "$Z_{\odot}$ - z = %.1lf" % z# + "\n[%.2lf %.2lf %.2lf]"%(rx,ry,rz)
print (titleStr)
sph.image(impData.g,qty="zsolar",width=smallbox,cmap="nipy_spectral", denoise=True ,av_z=False, subplot=ax,
log=True, vmax=1.0, vmin=1e-6, qtytitle=r"${\rm log}\, \langle Z\rangle/Z_{\odot}$", approximate_fast=False
); #vmin=0.006, vmax=1.0,
ax.set_xticks([-tic, 0, tic])
## ax.set_xticklabels(['-0.7','0','0.7'])
plt.savefig(fileOut,dpi=fig.dpi,bbox_inches='tight')
plt.close(fig)
fig = plt.figure()
ax = fig.add_subplot(111)
#ax.yaxis.set_visible(False)
#ax.set_xlabel(fontsize=40)
fileOut="img_log_ax_Z-f_pol-z=%.1lf-%i.pdf"% (z,i)
titleStr = r"$Z_{\odot}/f_{pol}$ - z = %.1lf" % z# + "\n[%.2lf %.2lf %.2lf]"%(rx,ry,rz)
print (titleStr)
sph.image(impData.g,qty="zEnhanced",width=smallbox,cmap="nipy_spectral", denoise=True ,av_z=False, subplot=ax,
log=True, vmax=1.0, vmin=1e-6, qtytitle=r"${\rm log}\, Z/Z_{\odot}$", approximate_fast=False
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pylab as plt
# load the snapshot and set to physical units
s = pynbody.load('testdata/g15784.lr.01024.gz')
s.physical_units()
# load the halos
h = s.halos()
# center on the largest halo and align the disk
pynbody.analysis.angmom.faceon(h[1])
#create an image of gas density integrated down the line of site (z axis)
sph.image(h[1].g, qty="rho", units="g cm^-2", width=100, cmap="Greys")
default="pynmovie.mp4",
)
parser.add_option("-e", action="store", dest="script", help="preprocessing script to run on each simulation.")
parser.add_option(
"-n", action="store_false", dest="video", help="Don't actually produce a video, just make pngs.", default=True
)
(opts, args) = parser.parse_args()
imgcount = 0
try:
(vmin, vmax) = [float(i) for i in opts.valrange.split()]
except AttributeError:
(vmin, vmax) = (None, None)
if opts.script != None:
sys.path.append(".")
scriptfile = __import__(opts.script.split(".")[0])
for i in args:
if opts.script != None:
scriptfile.process(i)
else:
sim = pyn.load(i)
ptypes = {"gas": sim.gas, "dm": sim.dm, "stars": sim.stars}
p_sph.image(ptypes[opts.ptype], units="m_p cm**-3", cmap="jet", vmin=vmin, vmax=vmax)
plt.savefig("%09d.png" % (imgcount), dpi=150)
imgcount += 1
if opts.video:
import envoy
vid = envoy.run("ffmpeg -qscale 1 -r %d -i %%09d.png %s" % (int(opts.fps), opts.outname))
for i in range(imgcount):
envoy.run("rm %09d.png" % (i))
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pylab as plt
# load the snapshot and set to physical units
s = pynbody.load('testdata/g15784.lr.01024.gz')
s.physical_units()
# load the halos
h = s.halos()
# center on the largest halo and align the disk
pynbody.analysis.angmom.sideon(h[1])
#create a simple slice showing the gas temperature
sph.image(h[1].g,qty="temp",width=50,cmap="YlOrRd", denoise=True,approximate_fast=False)
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pylab as plt
# load the snapshot and set to physical units
s = pynbody.load('testdata/g15784.lr.01024.gz')
s.physical_units()
# load the halos
h = s.halos()
# center on the largest halo and align the disk
pynbody.analysis.angmom.faceon(h[1])
#create a simple slice of gas density
sph.image(h[1].g,qty="rho",units="g cm^-3",width=100,cmap="Greys")
def render(sim,
filename=None,
r_band='i',
g_band='v',
b_band='u',
r_scale=0.5,
g_scale=1.0,
b_scale=1.0,
dynamic_range=2.0,
mag_range=None,
width=50,
starsize=None,
plot=True,
axes=None,
ret_im=False,
clear=True,
ret_range=False):
'''
Make a 3-color image of stars.
The colors are based on magnitudes found using stellar Marigo
stellar population code. However there is no radiative transfer
to account for dust.
Returns: If ret_im=True, an NxNx3 array representing an RGB image
**Optional keyword arguments:**
*filename*: string (default: None)
Filename to be written to (if a filename is specified)
*r_band*: string (default: 'i')
Determines which Johnston filter will go into the image red channel
*g_band*: string (default: 'v')
Determines which Johnston filter will go into the image green channel
*b_band*: string (default: 'b')
Determines which Johnston filter will go into the image blue channel
*r_scale*: float (default: 0.5)
The scaling of the red channel before channels are combined
*g_scale*: float (default: 1.0)
The scaling of the green channel before channels are combined
*b_scale*: float (default: 1.0)
The scaling of the blue channel before channels are combined
*width*: float in kpc (default:50)
Sets the size of the image field in kpc
*starsize*: float in kpc (default: None)
If not None, sets the maximum size of stars in the image
*ret_im*: bool (default: False)
if True, the NxNx3 image array is returned
*ret_range*: bool (default: False)
if True, the range of the image in mag arcsec^-2 is returned.
*plot*: bool (default: True)
if True, the image is plotted
*axes*: matplotlib axes object (deault: None)
if not None, the axes object to plot to
*dynamic_range*: float (default: 2.0)
The number of dex in luminosity over which the image brightness ranges
*mag_range*: float, float (default: None)
If provided, the brightest and faintest surface brightnesses in the range,
in mag arcsec^-2. Takes precedence over dynamic_range.
'''
if isinstance(width, str) or issubclass(width.__class__, _units.UnitBase):
if isinstance(width, str):
width = _units.Unit(width)
width = width.in_units(sim['pos'].units, **sim.conversion_context())
if starsize is not None:
smf = filt.HighPass('smooth', str(starsize) + ' kpc')
sim.s[smf]['smooth'] = array.SimArray(starsize, 'kpc', sim=sim)
r = image(sim.s,
qty=r_band + '_lum_den',
width=width,
log=False,
units="pc^-2",
clear=False,
noplot=True) * r_scale
g = image(sim.s,
qty=g_band + '_lum_den',
width=width,
log=False,
units="pc^-2",
clear=False,
noplot=True) * g_scale
b = image(sim.s,
qty=b_band + '_lum_den',
width=width,
log=False,
units="pc^-2",
clear=False,
noplot=True) * b_scale
# convert all channels to mag arcsec^-2
r = pynbody.plot.stars.convert_to_mag_arcsec2(r)
g = pynbody.plot.stars.convert_to_mag_arcsec2(g)
b = pynbody.plot.stars.convert_to_mag_arcsec2(b)
#r,g,b = nw_scale_rgb(r,g,b)
#r,g,b = nw_arcsinh_fit(r,g,b)
if mag_range is None:
rgbim, mag_max = pynbody.plot.stars.combine(r, g, b,
dynamic_range * 2.5)
mag_min = mag_max + 2.5 * dynamic_range
else:
mag_max, mag_min = mag_range
rgbim, mag_max = pynbody.plot.stars.combine(r, g, b, mag_min - mag_max,
mag_max)
if plot:
if clear:
plt.clf()
if axes is None:
axes = plt.gca()
if axes:
axes.imshow(rgbim[::-1, :],
extent=(-width / 2, width / 2, -width / 2, width / 2))
axes.set_xlabel('x [' + str(sim.s['x'].units) + ']')
axes.set_ylabel('y [' + str(sim.s['y'].units) + ']')
plt.draw()
if filename:
plt.axis('off')
plt.savefig(filename, dpi=1600, figsize=(25, 25), bbox_inches='tight')
if ret_im:
return rgbim
if ret_range:
return mag_max, mag_min
import matplotlib
matplotlib.use('Agg')
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pyplot as plt
import numpy as np
pynbody.config['number_of_threads'] = 1
s = pynbody.load('/oasis/scratch/comet/mjt29/temp_project/Romulus25/cosmo25p.768sg1bwK1BHe75.008192')
halos = s.halos(dosort=True)
#numbers = [18, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 102, 103, 104, 105, 106, 107, 108, 109, 110, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 151, 152, 153, 154, 155, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 186, 187, 188, 189, 190, 191, 192, 193, 194, 196, 197, 198, 199, 200, 201, 202, 204, 206, 207, 208, 209, 210, 213, 214, 215, 216, 218, 219, 222, 223, 224, 225, 226, 229, 230, 232, 233, 234, 235, 236, 237, 239, 242, 244, 245, 247, 249, 252, 253, 254, 258, 260, 264, 265, 266, 273, 276, 283, 304, 310, 335]
numbers = [38]
for i in range(len(numbers)):
h = halos.load_copy(i)
h.physical_units()
pynbody.analysis.halo.center(h, mode='hyb')
pynbody.plot.stars.render(h, width='40 kpc')
plt.savefig('stars_' + str(i) + '.png')
plt.close()
sph.image(h.g, qty="rho", units="g cm^-3", cmap="Greys")
plt.savefig('gas_density_' + str(i) + '.png')
plt.close()
rx,ry,rz = -121.77, -104.01, -203.10
tic = 0.8
i=0 # 00121, 0
print(rx,ry,rz)
impData = s[pynbody.filt.Cuboid(str((rx-sbox/2.0)) + " kpc", str((ry-sbox/2.0)) + " kpc",str((rz-sbox/4.0)) + " kpc",
str((rx+sbox/2.0)) + " kpc", str((ry+sbox/2.0)) + " kpc",str((rz+sbox/4.0)) + " kpc")]
rect = [0.15,0.15,0.85,0.9]
coords= [-rx,-ry,-rz] # Translation requires negative of the coord
with pynbody.transformation.translate(impData,coords):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.xaxis.set_visible(True)
ax.yaxis.set_visible(True)
fileOut="img_log_ax_vel-z=%.1lf-%i.pdf"% (z,i)
titleStr = "v - z = %.1lf" % z
print (titleStr)
sph.image(impData.g,qty="vel",width=smallbox,cmap="RdYlBu_r", denoise=True ,av_z=False, # units="km s^-1",
log=True, approximate_fast=False, subplot=ax, qtytitle=r"${\rm log}\, v\, {\rm km/s}$"
); #vmin=0.006, vmax=1.0,
plt.savefig(fileOut,dpi=fig.dpi,bbox_inches='tight')
plt.close(fig)
print("Fraction of PM ",
np.sum(impData.g['rho'] * impData.g['x']**3 * impData.g['pzsolar']/impData.g['zsolar'])/np.sum(impData.g['rho'] * impData.g['x']**3))
run_realnames) in zip(isnap_images, runs):
gizmoDir = gizmo_tools.getGizmoDir(run_dir)
with tempfile.NamedTemporaryFile() as tf:
for run_name, snap_list in zip(run_names, isnap_runs):
fullDir = os.path.join(gizmoDir, run_dir, run_name)
for ii, isnap in enumerate(snap_list):
infile = f"{fullDir}/snapshot_{isnap:03d}.hdf5"
header, snap = gizmo_tools.load_gizmo_nbody(
run_dir, run_name, f"{isnap:03d}")
tt = header["time"] / t_orbit
print(f"Rendering {run_name} {isnap} {tt}")
for iwidth, width in enumerate(widths):
m = sph.image(snap.gas,
qty="rho",
units="g cm^-3",
width=f"{width} pc",
resolution=res,
noplot=True,
approximate_fast=True)
key = f"{run_dir}_{run_name}_{ii}_{iwidth}_face"
f_out[key] = m # g/cm^2
# centre = snap[filt.disc(f"{width*2} pc",f"{width*2} pc")]
snap.rotate_x(90)
m = sph.image(snap.gas,
qty="rho",
units="g cm^-3",
width=f"{width} pc",
resolution=res,
noplot=True,
approximate_fast=True)
# m = generic.hist2d(centre["rxy"],centre["z"],gridsize=(res,res),weights=centre["mass"],make_plot=False)
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pylab as plt
# load the snapshot and set to physical units
s = pynbody.load('testdata/g15784.lr.01024.gz')
s.physical_units()
# load the halos
h = s.halos()
# center on the largest halo and align the disk
pynbody.analysis.angmom.faceon(h[1])
#create a simple slice of gas density
sph.image(h[1].g,qty="rho",units="g cm^-3",width=100,cmap="spectral")
def colorCodedImage(sim, qtys, width = 60, resolution = 500, z_camera = None,
av_zs = (False, False), cmap = 'Reds', vmins = (None, None),
vmaxs = (None, None), logs = (True, True)):
"""
Generates an image as with pynbody.plot.sph.image with brightness set by
one quantity and color set by a second quantity.
Parameters
----------
sim : SimSnap
Snapshot or sub-snap to render
qtys : list or tuple
A tuple/list of 2 quantities (strings) to render. The quantity are
SimSnap keys, e.g. 'rho', 'temp', 'mass', etc. The first quantity
sets the brightness of the image, the second sets the color
width : number
Width of the plot to render
resolution : int
Number of pixels to render along each axis
z_camera : number
z-camera location (see pynbody.plot.sph.image)
av_zs : tuple
Average along line-of-sight (see pynbody.plot.sph.image). If True,
volume averating is used. If a string averaging is over that qty.
E.g., mass averaging can be acheived by using av_zs = ('rho', 'rho')
cmap : str or cmap
colormap to use for color-coding
vmins, vmaxs : list/tuples
vmin, vmax for the quantities (one for each quantity)
logs : list/tuple
List or tuple of booleans. Defines whether color should use a log
scale.
Returns
-------
im : array
The rendered RGB image used
"""
cmaps = ('gray', cmap)
ims = []
# Generate the images
for i in range(2):
im = image(sim, qtys[i], width, resolution, av_z=av_zs[i],
z_camera=z_camera, log=logs[i], vmin=vmins[i],
vmax=vmaxs[i], cmap=cmaps[i], ret_im=True)
cb = plt.gcf().axes[-1]
ims.append(im)
# Grayscale image arrays
grayims = [im.get_array() for im in ims]
for i in range(2):
grayims[i] = normalizeArray(grayims[i], logs[i], vmins[i], vmaxs[i])
# Convert to rgb
rgb = colorCodeArray(grayims[0], grayims[1], cmap=cmap)
# Plot
#rgb = mpl.colors.hsv_to_rgb(hsv)
top = 0.5 * width
plt.gca().imshow(rgb, extent = (-top, top, -top, top))
# Add colorbar
#ax = im.get_axes()
cb = plt.colorbar(ims[1], orientation='vertical', label=qtys[1])
cb = plt.colorbar(ims[0], orientation='horizontal', label=qtys[0])
plt.ylabel('y ($' + sim['y'].units.latex() + '$)')
plt.tight_layout()
return rgb
import matplotlib
matplotlib.use('Agg')
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pyplot as plt
import numpy as np
pynbody.config['number_of_threads'] = 1
s = pynbody.load(
'/oasis/scratch/comet/mjt29/temp_project/Romulus25/cosmo25p.768sg1bwK1BHe75.008192'
)
halos = s.halos(dosort=True)
#numbers = [18, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 102, 103, 104, 105, 106, 107, 108, 109, 110, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 151, 152, 153, 154, 155, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 186, 187, 188, 189, 190, 191, 192, 193, 194, 196, 197, 198, 199, 200, 201, 202, 204, 206, 207, 208, 209, 210, 213, 214, 215, 216, 218, 219, 222, 223, 224, 225, 226, 229, 230, 232, 233, 234, 235, 236, 237, 239, 242, 244, 245, 247, 249, 252, 253, 254, 258, 260, 264, 265, 266, 273, 276, 283, 304, 310, 335]
numbers = [38]
for i in range(len(numbers)):
h = halos.load_copy(i)
h.physical_units()
pynbody.analysis.halo.center(h, mode='hyb')
pynbody.plot.stars.render(h, width='40 kpc')
plt.savefig('stars_' + str(i) + '.png')
plt.close()
sph.image(h.g, qty="rho", units="g cm^-3", cmap="Greys")
plt.savefig('gas_density_' + str(i) + '.png')
plt.close()
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pylab as plt
# load the snapshot and set to physical units
s = pynbody.load('testdata/g15784.lr.01024.gz')
s.physical_units()
# load the halos
h = s.halos()
# center on the largest halo and align the disk
pynbody.analysis.angmom.faceon(h[1])
#create a simple slice of gas density
sph.image(h[1].g,qty="temp",width=50,cmap="spectral")
z_crit = 2.0e-7
# Fix birth times
print s.derivable_keys()[1:5]
pynbody.analysis.ramses_util.get_tform(s,"/home1/02744/earnric/bin/part2birth");
if (len(s.s) > 0) :
x,y,zz = s.s['pos'][1] # Get the coords of the first SP
print "Star Particle 1 coords: ", x,y,zz
coords= [0, 0, -zz]
with pynbody.transformation.translate(s,coords):
try:
titleStr = "Z - z = %.1lf" % z + "\ncoords %s"%str(coords)
sph.image(s.g,qty="metal",width=boxsizestring,cmap="nipy_spectral", denoise=True ,av_z=False,
log=True, vmax=1.0, vmin=1e-7, approximate_fast=False,title=titleStr,
filename=fileOut); #vmin=0.006, vmax=1.0,
except:
print "EXCEPTION while plotting Z file: %s"%file
pass
try:
fileOut="PGF-z=%.1lf%s.png"% (z,str(coords))
titleStr = "PGF - z = %.1lf" % z + "\ncoords %s"%str(coords)
sph.image(s.g,qty="pgf",width=boxsizestring,cmap="nipy_spectral", denoise=True ,av_z=False,
log=True, vmin=1e-7, approximate_fast=False,title=titleStr,
filename=fileOut); #vmin=0.006, vmax=1.0,
except:
print "EXCEPTION while plotting PFG file: %s"%file
pass
try:
fileOut="Density-z=%.1lf%s.png"% (z,str(coords))
def view(sim,
k,
components=['d'],
angles=['faceon'],
styles=['cmap'],
figsize=(12, 6),
clim=[],
xcircle=0.1):
s1 = load_s(sim, snapshots[k], 's')
s2 = load_s(sim, snapshots[k + 1], 's')
h1 = s1.halos()[1]
h2 = s2.halos()[1]
t1 = pynbody.array.SimArray(float(s1.properties['time'].in_units('Gyr')))
t2 = pynbody.array.SimArray(float(s2.properties['time'].in_units('Gyr')))
Rvir1 = rvir_fangzhou[k]
Rvir2 = rvir_fangzhou[k + 1]
for angle in angles:
if angle == 'faceon':
pynbody.analysis.angmom.faceon(h1)
pynbody.analysis.angmom.faceon(h2)
elif angle == 'sideon':
pynbody.analysis.angmom.sideon(h1)
pynbody.analysis.angmom.sideon(h2)
else:
print 'The angle is not right'
for style in styles:
if style == 'cmap':
for component in components:
figure(figsize=figsize)
subplot(121)
ax1 = gca()
txt = ax1.text(0.03,
0.8,
r'$k = %i$' % (k),
transform=ax1.transAxes,
color='k',
fontsize=14)
txt.set_path_effects(
[PathEffects.withStroke(linewidth=5, foreground='w')])
if component == 'd':
if size(clim) == 0:
im = sph.image(h1.d,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax1,
show_cbar=False,
ret_im=True)
[vmin, vmax] = im.get_clim()
else:
sph.image(h1.d,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax1,
show_cbar=False,
vmin=clim[0],
vmax=clim[1])
txt = ax1.text(0.03,
0.9,
r'Dark matter',
transform=ax1.transAxes,
color='k',
fontsize=14)
elif component == 's':
if size(clim) == 0:
im = sph.image(h1.s,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax1,
show_cbar=False,
ret_im=True)
[vmin, vmax] = im.get_clim()
else:
sph.image(h1.s,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax1,
show_cbar=False,
vmin=clim[0],
vmax=clim[1])
txt = ax1.text(0.03,
0.9,
r'Stars',
transform=ax1.transAxes,
color='k',
fontsize=14)
elif component == 'g':
if size(clim) == 0:
im = sph.image(h1.g,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax1,
show_cbar=False,
ret_im=True)
[vmin, vmax] = im.get_clim()
else:
im = sph.image(h1.g,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax1,
show_cbar=False,
vmin=clim[0],
vmax=clim[1])
txt = ax1.text(0.03,
0.9,
r'Gas',
transform=ax1.transAxes,
color='k',
fontsize=14)
else:
print 'Components not valid'
txt.set_path_effects(
[PathEffects.withStroke(linewidth=5, foreground='w')])
u_st = h1['pos'].units.latex()
xlabel("$x/%s$" % u_st)
ylabel("$y/%s$" % u_st)
ax = gca()
circle = Circle((0, 0),
xcircle * Rvir1,
color='k',
fill=False)
ax.add_artist(circle)
if angle == 'faceon':
txt = ax1.text(0.75,
0.9,
r'Face on',
transform=ax1.transAxes,
color='k',
fontsize=14)
elif angle == 'sideon':
txt = ax1.text(0.75,
0.9,
r'Side on',
transform=ax1.transAxes,
color='k',
fontsize=14)
txt.set_path_effects(
[PathEffects.withStroke(linewidth=5, foreground='w')])
subplot(122)
ax2 = gca()
txt = ax2.text(0.03,
0.8,
r'$k +1 = %i$' % (k + 1),
transform=ax2.transAxes,
color='k',
fontsize=14)
txt.set_path_effects(
[PathEffects.withStroke(linewidth=5, foreground='w')])
if component == 'd':
sph.image(h2.d,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax2,
show_cbar=False,
vmin=vmin,
vmax=vmax) #,cmap="Greys")
txt = ax2.text(0.03,
0.9,
r'Dark matter',
transform=ax2.transAxes,
color='k',
fontsize=14)
elif component == 's':
sph.image(h2.s,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax2,
show_cbar=False,
vmin=vmin,
vmax=vmax) #,cmap="Greys")
txt = ax2.text(0.03,
0.9,
r'Stars',
transform=ax2.transAxes,
color='k',
fontsize=14)
elif component == 'g':
sph.image(h2.g,
qty="rho",
units="g cm^-3",
width=80,
subplot=ax2,
show_cbar=False,
vmin=vmin,
vmax=vmax) #,cmap="Greys")
txt = ax2.text(0.03,
0.9,
r'Gas',
transform=ax2.transAxes,
color='k',
fontsize=14)
else:
print 'Components not valid'
txt.set_path_effects(
[PathEffects.withStroke(linewidth=5, foreground='w')])
if angle == 'faceon':
txt = ax2.text(0.75,
0.9,
r'Face on',
transform=ax2.transAxes,
color='k',
fontsize=14)
elif angle == 'sideon':
txt = ax2.text(0.75,
0.9,
r'Side on',
transform=ax2.transAxes,
color='k',
fontsize=14)
txt.set_path_effects(
[PathEffects.withStroke(linewidth=5, foreground='w')])
ax = gca()
circle = Circle((0, 0),
xcircle * Rvir1,
color='k',
fill=False)
ax.add_artist(circle)
show()
elif style == 'HST':
figure(figsize=figsize)
subplot(121)
ax1 = gca()
ax1.text(0.03,
0.9,
r'HST image',
transform=ax1.transAxes,
color='w',
fontsize=14)
ax1.text(0.03,
0.8,
r'$k = %i$' % (k),
transform=ax1.transAxes,
color='w',
fontsize=14)
pynbody.plot.stars.render(s1,
width='20 kpc',
axes=ax1,
plot=True,
clear=False)
u_st = s1['pos'].units.latex()
xlabel("$x/%s$" % u_st)
ylabel("$y/%s$" % u_st)
ax = gca()
circle = Circle((0, 0), xcircle * Rvir1, color='w', fill=False)
ax.add_artist(circle)
if angle == 'faceon':
ax1.text(0.75,
0.9,
r'Face on',
transform=ax1.transAxes,
color='w',
fontsize=14)
elif angle == 'sideon':
ax1.text(0.75,
0.9,
r'Side on',
transform=ax1.transAxes,
color='w',
fontsize=14)
subplot(122)
ax2 = gca()
ax2.text(0.03,
0.9,
r'HST image',
transform=ax2.transAxes,
color='w',
fontsize=14)
ax2.text(0.03,
0.8,
r'$k +1 = %i$' % (k + 1),
transform=ax2.transAxes,
color='w',
fontsize=14)
pynbody.plot.stars.render(s2,
width='20 kpc',
axes=ax2,
plot=True,
clear=False)
u_st = s1['pos'].units.latex()
xlabel("$x/%s$" % u_st)
ylabel("$y/%s$" % u_st)
ax = gca()
circle = Circle((0, 0), xcircle * Rvir1, color='w', fill=False)
ax.add_artist(circle)
if angle == 'faceon':
ax2.text(0.75,
0.9,
r'Face on',
transform=ax2.transAxes,
color='w',
fontsize=14)
elif angle == 'sideon':
ax2.text(0.75,
0.9,
r'Side on',
transform=ax2.transAxes,
color='w',
fontsize=14)
show()
else:
print 'Style not compatible'
import pynbody
import pynbody.plot.sph as sph
import matplotlib.pylab as plt
# load the snapshot and set to physical units
s = pynbody.load('testdata/g15784.lr.01024.gz')
s.physical_units()
# load the halos
h = s.halos()
# center on the largest halo and align the disk
pynbody.analysis.angmom.sideon(h[1])
#create a simple slice showing the gas temperature
sph.image(h[1].g,
qty="temp",
width=50,
cmap="YlOrRd",
denoise=True,
approximate_fast=False)
indicies = np.in1d(s['iord'],outflow3)
outflow3_part = s[np.nonzero(indicies)]
#sph.image(outflow1_part.gas,units='m_p cm^-2', width=5*xymax)
#------------------------------------------------------
width = 3*xymax
fig = plt.figure(figsize=(7.,2.5))
fig.subplots_adjust(left=0.08, bottom=0.05, right=0.9, top=0.97, wspace=0.12,
hspace=0.13)
gs = matplotlib.gridspec.GridSpec(1, 4, width_ratios=[4,4,4,1.4])
sps = [fig.add_subplot(gs[0]), fig.add_subplot(gs[1]), fig.add_subplot(gs[2]), fig.add_subplot(gs[3])]
ax1 = (sps[0])
sim = sph.image(outflow1_part.gas,
units='m_p cm^-2', width=width, clear=False,
title='0.1 Gyr ago',show_cbar=True,vmin=1e16,vmax=1e22,
subplot=sps[0],cmap='ocean_r');
for label in ax1.yaxis.get_ticklabels():
label.set_fontsize(8)
for label in ax1.xaxis.get_ticklabels():
label.set_fontsize(8)
ax1.set_title(ax1.get_title(),fontsize = 12)
circle1=plt.Circle((0,0),xymax,ec='black',fc='none')
ax1.add_artist(circle1)
#Ejected 1 Myr ago
ax2 = subplot(sps[1],sharey = ax1)
#ax2.set_fontsize(12)
sim = sph.image(outflow2_part.gas,
