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[galaxy] move towards stats box analysis

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Noe Brucy
2021-05-27 23:52:19 +02:00
parent 5276323313
commit c20d698884
1 changed files with 127 additions and 102 deletions
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galaxy.py
+127 -102
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@@ -4,26 +4,6 @@ import numpy as np
from plotter import U
def get_dispersion(dset, name):
"""
Compute dispersion from dset["name"]
"""
vel = dset[name]
mass = dset["mass_kg"]
mass_tot = np.sum(mass)
mean = np.sum(mass * vel) / mass_tot
return np.sqrt(np.sum(mass * (vel - mean) ** 2) / mass_tot)
def get_polar_sigma(dset):
"""
Get speed dispersion in polar coordinates
"""
return {
velname: get_dispersion(dset, velname) for velname in ["velphi", "velr", "velz"]
}
def get_gas_dm_stars(pp):
# Load arrays
pp.load_parts()
@@ -74,65 +54,133 @@ def get_gas_dm_stars(pp):
return gas, dm, stars
def extract_polar_region(dset, r=4, dr=0.5, phi=0, dphi=0.125, z=0, dz=0.5):
def get_dispersion(dset, name):
"""
Returns a mask for dset of the polar volume within polar coordinates
[r - dr, r + dr] x [phi - dphi, phi + dphi] x [z -dz, z + dz]
Compute dispersion from dset["name"]
"""
mask_box = (
(np.abs(dset["r"] - r) < dr)
& (np.abs(dset["phi"] - phi) < dphi)
& (np.abs(dset["pos_kpc"][:, 2] - z) < dz)
)
return {key: dset[key][mask_box] for key in dset}
vel = dset[name]
mass = dset["mass_kg"]
mass_tot = np.sum(mass)
mean = np.sum(mass * vel) / mass_tot
return np.sqrt(np.sum(mass * (vel - mean) ** 2) / mass_tot)
def sector_analysis(pp, r=4, dr=0.5, phi=0, dphi=0.125, z=0, dz=0.5):
def get_polar_sigma(dset):
"""
Get speed dispersion in polar coordinates
"""
return {
velname: get_dispersion(dset, velname) for velname in ["velphi", "velr", "velz"]
}
def get_sfr(pp, stars):
try:
epoch = stars["epoch"].copy()
epoch *= pp.info["unit_time"].express(U.year)
mass = stars["mass"].copy()
mass *= pp.info["unit_mass"].express(U.Msun)
masstot, time = np.histogram(epoch, weights=mass, bins=100)
dtime = np.diff(time)
sfr = masstot[-1] / dtime[-1]
except KeyError:
sfr = 0.0
return sfr
def get_coldens(pp):
"""
Get mean column density in a sector
"""
pp.coldens("z")
pp.coldens_map = pp.get_value("/maps/coldens_z", unit=U.coldens)
im_extent = np.array(pp.get_attribute("/maps", "im_extent"))
im_extent *= pp.info["unit_length"].express(U.kpc)
map_size = pp.pp_params.pymses.map_size
center = np.array(pp.pp_params.disk.center)
center *= pp.info["unit_length"].express(U.kpc)
# Physical size of cells
dx = (im_extent[1] - im_extent[0]) / map_size
dy = (im_extent[3] - im_extent[2]) / map_size
# Physical coordinates of the center of the cells
x = np.linspace(im_extent[0], im_extent[1], map_size) + 0.5 * dx - center[0]
y = np.linspace(im_extent[2], im_extent[3], map_size) + 0.5 * dy - center[1]
xx, yy = np.meshgrid(x, y)
# Physical radius
pp.rr_map = np.sqrt(xx ** 2 + yy ** 2)
pp.phi_map = np.angle(xx + yy * 1j)
def sector_analysis(pp, gds_ring, mask_ring, phi=0, dphi=0.125):
"""
Analyze box at given coordinates
"""
gds = [pp.gas, pp.dm, pp.stars]
gds_box = [extract_polar_region(dset, r, dr, phi, dphi, z, dz) for dset in gds]
result = {}
result["ek"] = np.array([np.sum(dset["ek"]) for dset in gds_box]) # J
result["mass"] = np.array([np.sum(dset["mass_kg"]) for dset in gds_box]) # kg
result["ek_spe"] = result["ek"] / result["mass"] # J.kg^-1
for dset in gds_box:
masks_box = [(np.abs(dset["phi"] - phi) < dphi) for i, dset in enumerate(gds_ring)]
gds_box = [
{key: dset[key][mask] for key in dset if key in keys}
for dset, mask in zip(gds_ring, masks_box)
]
res = {}
# Generic Info
res["phi"] = phi
res["dphi"] = dphi
res["sfr"] = get_sfr(pp, gds_box[2])
res["coldens"] = np.mean(
pp.coldens_map[mask_ring & (np.abs(pp.phi_map - phi) < dphi)]
)
for dset, fluid in zip(gds_box, ["gas", "dm", "stars"]):
res[f"ek_{fluid}"] = np.sum(dset["ek"]) # J
res[f"mass_{fluid}"] = np.sum(dset["mass_kg"]) # kg
res[f"ek_spe_{fluid}"] = res[f"ek_{fluid}"] / res[f"mass_{fluid}"] # J.kg^-1
sigma = get_polar_sigma(dset)
for key in sigma:
keyres = "sigma_" + key
if keyres in result:
result[keyres].append(sigma[key])
else:
result[keyres] = [sigma[key]]
return result
for dir in sigma:
res[f"sigma_{dir}_{fluid}"] = sigma[dir]
return res
keys = ["epoch", "ek", "mass_kg", "pos_kpc", "velphi", "velr", "velz", "mass", "phi"]
def ring_analysis(pp, r=4, dr=0.5, dphi=0.125, z=0, dz=0.5):
"""
Compute the average at a given of quantities computed in polar sectors.
"""
gds = [pp.gas, pp.dm, pp.stars]
phi_sectors = np.arange(-np.pi + dphi, np.pi - dphi, 2 * dphi)
data_sec = [sector_analysis(pp, r, dr, phi, dphi, z, dz) for phi in phi_sectors]
masks_ring = [
(np.abs(dset["r"] - r) < dr) & (np.abs(dset["pos_kpc"][:, 2] - z) < dz)
for dset in gds
]
gds_ring = [
{key: dset[key][mask] for key in dset if key in keys}
for dset, mask in zip(gds, masks_ring)
]
mask_ring = np.abs(pp.rr_map - r) < dr
data_sec = [
sector_analysis(pp, gds_ring, mask_ring, phi, dphi) for phi in phi_sectors
]
data = {}
mwavg = {}
tot_mass = [np.sum([d["mass"][i] for d in data_sec]) for i in range(3)]
res = {}
for key in data_sec[0]:
mwavg[key] = []
for i in range(3):
mwavg[key].append(
np.sum([d["mass"][i] * d[key][i] for d in data_sec]) / tot_mass[i]
)
res[key] = [d[key] for d in data_sec]
data[key] = np.array([d[key] for d in data_sec])
res["r"] = [r] * len(phi_sectors)
res["dr"] = [dr] * len(phi_sectors)
return res
return mwavg, phi_sectors, data
def get_time_from_relax(pp):
pp.load_parts()
try:
epoch = pp.parts["epoch"].copy()
epoch *= pp.info["unit_time"].express(U.Myr)
@@ -143,57 +191,32 @@ def get_time_from_relax(pp):
return tfromrelax
def get_last_sfr(pp, r=4, dr=0.5, z=0, dz=0.5):
pp.load_parts()
try:
epoch = pp.stars["epoch"].copy()
epoch *= pp.info["unit_time"].express(U.year)
mass = pp.stars["mass"].copy()
mass *= pp.info["unit_mass"].express(U.Msun)
mask = (
(epoch > 0)
& (np.abs(pp.stars["r"] - r) < dr)
& (np.abs(pp.stars["pos_kpc"][:, 2] - z) < dz)
)
masstot, time = np.histogram(epoch[mask], weights=mass[mask], bins=100)
dtime = np.diff(time)
sfr = masstot[-1] / dtime[-1]
except KeyError:
sfr = 0.0
return sfr
def colmean_ring(pp, r=4, dr=0.5):
pp.coldens("z")
pp.rr("z")
col = pp.get_value("/maps/coldens_z", unit=U.coldens)
rr = pp.get_value("/maps/rr_z", unit=U.kpc)
colmean = np.mean(col[np.abs(rr - r) < dr])
return colmean
def analyse_ring(pp, r=4):
def analyse_rings(pp, radius=[4]):
res = {}
res["run"] = pp.run
res["num"] = pp.num
res["coldens"] = colmean_ring(pp, r)
res["sfr"] = get_last_sfr(pp, r)
res["time"] = get_time_from_relax(pp)
ring = ring_analysis(pp, r, dphi=1.0 / (2 * r))[0]
for key in ring:
for i, fluid in enumerate(["gas", "dm", "stars"]):
res[f"{key}_{fluid}"] = ring[key][i]
for i, r in enumerate(radius):
ring = ring_analysis(pp, r, dphi=1.0 / (2 * r))
if i == 0:
res = ring
else:
for key in res:
res[key].extend(ring[key])
res["run"] = [pp.run] * len(res["r"])
res["num"] = [pp.num] * len(res["r"])
time = get_time_from_relax(pp)
res["time"] = [time] * len(res["r"])
return res
def analyse_disk(pp, rmax=6.0, zmax=1.0):
get_gas_dm_stars(pp)
def analyse_disk(pp, rmax=12.0):
res = {}
res["run"] = pp.run
res["num"] = pp.num
res["coldens"] = colmean_ring(pp, rmax / 2.0, rmax / 2.0)
res["sfr"] = get_last_sfr(pp, rmax / 2.0, rmax / 2.0, 0, zmax)
res["coldens"] = np.mean(pp.coldens_map[pp.rr_map < rmax])
res["sfr"] = get_sfr(pp, pp.stars)
res["time"] = get_time_from_relax(pp)
for dset, fluid in zip([pp.gas, pp.dm, pp.stars], ["gas", "dm", "stars"]):
@@ -208,6 +231,8 @@ def load_wrapper(pp, fun):
Wrapper to load_unload data and map function
"""
get_gas_dm_stars(pp)
get_coldens(pp)
res = fun(pp)
pp.unload_cells()
pp.unload_parts()
@@ -219,6 +244,6 @@ def load_wrapper(pp, fun):
def allinone(pp):
def fun(pp):
return analyse_disk(pp), analyse_ring(pp, 4), analyse_ring(pp, 6)
return analyse_disk(pp), analyse_rings(pp, [4, 5, 6, 7, 8])
return load_wrapper(pp, fun)