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add cartesian analysis

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This commit is contained in:
Noe Brucy
2023-05-05 19:15:44 +02:00
parent 946f11725e
commit 173de1151c
1 changed files with 78 additions and 1 deletions
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79
galsec.py
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@@ -90,7 +90,7 @@ def aggregate(
grouped_data: QTable,
weight_field: str = "mass",
extensive_fields: str = ["mass", "ek"],
weighted_fields: list = ["velr", "velphi", "velz"],
weighted_fields: list = ["velr", "velphi", "velx", "vely", "velz"],
) -> QTable:
"""Aggregate wisely from grouped data
@@ -281,6 +281,8 @@ class Galsec:
dset["position"], dset["velocity"]
) # azimuthal velocity
dset["velr"] = vect_r(dset["position"], dset["velocity"]) # radial velocity
dset["velx"] = dset["velocity"][:, 0] # x velocity (TODO this is stupid)
dset["vely"] = dset["velocity"][:, 1] # y velocity
dset["velz"] = dset["velocity"][:, 2] # vertical velocity
dset["ek"] = (dset["mass"] * np.sum(dset["velocity"] ** 2, axis=1)).to(
u.erg
@@ -316,6 +318,26 @@ class Galsec:
delta_phi = (delta_l / self.data[fluid]["r_bin"]) * u.rad
phi_bin = (np.trunc(self.data[fluid]["phi"] / delta_phi) + 0.5) * delta_phi
self.data[fluid]["phi_bin"] = phi_bin
def cartesian_binning(self, delta_x: Quantity[u.kpc],
delta_y: Quantity[u.kpc],
delta_z: Quantity[u.kpc]):
"""Add cartesian bin information to the dataset
Parameters
----------
delta_x : Quantity[u.kpc]
spacing between two x bins
delta_y : Quantity[u.kpc]
spacing between two y bins
"""
for fluid in self.fluids:
x_bin = np.trunc(self.data[fluid]["pos"][:, 0] / delta_x)
y_bin = np.trunc(self.data[fluid]["pos"][:, 0] / delta_y)
z_bin = np.trunc(self.data[fluid]["pos"][:, 0] / delta_z)
self.data[fluid]["x_bin"] = x_bin
self.data[fluid]["y_bin"] = y_bin
self.data[fluid]["z_bin"] = z_bin
def sector_analysis(
self,
@@ -376,6 +398,61 @@ class Galsec:
self.sectors["stars"]["sfr"][i] = get_sfr(group, self.time)
self.sectors["stars"]["sfr"][i] = get_sfr(group, self.time)
def cartesian_analysis(
self,
delta_x: Quantity[u.kpc] = u.kpc,
delta_y: Quantity[u.kpc] = u.kpc,
delta_z: Quantity[u.kpc] = u.kpc,
zmin: Quantity[u.kpc] = -0.5 * u.kpc,
zmax: Quantity[u.kpc] = 0.5 * u.kpc,
):
"""Compute the aggration of quantities in sectors bins
Parameters
----------
delta_x : Quantity[u.kpc]
spacing between two x bins
delta_y : Quantity[u.kpc]
spacing between two y bins
"""
self.cartesian_binning(delta_x, delta_y)
self.grouped_data = {}
self.sectors = {}
for fluid in self.fluids:
if fluid == "gas":
extensive_fields = ["mass", "ek", "volume"]
else:
extensive_fields = ["mass", "ek"]
filtered_data = self.data[fluid][
(self.data[fluid]["position"][:, 2] > zmin)
& (self.data[fluid]["position"][:, 2] < zmax)
]
self.grouped_data[fluid] = filtered_data.group_by(["x_bin", "y_bin", "z_bin"])
self.sectors[fluid] = hstack(
[
self.grouped_data[fluid]["x_bin", "y_bin", "z_bin"].groups.aggregate(
np.fmin
),
aggregate(
self.grouped_data[fluid], extensive_fields=extensive_fields
),
]
)
self.sectors[fluid].rename_column("x_bin", "x")
self.sectors[fluid].rename_column("y_bin", "y")
self.sectors[fluid].rename_column("z_bin", "z")
self.sectors["stars"]["sfr"] = (
np.zeros(len(self.sectors["stars"]["mass"])) * u.Msun / u.year
)
for i, group in enumerate(self.grouped_data["stars"].groups):
self.sectors["stars"]["sfr"][i] = get_sfr(group, self.time)
self.sectors["stars"]["sfr"][i] = get_sfr(group, self.time)
def ring_analysis(
self,