Python library to create optically thick kinematic toy models and explore their kinematics, given a user-defined structure and velocity, projected on a grid.
Project description
kintomo
kintomo is a Python library to create optically thick kinematic toy models and explore their kinematics, given a user-defined structure and velocity, projected on a grid.
Development status
kintomo is still in development, but we are trying to keep breaking changes to a minimum. Possible changes include:
- ENH: improve notebooks
- DOC: to be added.
- REL: publish to pipy
- RFC: keep
projection_deposition_visibleas a rogue function? - ENH: add additional shapes as classmethods.
- ENH: add optically-thin sculptures.
- RFC: use
__post_init__method to automatically convert sculpture and velocity profile to cartesian.
Installation
We recommend to install this repo using the package and project manager uv. See the documentation to install uv on your system. To install kintomo, run (ongoing work)
Notebooks
Examples are provided in the kintomo/notebooks directory. To run them:
uv run jupyter lab $PATH_TO_NOTEBOOK/notebook.ipynb
with the corresponding path to the notebook.ipynb of your choice.
Usage
The usual way of using kintomo starts with three steps:
- Define a point cloud as a cartesian
Sculpture. - Define a
Velocityprofile for every point in theSculpture. - Define a
Gridto project the point cloud on.
Sculpture
There are several ways of defining a Sculpture object. One possibility is to define first a cube of points cartesian_cube as a Sculpture, with arguments x, y, z (1D arrays):
num_points = 5
x0, y0, z0 = (2 * np.random.rand(num_points) - 1 for _ in range(3))
cartesian_cube = Sculpture(x=x0, y=y0, z=z0)
Here, the point cloud is composed of 5 points and is contained inside a cube of length 2, in the interval [-1,1] for every direction.
:information_source: Remark: You can also use a shorter version where you use directly the cube classmethod:
cartesian_cube = Sculpture.cube(500000)
x0, y0, z0 = (cartesian_cube.coordinates[k] for k in ("x","y","z"))
# equivalent to x0, y0, z0 = (cartesian_cube.x, cartesian_cube.y, cartesian_cube.z)
Then, it is possible to carve a user-defined Shape, like a cylinder, from cartesian_cube:
cylinder = (x0**2 + y0**2 < 1.0**2) & (abs(z0) < 0.02)
sculpture = cartesian_cube.carve(
shape=Shape(cylinder)
)
:information_source: Remark: There are several shapes that are already defined in kintomo if needed, like the cylinder:
sculpture = Sculpture(x=x0, y=y0, z=z0).carve(
shape=Shape.cylinder(
x=x0,
y=y0,
z=z0,
rmin=0.2,
rmax=1.0,
height=0.02,
)
)
Velocity
In order to define a Velocity depending on the points position in space, it is possible to convert and access the cartesian, cylindrical and spherical coordinates associated to the Sculpture:
x, y, z = sculpture.cartesian_coordinates()
r, phi, z = sculpture.cylindrical_coordinates()
r, theta, phi = sculpture.spherical_coordinates()
If the Shape is defined with an offset compared to the origin (0,0,0), you can add an offset when accessing the coordinates using the arguments x_offset, y_offset, z_offset (see the notebooks/double_spheres.ipynb notebook for a concrete example).
It is then possible to define the velocity profile, with 4 arguments : the geometry ("cartesian","cylindrical","spherical") and the 3 components of the velocity (v1,v2,v3) with the correct order depending on the geometry.
Example (spherical) : (v1, v2, v3) $\rightarrow$ (v$\rm r$, v$\theta$, v$_\phi$). Example of a userfef velocity profile corresponding to a keplerian profile:
velocity = Velocity(
geometry=Geometry("cylindrical"),
v1=np.zeros_like(r),
v2=np.sqrt(1/r),
v3=np.zeros_like(r),
).to_cartesian(phi=phi)
For now, note that the Velocity must be converted to cartesian if not already, using the to_cartesian method, specifying:
- the
phicoordinate if the native geometry is"cylindrical" - the
phiandthetacoordinates if the native geometry is"spherical"
:information_source: Remark: There are several velocity profiles that are already defined in kintomo if needed, e.g.,:
velocity = Velocity.keplerian(r=r).to_cartesian(phi=phi)
Grid
To define the Grid on which will be deposited the point cloud, you can use the encompass override method:
nx, ny, nz = (65, 65, 33)
grid = Grid.encompass(
sculpture=sculpture,
dimension=(nx, ny, nz),
)
It is also possible to have a user-defined grid. The following example corresponds to what is performed in the encompass override method:
grid = Grid(
xedge = np.linspace(2*x.min(), 2*x.max(), nx+1),
yedge = np.linspace(-2*sculpture.max_size_yz, 2*sculpture.max_size_yz, ny+1),
zedge = np.linspace(-2*sculpture.max_size_yz, 2*sculpture.max_size_yz, nz+1),
)
For more info, see the notebooks/keplerian_disk.ipynb notebook.
Additional remarks
kintomo & simulations. It is possible to use outputs from simulations to take a look at the kinematics, as long as the arrays are flattened into 1D arrays. For more info, see the notebooks/from_idefix_outputs.ipynb notebook.
kintomo & multiple sculptures. You can combine multiple sculpture objects and their corresponding velocities, using the + operator:
(sculpture, velocity) = (sculpture_1+sculpture_2, velocity_1+velocity_2)
For more info, see the notebooks/double_spheres.ipynb notebook.
kintomo & units. You can dimensionalize your problem with astropy.units using the to method:
unit_l = 100.0*u.au
cube = Sculpture.cube(5).to(unit=unit_l)
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