# ORBKIT’s Low-Level Interface¶

This section is addressed to more advanced users, who want to use the modules of ORBKIT in their own programs.

Please refer to the Function Reference to get information about all modules and functions available.

Hint

Complete examples of using ORBKIT’s modules can be found in
`orbkit/examples`

, e.g.,
`use_as_module.py`

and `calculate_derivatives.py`

)

The tutorials Tutorial for the Integration with Cubature and Tutorial for Processing Multiple Input Files show further practical applications.

Table of Contents:

## Reading QC Input¶

All reading processes are handled by the module `orbkit.read`

, i.e.:

```
from orbkit import read
```

Here, you have one function for each quantum chemistry input type converting
the input to the `QCinfo`

class (cf. Central Variables). These
functions are managed by:

```
qc = read.main_read(filename,itype='molden',all_mo=False,spin=None,**kwargs)
```

Besides choosing the filename and the input type, you can specify, if the function
should read the occupied *and* the virtual molecular orbitals (`all_mo`

).
Moreover, `read.main_read`

forwards all additional keyword arguments (`**kwargs`

)
to the specific reading function, e.g., you can disable the interactive mode
in `read.read_molden`

.
For unrestricted calculations, the `spin`

keyword can specify, if only
molecular orbitals of alpha or beta spin shall be read.

Hint

The main computational functions are not restricted to the `QCinfo`

class.
They also accept dictionaries having the same members.

You can convert the `QCinfo`

class to a dictionaries containing *only*
the essential members by:

```
qc_dict = qc.todict()
```

## Initializing the Grid¶

The `orbkit.grid`

module organizes all grid related features of ORBKIT,
of which some will be discussed in this section.

If you want to initialize a standard regular (vector) grid you have to set the grid parameters which are global values within this module:

```
from orbkit import grid
grid.min_ = [-8.0, -8.0, -8.0] #: Specifies minimum grid values (regular grid).
grid.max_ = [ 8.0, 8.0, 8.0] #: Specifies maximum grid values (regular grid).
grid.N_ = [ 101, 101, 101] #: Specifies the number of grid points (regular grid).
```

Note

If you prefer setting the grid spacing instead of the number of data points, you may set this parameters by:

```
ok.grid.delta_ = [0.1, 0.2, 0.1]
```

Now, you can initialize the grid:

```
grid.grid_init(is_vector=False, force=False)
```

To invoke the creation of a **vector** grid, i.e.,
(see Grid Related Options (Usage via the Terminal)), the variable `is_vector`

has to
set to `True`

. If you want to change the grid, e.g., for a subsequent
calculation, you have either to set:

```
grid.is_initialized=False
```

or to call:

```
grid.grid_init(force=True)
```

Hint

The current grid parameters can be displayed with:

```
print(grid.get_grid())
```

Another way to automatically set the grid parameters according to the molecular geometry is calling:

```
grid.adjust_to_geo(qc,extend=5.0,step=0.1)
```

Here, ORBKIT creates grid parameters (`grid.min_`

, `grid.max_`

, `grid.N_`

)
with a grid spacing of 0.1 a_{0} and the size of the molecule plus
5 a_{0} in each direction. After calling this function you have to
**initialize the grid** using `grid.grid_init()`

.

The last way to initialize a grid is by setting the *x*, *y*, *z* coordinates
manually:

```
import numpy
grid.x = numpy.linspace(-10,10,201)
grid.y = numpy.array([0],dtype=float)
grid.z = numpy.array([-1.0,1.1])
# We have already initialized a grid for orbkit:
grid.is_initialized = True
```

Here, x, y and z have to be one-dimensional `numpy.array`

of type `float`

(`numpy.float64`

).

If you have set a regular grid, please be sure that you set the following variables:

```
grid.is_vector = False
grid.is_regualar = True
```

Attention

The last line is **mandatory**, i.e., we have to tell ORBKIT, that there is no
need to initialize the grid.

Hint

For your convenience, you may also set the variable `grid.is_vector = True`

,
if you have initialized a **vector grid** manually. You can use this
standard variable as input parameter in other ORBKIT functions.

## Operations on the Grid¶

The module `orbkit.grid`

has some more features. For instance, starting
from a **regular grid**, you can always convert between **regular** and a **vector
grid**:

```
from orbkit import grid
# Initialize the grid
grid.grid_init(is_vector=False, force=False)
# Convert the grid to a vector grid
grid.grid2vector()
print(grid.get_grid()) # Display the new grid parameters
# Convert it back to a regular grid
grid.vector2grid(*grid.N_)
# Display the new grid parameters
print(grid.get_grid()) # Display the new grid parameters
```

The same can be done for matrices of the specific shapes, e.g.:

```
import numpy
from orbkit import grid
# Initialize a vector grid
grid.grid_init(is_vector=True)
# Create an array of the same shape, i.e., Nx=Ny=Nz=shape(matrix)
matrix = numpy.arange(len(grid.x))
Nx, Ny, Nz = grid.N_
matrix = grid.matrix_vector2grid(matrix=matrix,Nx=Nx,Ny=Ny,Nz=Nz)
```

## Computational Functions¶

All major computational processes are carried out by the module
`orbkit.core`

. The function `rho_compute`

manages the computational tasks,
slices the grid, and distributes the slices to the subprocesses:

```
from orbkit import core
data = core.rho_compute(qc,calc_mo=False,slice_length=1e4,
drv=None,laplacian=False,numproc=1)
```

If you set `calc_mo=True`

, all molecular orbitals will be computed and
returned. The variable `slice_length`

contains an integer value specifying the number of
grid points per subprocess.

Derivatives can be computed by changing the variable `drv`

, e.g.,
`drv=['x','zz','xy']`

will invoke the computation of the first derivative
with respect to , the second derivative with respect to , and the mixed
derivative .

If the number of processes (`numproc`

) is smaller or equal one, no subprocesses will be
started, i.e., ORBKIT uses only a single CPU. If you even want to omit the
slicing of the grid, you can use:

```
data = core.rho_compute_no_slice(qc,calc_mo=False,drv=None,laplacian=False
return_components=False,
is_vector=None,x=None,y=None,z=None)
```

Here, you can even return the atomic orbitals (and/or their derivatives) as well
with `return_components`

.
Furthermore, you can specify the grid (`x`

, `y`

, `z`

, and `is_vector`

)
without using the `orbkit.grid`

module.

If you do not want to use those functions, you can go further to the function computing the atomic orbitals and the function combining these orbitals to molecular orbitals:

```
ao_list = core.ao_creator(geo_spec,ao_spec,ao_spherical=ao_spherical,drv=None,
is_vector=None,x=None,y=None,z=None)
mo_list = core.mo_creator(ao_list,mo_spec)
```

Those functions use the only specific members of the `QCinfo`

class.
Again, you can specify the grid (`x`

, `y`

, `z`

, and `is_vector`

)
without using the `orbkit.grid`

module.

The functionalities `calc_mo`

and `mo_set`

, i.e., the computation of
selected molecular orbitals and the calculation of the density with a
selected set of molecular orbitals, are handled by two functions of the module
`orbkit.extras`

:

```
mo_list, mo_info = extras.calc_mo(qc, fid_mo_list, drv=None, otype=None, ofid=None)
```

and:

```
data = extras.mo_set(qc, fid_mo_list, drv=None, laplacian=False,
otype=None, ofid=None, return_all=True)
```

`fid_mo_list`

is a list molecular orbital labels, cf. Molecular Orbital Selection (High-Level Interface).
Here, `slice_length`

and `numproc`

are read from the respective `orbkit.options`

variables.

## Output Functions¶

The output functionalities of ORBKIT are handled by the module `orbkit.output`

.

In this module, there are functions for every output type. These functions are managed by:

```
output.main_output(data,geo_info,geo_spec,outputname='new',otype='h5',
drv=None,omit=[],**kwargs)
```