# Structure of `odes`

and User’s Guide¶

There are a number of different ways of using `odes`

to solve a system of
ODEs/DAEs:

`scikits.odes.ode.ode`

and`scikits.odes.dae.dae`

classes, which provides an object oriented interface and significant amount of control of the solver.`scikits.odes.odeint.odeint()`

, a single function alternative to the object oriented interface.- Accessing the lower-level solver-specific wrappers, such as the modules in
`scikits.odes.sundials`

.

In general, a user supplies a function with the signature:

```
right_hand_side(t: float, y: Array[float], ydot: Array[float]) -> int
```

for the ODE solvers, and:

```
right_hand_side(t: float, y: Array[float], ydot: Array[float], residue: Array[float]) -> int
```

for the DAE solvers, as well as positions to integrate between and initial values.

## Simple Function Interface (`odeint`

)¶

The simplest user program using the `odeint`

interface, assuming you have
implemented the ODE `right_hand_side`

mentioned above, is:

```
import numpy as np
from scikits.odes.odeint import odeint
tout = np.linspace(0, 1)
initial_values = np.array([0])
def right_hand_side(t, y, ydot):
"""
User's right hand side function
"""
pass
output = odeint(right_hand_side, tout, initial_values)
print(output.values.y)
```

By default, CVODE’s BDF method is used, however a different method can be
specified via the `method`

keyword. Methods specific to `odeint`

, which use
the recommended setting for the individual solvers, are:

`bdf`

- CVODE’s BDF method (default)
`admo`

- CVODE’s Adams-Moulton method
`rk5`

- dopri5 Runge-Kutta method of order (4)5
`rk8`

- dop853 Runge-Kutta method of order 8(5,3)
`beuler`

- Implicit/Backward Euler method (for educational purposes only!)
`trapz`

- Trapezoidal Rule method (for educational purposes only!)

A specific solver (e.g. CVODE) can also be passed in via `method`

, in the
same way specified by the Object Oriented Interface. Solver specific options
can be passed in via additional keyword arguments.

## Object Oriented Interface (`ode`

and `dae`

)¶

The object oriented interfaces for `ode`

and `dae`

are almost identical,
with solver customisations via either keyword arguments or via a
`set_options`

method, repeated usage of the same solver via the `solve`

method, and individual stepping via the `step`

method.

Note

`odes`

2.2.2 and later have a new output format, which provides
access to more solver information. In a future release, the default will be
the new output format. To use the new output format, pass as a keyword
argument `old_api=False`

.

`ode`

Object Oriented Interface¶

The simplest user program using the `ode`

interface, assuming you have
implemented the ODE `right_hand_side`

mentioned above, is:

```
import numpy as np
from scikits.odes.ode import ode
SOLVER = 'cvode'
tout = np.linspace(0, 1)
initial_values = np.array([0])
extra_options = {'old_api': False}
def right_hand_side(t, y, ydot):
"""
User's right hand side function
"""
pass
ode_solver = ode(SOLVER, right_hand_side, **extra_options)
output = ode_solver.solve(tout, initial_values)
print(output.values.y)
```

Extra options are solver specific, but there is usually support for passing in
user data (passed as additional arguments to the provided `right_hand_side`

),
and for setting the tolerance of the solver. See Choosing a Solver for
more information about individual solvers.

#### Examples¶

There are a number of `ode`

examples showing different features, including
solver specific features. Here are some of them:

`dae`

Object Oriented Interface¶

The simplest user program using the `dae`

interface, assuming you have
implemented the DAE `right_hand_side`

mentioned above, is:

```
import numpy as np
from scikits.odes.dae import dae
SOLVER = 'ida'
tout = np.linspace(0, 1)
y_initial = np.array([0])
ydot_initial = np.array([0])
extra_options = {'old_api': False}
def right_hand_side(t, y, ydot, residue):
"""
User's right hand side function
"""
pass
dae_solver = dae(SOLVER, right_hand_side, **extra_options)
output = dae_solver.solve(tout, y_initial, ydot_initial)
print(output.values.y)
```

Extra options are solver specific, but there is usually support for passing in
user data (passed as additional arguments to the provided `right_hand_side`

),
and for setting the tolerance of the solver. See Choosing a Solver for
more information about individual solvers.

#### Examples¶

There are a number of `dae`

examples showing different features, including
solver specific features. Here are some of them:

## Lower-level interfaces¶

Using the lower-level interfaces is solver-specific, see the API docs for more information and Choosing a Solver for comparisons between solvers.