This page describes how to use Python libraries for macroeconomic modelling, allowing to extend Dynare functionalities.
Python ressources
* Formal calculus
[http://code.google.com/p/sympy/ sympy ] python library to perform formal calculus.
[http://www.sagemath.org/ sage ] (includes sympy) python wrapper around many opensource libraries which converts all of them into a single webbased interface. Is also able to delegate calculus to Maple or Mathematica.
* Numerical computing
[http://numpy.scipy.org/ numpy] : contains an efficient implementation of matrix processing whose performance is close to matlab
[http://www.scipy.org/ scipy] : set of scientific routines including optimization routines
[http://www.cosc.canterbury.ac.nz/greg.ewing/python/Pyrex/ pyrex] and [http://psyco.sourceforge.net/ psyco ] (included in scipy) can speedup computations. The first allows to write C extensions in a python-like syntax, while the second performs just-in-time compilation of python functions.
* Other
[http://epydoc.sourceforge.net/ epydoc ] generates online documentation from inline documentation
[http://mlabwrap.sourceforge.net/ mlabwrap ] uses the Matlab Engine to interact with Matlab. It permits to send and retrieve data, as well as to call Matlab function from Python.
[http://rpy.sourceforge.net/ rpy] : low-level access to statistical program R permitting to call every R functions as python functions.
[http://www.py2exe.org/ py2exe] packs a python program with all its libraries in a single windows executable which includes the interpreter.
Writing/extending modfiles in Python
Here is the code of ramsey.py, which translates ramst.mod into python code. It is run by the standard Python interpreter.
1 ###
2 Model Definition
3 ###
4
5 from daredare import *
6
7 set_variables("k c")
8 set_exovariables("z")
9 set_shocks("x")
10 set_parameters("alpha beta gamma delta aa")
11
12 equations = [
13 Equation(c + k , (1 - delta)*k(-1) + k(-1)**alpha*(1 + z)*aa),
14 Equation(0 , -1/(1 + beta)*c(1)**(-gamma)*(1 - delta + k**(-1 + alpha)*(1 + z(1))*aa*alpha) + c**(-gamma)),
15 Equation(z(1),x)
16 ]
17
18 parameters_values = {
19 alpha : 0.5,
20 gamma : 1*alpha,
21 delta : 0.02,
22 beta : 0.05,
23 aa : 0.5
24 }
25
26 covariances = matrix([[0.01]])
27
28 init_values = {
29 k:(1/aa/alpha*(beta + delta))**(1/(-1 + alpha)),
30 c:k**alpha*aa - delta*k
31 }
32
33 ###
34 Model processing
35 ###
Language extension (for model definition)
On the very first line of this code from daredare import * imports the library. The second block
creates formal objects "k,c,z" which all derive of the same class Variable. This class is a subclass of the standard Sympy class Symbol, which only adds the possibility to take lags or leads with a function call : for instance k(1) returns another Variable whose formal name is k_{+1}. k.lag returns the lag so that k(-k.lag))}} or equivalently {{{k.p() will always return a variable with lag 0. Parameters are of the class Parameter which doesn't have the same facility. It should be noted that, a priori, the formal object, and the Python reference name which is used by the compiler are to different things. For instance,
will print : x**2/y. In this respect the functions like set_variables are notable because instead of returning the created objects, they also add references to the interpreter context, with the same names as the variables. They also add the python names variables,shocks,exovariables,parameters. The next block
defines equations. The object Equation is a child of Sympy's Equality object. It contains the expression as well as some attributes as (optionally) equation name, expectational nature, and other information that could be computed later. Three remarks :
unfortunately we cannot write x+y == z because in python == must always return true or false (see Sympy mailing list).
to convert from/to matlab, you only have to convert * from/to ^. For instance, if eq is a python formal expression, str(eq).replace('==','=').replace('**','^') will give the valid Dynare expression.
- every sympy operations on equalities are available
printing.latex(eq) (or printing.mathml(eq) will return the latex (or mathml) representation of the equality
preview(eq) will launch an viewer to preview the latexified output
eq.rhs.diff(c) will return the right side of the equation differentiated with respect to c
eq.rhs.subs(c(1),c) will replace c(1) by c in the right side
(for model definition)