Extended IDL Help

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Last modified: Sun Jun 11 15:19:57 2006.


List of Routines


Routine Descriptions

DIMENSIONLESS_SPDE

[List of Routines]
 NAME:
	dimensionless_spde

 PURPOSE:
           Compute a numerical solution to the 1-dimensional SPDEs
           from Kramer, Szeri, Kirsch, Szeri, JCN, in press.

 CATEGORY:

 CALLING SEQUENCE:
                    d=dimensionless_spde(N, dt, L, dl, Gamma_e, pee_in, alpha=alpha, read=read, write=write)

 INPUTS:
        N:  The number of time steps to take.      (Suggested = 10000)
       dt:  The dimensionless temporal step size.  (Suggested = 0.0025)
        L:  The number of spatial points.          (Suggested = 50)
       dx:  The dimensionless spatial step size.   (Suggested = 0.05)
  Gamma_e:  The value of the parameter Gamma_e.    (Typical = 1.42e-3)
     P_ee:  The value of parameter P_ee.           (Typical = 11.0)

 KEYWORDS:
    ALPHA:	If this keyword is set to a nonzero value, then set the parameters
               controlling the strength of stochastic input to the cortex to:
               alpha_ee = alpha_ei = alpha_ie = alpha_ii = ALPHA.
               Otherwise, there is NO noisy input to the cortex
               (i.e., alpha_ee = alpha_ei = alpha_ie = alpha_ii = 0.0)

     READ:	If this keyword is set, then read in the initial coniditions
               for the model variables from the file:
               input_output_path+'ic_dimensionless.dat'

    WRITE:	If this keyword is set, then write out the model variables at
               the final time step (N-1) to the file:
               input_output_path+'ic_dimensionless.dat'

 COMMON BLOCKS:
	None.

 SIDE EFFECTS:
       When the keyword WRITE is set, a text file is created at:
       input_output_path+'ic_dimensionless.dat'

 EXAMPLE:
  d = dimensionless_spde(10000, 0.0025, 50, 0.05, 1.42e-3, 11.0)
  d = dimensionless_spde(10000, 0.0025, 50, 0.05, 1.42e-3, 11.0, /write)
  d = dimensionless_spde(10000, 0.0025, 50, 0.05, 1.42e-3, 11.0, alpha=0.02, /read, /write)

 MODIFICATION HISTORY:
       June 9, 2006, Mark Kramer, Boston University.

(See ~/research/STOCH/code/dimensionless_spde.pro)