[Scipy-svn] r4466 - trunk/scipy/integrate

scipy-svn@scip... scipy-svn@scip...
Mon Jun 23 15:53:30 CDT 2008


Author: ptvirtan
Date: 2008-06-23 15:53:22 -0500 (Mon, 23 Jun 2008)
New Revision: 4466

Modified:
   trunk/scipy/integrate/odepack.py
Log:
Reformat integrate.odeint docstring

Modified: trunk/scipy/integrate/odepack.py
===================================================================
--- trunk/scipy/integrate/odepack.py	2008-06-23 14:37:03 UTC (rev 4465)
+++ trunk/scipy/integrate/odepack.py	2008-06-23 20:53:22 UTC (rev 4466)
@@ -21,96 +21,115 @@
            ml=None, mu=None, rtol=None, atol=None, tcrit=None, h0=0.0,
            hmax=0.0, hmin=0.0, ixpr=0, mxstep=0, mxhnil=0, mxordn=12,
            mxords=5, printmessg=0):
-
     """Integrate a system of ordinary differential equations.
 
-    Description:
+    Solve a system of ordinary differential equations using lsoda from the
+    FORTRAN library odepack.
 
-      Solve a system of ordinary differential equations Using lsoda from the
-      FORTRAN library odepack.
+    Solves the initial value problem for stiff or non-stiff systems
+    of first order ode-s::
+    
+        dy/dt = func(y,t0,...)
 
-      Solves the initial value problem for stiff or non-stiff systems
-      of first order ode-s:
-           dy/dt = func(y,t0,...) where y can be a vector.
+    where y can be a vector.
 
-    Inputs:
+    Parameters
+    ----------
+    func : callable(y, t0, ...)
+        Computes the derivative of y at t0.
+    y0 : array
+        Initial condition on y (can be a vector).
+    t : array
+        A sequence of time points for which to solve for y.  The initial
+        value point should be the first element of this sequence.
+    args : tuple
+        Extra arguments to pass to function.
+    Dfun : callable(y, t0, ...)
+        Gradient (Jacobian) of func.
+    col_deriv : boolean
+        True if Dfun defines derivatives down columns (faster),
+        otherwise Dfun should define derivatives across rows.
+    full_output : boolean
+        True if to return a dictionary of optional outputs as the second output
+    printmessg : boolean
+        Whether to print the convergence message
 
-      func -- func(y,t0,...) computes the derivative of y at t0.
-      y0   -- initial condition on y (can be a vector).
-      t    -- a sequence of time points for which to solve for y.  The intial
-              value point should be the first element of this sequence.
-      args -- extra arguments to pass to function.
-      Dfun -- the gradient (Jacobian) of func (same input signature as func).
-      col_deriv -- non-zero implies that Dfun defines derivatives down
-                   columns (faster), otherwise Dfun should define derivatives
-                   across rows.
-      full_output -- non-zero to return a dictionary of optional outputs as
-                     the second output.
-      printmessg -- print the convergence message.
+    Returns
+    -------
+    y : array, shape (len(y0), len(t))
+        Array containing the value of y for each desired time in t,
+        with the initial value y0 in the first row.
+    
+    infodict : dict, only returned if full_output == True
+        Dictionary containing additional output information
+        
+        =======  ============================================================
+        key      meaning
+        =======  ============================================================
+        'hu'     vector of step sizes successfully used for each time step.
+        'tcur'   vector with the value of t reached for each time step.
+                 (will always be at least as large as the input times).
+        'tolsf'  vector of tolerance scale factors, greater than 1.0,
+                 computed when a request for too much accuracy was detected.
+        'tsw'    value of t at the time of the last method switch
+                 (given for each time step)
+        'nst'    cumulative number of time steps
+        'nfe'    cumulative number of function evaluations for each time step
+        'nje'    cumulative number of jacobian evaluations for each time step
+        'nqu'    a vector of method orders for each successful step.
+        'imxer'  index of the component of largest magnitude in the
+                 weighted local error vector (e / ewt) on an error return.
+        'lenrw'  the length of the double work array required.
+        'leniw'  the length of integer work array required.
+        'mused'  a vector of method indicators for each successful time step:
+                 1: adams (nonstiff), 2: bdf (stiff)
+        =======  ============================================================
+    
+    Other Parameters
+    ----------------
+    ml, mu : integer
+        If either of these are not-None or non-negative, then the
+        Jacobian is assumed to be banded.  These give the number of
+        lower and upper non-zero diagonals in this banded matrix.
+        For the banded case, Dfun should return a matrix whose
+        columns contain the non-zero bands (starting with the
+        lowest diagonal).  Thus, the return matrix from Dfun should
+        have shape len(y0) * (ml + mu + 1) when ml >=0 or mu >=0
+    rtol, atol : float
+        The input parameters rtol and atol determine the error
+        control performed by the solver.  The solver will control the
+        vector, e, of estimated local errors in y, according to an
+        inequality of the form::         
+            max-norm of (e / ewt) <= 1
+        where ewt is a vector of positive error weights computed as::
+            ewt = rtol * abs(y) + atol
+        rtol and atol can be either vectors the same length as y or scalars.
+    tcrit : array
+        Vector of critical points (e.g. singularities) where integration
+        care should be taken.
+    h0 : float, (0: solver-determined)
+        The step size to be attempted on the first step.
+    hmax : float, (0: solver-determined)
+        The maximum absolute step size allowed.
+    hmin : float, (0: solver-determined)
+        The minimum absolute step size allowed.
+    ixpr : boolean
+        Whether to generate extra printing at method switches.
+    mxstep : integer, (0: solver-determined)
+        Maximum number of (internally defined) steps allowed for each
+        integration point in t.
+    mxhnil : integer, (0: solver-determined)
+        Maximum number of messages printed.
+    mxordn : integer, (0: solver-determined)
+        Maximum order to be allowed for the nonstiff (Adams) method.
+    mxords : integer, (0: solver-determined)
+        Maximum order to be allowed for the stiff (BDF) method.
 
-    Outputs: (y, {infodict,})
-
-      y -- a rank-2 array containing the value of y in each row for each
-           desired time in t (with the initial value y0 in the first row).
-
-      infodict -- a dictionary of optional outputs:
-        'hu'    : a vector of step sizes successfully used for each time step.
-        'tcur'  : a vector with the value of t reached for each time step.
-                  (will always be at least as large as the input times).
-        'tolsf' : a vector of tolerance scale factors, greater than 1.0,
-                  computed when a request for too much accuracy was detected.
-        'tsw'   : the value of t at the time of the last method switch
-                  (given for each time step).
-        'nst'   : the cumulative number of time steps.
-        'nfe'   : the cumulative number of function evaluations for eadh
-                  time step.
-        'nje'   : the cumulative number of jacobian evaluations for each
-                  time step.
-        'nqu'   : a vector of method orders for each successful step.
-        'imxer' : index of the component of largest magnitude in the
-                   weighted local error vector (e / ewt) on an error return.
-        'lenrw' : the length of the double work array required.
-        'leniw' : the length of integer work array required.
-        'mused' : a vector of method indicators for each successful time step:
-                  1 -- adams (nonstiff)
-                  2 -- bdf (stiff)
-
-    Additional Inputs:
-
-      ml, mu -- If either of these are not-None or non-negative, then the
-                Jacobian is assumed to be banded.  These give the number of
-                lower and upper non-zero diagonals in this banded matrix.
-                For the banded case, Dfun should return a matrix whose
-                columns contain the non-zero bands (starting with the
-                lowest diagonal).  Thus, the return matrix from Dfun should
-                have shape len(y0) x (ml + mu + 1) when ml >=0 or mu >=0
-      rtol -- The input parameters rtol and atol determine the error
-      atol    control performed by the solver.  The solver will control the
-              vector, e, of estimated local errors in y, according to an
-              inequality of the form
-                   max-norm of (e / ewt) <= 1
-              where ewt is a vector of positive error weights computed as
-                   ewt = rtol * abs(y) + atol
-              rtol and atol can be either vectors the same length as y or
-              scalars.
-      tcrit -- a vector of critical points (e.g. singularities) where
-               integration care should be taken.
-
-       (For the next inputs a zero default means the solver determines it).
-
-      h0 -- the step size to be attempted on the first step.
-      hmax -- the maximum absolute step size allowed.
-      hmin -- the minimum absolute step size allowed.
-      ixpr -- non-zero to generate extra printing at method switches.
-      mxstep -- maximum number of (internally defined) steps allowed
-                for each integration point in t.
-      mxhnil -- maximum number of messages printed.
-      mxordn -- maximum order to be allowed for the nonstiff (Adams) method.
-      mxords -- maximum order to be allowed for the stiff (BDF) method.
-
-    See also:
-      ode - a more object-oriented integrator based on VODE
-      quad - for finding the area under a curve
+    See Also
+    --------
+    ode : a more object-oriented integrator based on VODE
+    quad : for finding the area under a curve
+    
     """
 
     if ml is None:



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