[Scipy-svn] r4591 - in branches/Interpolate1D: . docs
scipy-svn@scip...
scipy-svn@scip...
Thu Jul 31 18:58:47 CDT 2008
Author: fcady
Date: 2008-07-31 18:58:42 -0500 (Thu, 31 Jul 2008)
New Revision: 4591
Added:
branches/Interpolate1D/_fitpack.pyf
Removed:
branches/Interpolate1D/fitpack.pyf
Modified:
branches/Interpolate1D/TODO.txt
branches/Interpolate1D/docs/tutorial.rst
branches/Interpolate1D/example_script.py
branches/Interpolate1D/fitpack_wrapper.py
branches/Interpolate1D/interpolate1d.py
branches/Interpolate1D/interpolate_wrapper.py
branches/Interpolate1D/setup.py
Log:
fitpack.pyf to _fitpack.pyf to make it more in the background, added 'nearest' interpolate method for more functionality
Modified: branches/Interpolate1D/TODO.txt
===================================================================
--- branches/Interpolate1D/TODO.txt 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/TODO.txt 2008-07-31 23:58:42 UTC (rev 4591)
@@ -15,11 +15,11 @@
In fitpack_wrapper the smoothing parameter is s. It now defaults
to 0.0 (exact interpolation). Zero smoothing and moderate (s ~ 1)
are fast, but small non-zero s makes the algorithm VERY slow.
+
+ This appears resolved, in that Spline can do smoothing (but defaults
+ to not), and user-defined classes are allowed to smooth.
- Currently the user does see s in Interpolate1d; no smoothing
- is available. The Spline class, however, has it available (default = 0.0).
-
**pick best spline
Under-the-hood machinery currently comes from _interpolate.cpp
(used in enthought.interpolate) and FITPACK (Fortran, used in
@@ -41,6 +41,21 @@
that stuff needs to be cleaned up, and the
rest needs to be either removed or set aside.
+**allow y to be 2-dimensional?
+ It is not decided whether this feature should be supported, but
+ I don't think it should; I think there should be another class with
+ that functionality which wraps Interpolate1d. The main reasons
+ are:
+ 1) interpolation should probably be along columns, so the user
+ can enter data as enter the data as y=array([obs1, obs2, ...]). But
+ the interpolate_wrapper and fitpack_wrapper interpolate along
+ rows; this means there would be messy transposes in the code.
+ 2) FITPACK doesn't support 2D y arrays, which means we would
+ have to store the y columns separately
+ 3) If we remove bad data, bearing in mind (2), we would also
+ have to store copies of x, since the bad data in the y cols aren't
+ at the same locations, meaning that different data points should be
+ deleted for each column.
**better handling of variable types
Currently everything is cast to a float64 if it is not already
@@ -56,7 +71,7 @@
-*********** DOCUENTATION-TYPE AND NON-URGENT TASKS *******
+*********** DOCUMENTATION-TYPE AND NON-URGENT TASKS *******
**improve regression tests
desired for fitpack_wrapper and _interpolate_wrapper
@@ -64,10 +79,7 @@
really basic.
-**improve unit tests
- interpolate1d.py has its own unit tests, which also call
- the unit tests of fitpack_wrapper and _interpolate_wrapper.
- But they could surely be made better.
+**improve unit tests in tests directory
**comment all files
@@ -102,7 +114,7 @@
********* LONGER TERM ************
**update for 2D and ND
- This will probably take the form of two additional
+ This will take the form of two additional
classes both modelled after interpolate1d. Thus it probably
shouldn't be done until interpolate1d is more settled.
@@ -147,20 +159,3 @@
differentiation of functionality (one for splines, one for simple
operations, etc), rather than being a holdover of where they
were stolen from.
-
-
-**allow y to be 2-dimensional?
- It is not decided whether this feature should be supported, but
- I don't think it should; I think there should be another class with
- that functionality which wraps Interpolate1d. The main reasons
- are:
- 1) interpolation should probably be along columns, so the user
- can enter data as enter the data as y=array([obs1, obs2, ...]). But
- the interpolate_wrapper and fitpack_wrapper interpolate along
- rows; this means there would be messy transposes in the code.
- 2) FITPACK doesn't support 2D y arrays, which means we would
- have to store the y columns separately
- 3) If we remove bad data, bearing in mind (2), we would also
- have to store copies of x, since the bad data in the y cols aren't
- at the same locations, meaning that different data points should be
- deleted for each column.
Copied: branches/Interpolate1D/_fitpack.pyf (from rev 4587, branches/Interpolate1D/fitpack.pyf)
Modified: branches/Interpolate1D/docs/tutorial.rst
===================================================================
--- branches/Interpolate1D/docs/tutorial.rst 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/docs/tutorial.rst 2008-07-31 23:58:42 UTC (rev 4591)
@@ -481,6 +481,9 @@
#) s
If s is zero, the interpolation is exact. If s is not 0, the curve is smoothe subject to
the constraint that sum((w[i]*( y[i]-s(x[i]) ))**2,axis=0) <= s
+
+ BEWARE : in the current implementation of the code, if s is small but not zero,
+ instantiating Spline can become painfully slow.
At calling:
Modified: branches/Interpolate1D/example_script.py
===================================================================
--- branches/Interpolate1D/example_script.py 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/example_script.py 2008-07-31 23:58:42 UTC (rev 4591)
@@ -82,10 +82,6 @@
interp = I.Interpolate1d(x, y, fitpack_wrapper.Spline(k=2))
y_quad2 = interp(newx)
- # 3rd order spline with additional keyword arguments
- interp = I.Interpolate1d(x, y, fitpack_wrapper.Spline, kindkw = {'k':3})
- y_cubic2 = interp(newx)
-
# 4th order spline
interp = I.Interpolate1d(x, y, 'Quartic')
y_quartic2 = interp(newx)
@@ -100,7 +96,6 @@
P.plot(newx, y_block2, 'g')
P.plot(newx, y_linear2, 'b')
P.plot(newx, y_quad2, 'r')
- P.plot(newx, y_cubic2, 'm')
P.plot(newx, y_quartic2, 'y')
P.plot(newx, y_quintic2, 'y')
P.title( "same data through different interface" )
Deleted: branches/Interpolate1D/fitpack.pyf
===================================================================
--- branches/Interpolate1D/fitpack.pyf 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/fitpack.pyf 2008-07-31 23:58:42 UTC (rev 4591)
@@ -1,479 +0,0 @@
-! -*- f90 -*-
-! Author: Pearu Peterson <pearu@cens.ioc.ee>
-!
-python module _dfitpack ! in
-
- usercode '''
-
-static double dmax(double* seq,int len) {
- double val;
- int i;
- if (len<1)
- return -1e308;
- val = seq[0];
- for(i=1;i<len;++i)
- if (seq[i]>val) val = seq[i];
- return val;
-}
-static double dmin(double* seq,int len) {
- double val;
- int i;
- if (len<1)
- return 1e308;
- val = seq[0];
- for(i=1;i<len;++i)
- if (seq[i]<val) val = seq[i];
- return val;
-}
-static double calc_b(double* x,int m,double* tx,int nx) {
- double val1 = dmin(x,m);
- double val2 = dmin(tx,nx);
- if (val2>val1) return val1;
- val1 = dmax(tx,nx);
- return val2 - (val1-val2)/nx;
-}
-static double calc_e(double* x,int m,double* tx,int nx) {
- double val1 = dmax(x,m);
- double val2 = dmax(tx,nx);
- if (val2<val1) return val1;
- val1 = dmin(tx,nx);
- return val2 + (val2-val1)/nx;
-}
-static int imax(int i1,int i2) {
- return MAX(i1,i2);
-}
-
-static int calc_surfit_lwrk1(int m, int kx, int ky, int nxest, int nyest) {
- int u = nxest-kx-1;
- int v = nyest-ky-1;
- int km = MAX(kx,ky)+1;
- int ne = MAX(nxest,nyest);
- int bx = kx*v+ky+1;
- int by = ky*u+kx+1;
- int b1,b2;
- if (bx<=by) {b1=bx;b2=bx+v-ky;}
- else {b1=by;b2=by+u-kx;}
- return u*v*(2+b1+b2)+2*(u+v+km*(m+ne)+ne-kx-ky)+b2+1;
-}
-static int calc_surfit_lwrk2(int m, int kx, int ky, int nxest, int nyest) {
- int u = nxest-kx-1;
- int v = nyest-ky-1;
- int bx = kx*v+ky+1;
- int by = ky*u+kx+1;
- int b2 = (bx<=by?bx+v-ky:by+u-kx);
- return u*v*(b2+1)+b2;
-}
-
-static int calc_regrid_lwrk(int mx, int my, int kx, int ky,
- int nxest, int nyest) {
- int u = MAX(my, nxest);
- return 4+nxest*(my+2*kx+5)+nyest*(2*ky+5)+mx*(kx+1)+my*(ky+1)+u;
-}
-'''
-
- interface
-
- !!!!!!!!!! Univariate spline !!!!!!!!!!!
-
- subroutine splev(t,n,c,k,x,y,m,ier)
- ! y = splev(t,c,k,x)
- real*8 dimension(n),intent(in) :: t
- integer intent(hide),depend(t) :: n=len(t)
- real*8 dimension(n),depend(n,k),check(len(c)==n),intent(in) :: c
- integer :: k
- real*8 dimension(m),intent(in) :: x
- real*8 dimension(m),depend(m),intent(out) :: y
- integer intent(hide),depend(x) :: m=len(x)
- integer intent(hide) :: ier
- end subroutine splev
-
- subroutine splder(t,n,c,k,nu,x,y,m,wrk,ier)
- ! dy = splder(t,c,k,x,[nu])
- real*8 dimension(n) :: t
- integer depend(t),intent(hide) :: n=len(t)
- real*8 dimension(n),depend(n,k),check(len(c)==n),intent(in) :: c
- integer :: k
- integer depend(k),check(0<=nu && nu<=k) :: nu = 1
- real*8 dimension(m) :: x
- real*8 dimension(m),depend(m),intent(out) :: y
- integer depend(x),intent(hide) :: m=len(x)
- real*8 dimension(n),depend(n),intent(cache,hide) :: wrk
- integer intent(hide) :: ier
- end subroutine splder
-
- function splint(t,n,c,k,a,b,wrk)
- ! iy = splint(t,c,k,a,b)
- real*8 dimension(n),intent(in) :: t
- integer intent(hide),depend(t) :: n=len(t)
- real*8 dimension(n),depend(n),check(len(c)==n) :: c
- integer intent(in) :: k
- real*8 intent(in) :: a
- real*8 intent(in) :: b
- real*8 dimension(n),depend(n),intent(cache,hide) :: wrk
- real*8 :: splint
- end function splint
-
- subroutine sproot(t,n,c,zero,mest,m,ier)
- ! zero,m,ier = sproot(t,c[,mest])
- real*8 dimension(n),intent(in) :: t
- integer intent(hide),depend(t),check(n>=8) :: n=len(t)
- real*8 dimension(n),depend(n),check(len(c)==n) :: c
- real*8 dimension(mest),intent(out),depend(mest) :: zero
- integer optional,intent(in),depend(n) :: mest=3*(n-7)
- integer intent(out) :: m
- integer intent(out) :: ier
- end subroutine sproot
-
- subroutine spalde(t,n,c,k,x,d,ier)
- ! d,ier = spalde(t,c,k,x)
-
- callprotoargument double*,int*,double*,int*,double*,double*,int*
- callstatement {int k1=k+1; (*f2py_func)(t,&n,c,&k1,&x,d,&ier); }
-
- real*8 dimension(n) :: t
- integer intent(hide),depend(t) :: n=len(t)
- real*8 dimension(n),depend(n),check(len(c)==n) :: c
- integer intent(in) :: k
- real*8 intent(in) :: x
- real*8 dimension(k+1),intent(out),depend(k) :: d
- integer intent(out) :: ier
- end subroutine spalde
-
- subroutine curfit(iopt,m,x,y,w,xb,xe,k,s,nest,n,t,c,fp,wrk,lwrk,iwrk,ier)
- ! in curfit.f
- integer :: iopt
- integer intent(hide),depend(x),check(m>k),depend(k) :: m=len(x)
- real*8 dimension(m) :: x
- real*8 dimension(m),depend(m),check(len(y)==m) :: y
- real*8 dimension(m),depend(m),check(len(w)==m) :: w
- real*8 optional,depend(x),check(xb<=x[0]) :: xb = x[0]
- real*8 optional,depend(x,m),check(xe>=x[m-1]) :: xe = x[m-1]
- integer optional,check(1<=k && k <=5),intent(in) :: k=3
- real*8 optional,check(s>=0.0) :: s = 0.0
- integer intent(hide),depend(t) :: nest=len(t)
- integer intent(out), depend(nest) :: n=nest
- real*8 dimension(nest),intent(inout) :: t
- real*8 dimension(n),intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(lwrk),intent(inout) :: wrk
- integer intent(hide),depend(wrk) :: lwrk=len(wrk)
- integer dimension(nest),intent(inout) :: iwrk
- integer intent(out) :: ier
- end subroutine curfit
-
- subroutine percur(iopt,m,x,y,w,k,s,nest,n,t,c,fp,wrk,lwrk,iwrk,ier)
- ! in percur.f
- integer :: iopt
- integer intent(hide),depend(x),check(m>k),depend(k) :: m=len(x)
- real*8 dimension(m) :: x
- real*8 dimension(m),depend(m),check(len(y)==m) :: y
- real*8 dimension(m),depend(m),check(len(w)==m) :: w
- integer optional,check(1<=k && k <=5),intent(in) :: k=3
- real*8 optional,check(s>=0.0) :: s = 0.0
- integer intent(hide),depend(t) :: nest=len(t)
- integer intent(out), depend(nest) :: n=nest
- real*8 dimension(nest),intent(inout) :: t
- real*8 dimension(n),intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(lwrk),intent(inout) :: wrk
- integer intent(hide),depend(wrk) :: lwrk=len(wrk)
- integer dimension(nest),intent(inout) :: iwrk
- integer intent(out) :: ier
- end subroutine percur
-
-
- subroutine parcur(iopt,ipar,idim,m,u,mx,x,w,ub,ue,k,s,nest,n,t,nc,c,fp,wrk,lwrk,iwrk,ier)
- ! in parcur.f
- integer check(iopt>=-1 && iopt <= 1):: iopt
- integer check(ipar == 1 || ipar == 0) :: ipar
- integer check(idim > 0 && idim < 11) :: idim
- integer intent(hide),depend(u,k),check(m>k) :: m=len(u)
- real*8 dimension(m), intent(inout) :: u
- integer intent(hide),depend(x,idim,m),check(mx>=idim*m) :: mx=len(x)
- real*8 dimension(mx) :: x
- real*8 dimension(m) :: w
- real*8 :: ub
- real*8 :: ue
- integer optional, check(1<=k && k<=5) :: k=3.0
- real*8 optional, check(s>=0.0) :: s = 0.0
- integer intent(hide), depend(t) :: nest=len(t)
- integer intent(out), depend(nest) :: n=nest
- real*8 dimension(nest), intent(inout) :: t
- integer intent(hide), depend(c,nest,idim), check(nc>=idim*nest) :: nc=len(c)
- real*8 dimension(nc), intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(lwrk), intent(inout) :: wrk
- integer intent(hide),depend(wrk) :: lwrk=len(wrk)
- integer dimension(nest), intent(inout) :: iwrk
- integer intent(out) :: ier
- end subroutine parcur
-
-
- subroutine fpcurf0(iopt,x,y,w,m,xb,xe,k,s,nest,tol,maxit,k1,k2,n,t,c,fp,fpint,wrk,nrdata,ier)
- ! x,y,w,xb,xe,k,s,n,t,c,fp,fpint,nrdata,ier = \
- ! fpcurf0(x,y,k,[w,xb,xe,s,nest])
-
- fortranname fpcurf
- callprotoargument int*,double*,double*,double*,int*,double*,double*,int*,double*,int*,double*,int*,int*,int*,int*,double*,double*,double*,double*,double*,double*,double*,double*,double*,int*,int*
- callstatement (*f2py_func)(&iopt,x,y,w,&m,&xb,&xe,&k,&s,&nest,&tol,&maxit,&k1,&k2,&n,t,c,&fp,fpint,wrk,wrk+nest,wrk+nest*k2,wrk+nest*2*k2,wrk+nest*3*k2,nrdata,&ier)
-
- integer intent(hide) :: iopt = 0
- real*8 dimension(m),intent(in,out) :: x
- real*8 dimension(m),depend(m),check(len(y)==m),intent(in,out) :: y
- real*8 dimension(m),depend(m),check(len(w)==m),intent(in,out) :: w = 1.0
- integer intent(hide),depend(x),check(m>k),depend(k) :: m=len(x)
- real*8 intent(in,out),depend(x),check(xb<=x[0]) :: xb = x[0]
- real*8 intent(in,out),depend(x,m),check(xe>=x[m-1]) :: xe = x[m-1]
- integer check(1<=k && k<=5),intent(in,out) :: k
- real*8 check(s>=0.0),depend(m),intent(in,out) :: s = m
- integer intent(in),depend(m,s,k,k1),check(nest>=2*k1) :: nest = (s==0.0?m+k+1:MAX(m/2,2*k1))
- real*8 intent(hide) :: tol = 0.001
- integer intent(hide) :: maxit = 20
- integer intent(hide),depend(k) :: k1=k+1
- integer intent(hide),depend(k) :: k2=k+2
- integer intent(out) :: n
- real*8 dimension(nest),intent(out),depend(nest) :: t
- real*8 dimension(nest),depend(nest),intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(nest),depend(nest),intent(out,cache) :: fpint
- real*8 dimension(nest*3*k2+m*k1),intent(cache,hide),depend(nest,k1,k2,m) :: wrk
- integer dimension(nest),depend(nest),intent(out,cache) :: nrdata
- integer intent(out) :: ier
- end subroutine fpcurf0
-
- subroutine fpcurf1(iopt,x,y,w,m,xb,xe,k,s,nest,tol,maxit,k1,k2,n,t,c,fp,fpint,wrk,nrdata,ier)
- ! x,y,w,xb,xe,k,s,n,t,c,fp,fpint,nrdata,ier = \
- ! fpcurf1(x,y,w,xb,xe,k,s,n,t,c,fp,fpint,nrdata,ier)
-
- fortranname fpcurf
- callprotoargument int*,double*,double*,double*,int*,double*,double*,int*,double*,int*,double*,int*,int*,int*,int*,double*,double*,double*,double*,double*,double*,double*,double*,double*,int*,int*
- callstatement (*f2py_func)(&iopt,x,y,w,&m,&xb,&xe,&k,&s,&nest,&tol,&maxit,&k1,&k2,&n,t,c,&fp,fpint,wrk,wrk+nest,wrk+nest*k2,wrk+nest*2*k2,wrk+nest*3*k2,nrdata,&ier)
-
- integer intent(hide) :: iopt = 1
- real*8 dimension(m),intent(in,out,overwrite) :: x
- real*8 dimension(m),depend(m),check(len(y)==m),intent(in,out,overwrite) :: y
- real*8 dimension(m),depend(m),check(len(w)==m),intent(in,out,overwrite) :: w
- integer intent(hide),depend(x),check(m>k),depend(k) :: m=len(x)
- real*8 intent(in,out) :: xb
- real*8 intent(in,out) :: xe
- integer check(1<=k && k<=5),intent(in,out) :: k
- real*8 check(s>=0.0),intent(in,out) :: s
- integer intent(hide),depend(t) :: nest = len(t)
- real*8 intent(hide) :: tol = 0.001
- integer intent(hide) :: maxit = 20
- integer intent(hide),depend(k) :: k1=k+1
- integer intent(hide),depend(k) :: k2=k+2
- integer intent(in,out) :: n
- real*8 dimension(nest),intent(in,out,overwrite) :: t
- real*8 dimension(nest),depend(nest),check(len(c)==nest),intent(in,out,overwrite) :: c
- real*8 intent(in,out) :: fp
- real*8 dimension(nest),depend(nest),check(len(fpint)==nest),intent(in,out,cache,overwrite) :: fpint
- real*8 dimension(nest*3*k2+m*k1),intent(cache,hide),depend(nest,k1,k2,m) :: wrk
- integer dimension(nest),depend(nest),check(len(nrdata)==nest),intent(in,out,cache,overwrite) :: nrdata
- integer intent(in,out) :: ier
- end subroutine fpcurf1
-
- subroutine fpcurfm1(iopt,x,y,w,m,xb,xe,k,s,nest,tol,maxit,k1,k2,n,t,c,fp,fpint,wrk,nrdata,ier)
- ! x,y,w,xb,xe,k,s,n,t,c,fp,fpint,nrdata,ier = \
- ! fpcurfm1(x,y,k,t,[w,xb,xe])
-
- fortranname fpcurf
- callprotoargument int*,double*,double*,double*,int*,double*,double*,int*,double*,int*,double*,int*,int*,int*,int*,double*,double*,double*,double*,double*,double*,double*,double*,double*,int*,int*
- callstatement (*f2py_func)(&iopt,x,y,w,&m,&xb,&xe,&k,&s,&nest,&tol,&maxit,&k1,&k2,&n,t,c,&fp,fpint,wrk,wrk+nest,wrk+nest*k2,wrk+nest*2*k2,wrk+nest*3*k2,nrdata,&ier)
-
- integer intent(hide) :: iopt = -1
- real*8 dimension(m),intent(in,out) :: x
- real*8 dimension(m),depend(m),check(len(y)==m),intent(in,out) :: y
- real*8 dimension(m),depend(m),check(len(w)==m),intent(in,out) :: w = 1.0
- integer intent(hide),depend(x),check(m>k),depend(k) :: m=len(x)
- real*8 intent(in,out),depend(x),check(xb<=x[0]) :: xb = x[0]
- real*8 intent(in,out),depend(x,m),check(xe>=x[m-1]) :: xe = x[m-1]
- integer check(1<=k && k<=5),intent(in,out) :: k
- real*8 intent(out) :: s = -1
- integer intent(hide),depend(n) :: nest = n
- real*8 intent(hide) :: tol = 0.001
- integer intent(hide) :: maxit = 20
- integer intent(hide),depend(k) :: k1=k+1
- integer intent(hide),depend(k) :: k2=k+2
- integer intent(out),depend(t) :: n = len(t)
- real*8 dimension(n),intent(in,out,overwrite) :: t
- real*8 dimension(nest),depend(nest),intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(nest),depend(nest),intent(out,cache) :: fpint
- real*8 dimension(nest*3*k2+m*k1),intent(cache,hide),depend(nest,k1,k2,m) :: wrk
- integer dimension(nest),depend(nest),intent(out,cache) :: nrdata
- integer intent(out) :: ier
- end subroutine fpcurfm1
-
- !!!!!!!!!! Bivariate spline !!!!!!!!!!!
-
- subroutine bispev(tx,nx,ty,ny,c,kx,ky,x,mx,y,my,z,wrk,lwrk,iwrk,kwrk,ier)
- ! z,ier = bispev(tx,ty,c,kx,ky,x,y)
- real*8 dimension(nx),intent(in) :: tx
- integer intent(hide),depend(tx) :: nx=len(tx)
- real*8 dimension(ny),intent(in) :: ty
- integer intent(hide),depend(ty) :: ny=len(ty)
- real*8 intent(in),dimension((nx-kx-1)*(ny-ky-1)),depend(nx,ny,kx,ky),&
- check(len(c)==(nx-kx-1)*(ny-ky-1)):: c
- integer :: kx
- integer :: ky
- real*8 intent(in),dimension(mx) :: x
- integer intent(hide),depend(x) :: mx=len(x)
- real*8 intent(in),dimension(my) :: y
- integer intent(hide),depend(y) :: my=len(y)
- real*8 dimension(mx,my),depend(mx,my),intent(out,c) :: z
- real*8 dimension(lwrk),depend(lwrk),intent(hide,cache) :: wrk
- integer intent(hide),depend(mx,kx,my,ky) :: lwrk=mx*(kx+1)+my*(ky+1)
- integer dimension(kwrk),depend(kwrk),intent(hide,cache) :: iwrk
- integer intent(hide),depend(mx,my) :: kwrk=mx+my
- integer intent(out) :: ier
- end subroutine bispev
-
- subroutine surfit_smth(iopt,m,x,y,z,w,xb,xe,yb,ye,kx,ky,s,nxest,nyest,&
- nmax,eps,nx,tx,ny,ty,c,fp,wrk1,lwrk1,wrk2,lwrk2,&
- iwrk,kwrk,ier)
- ! nx,tx,ny,ty,c,fp,ier = surfit_smth(x,y,z,[w,xb,xe,yb,ye,kx,ky,s,eps,lwrk2])
-
- fortranname surfit
-
- integer intent(hide) :: iopt=0
- integer intent(hide),depend(x,kx,ky),check(m>=(kx+1)*(ky+1)) &
- :: m=len(x)
- real*8 dimension(m) :: x
- real*8 dimension(m),depend(m),check(len(y)==m) :: y
- real*8 dimension(m),depend(m),check(len(z)==m) :: z
- real*8 optional,dimension(m),depend(m),check(len(w)==m) :: w = 1.0
- real*8 optional,depend(x,m) :: xb=dmin(x,m)
- real*8 optional,depend(x,m) :: xe=dmax(x,m)
- real*8 optional,depend(y,m) :: yb=dmin(y,m)
- real*8 optional,depend(y,m) :: ye=dmax(y,m)
- integer check(1<=kx && kx<=5) :: kx = 3
- integer check(1<=ky && ky<=5) :: ky = 3
- real*8 optional,check(0.0<=s) :: s = m
- integer optional,depend(kx,m),check(nxest>=2*(kx+1)) &
- :: nxest = imax(kx+1+sqrt(m/2),2*(kx+1))
- integer optional,depend(ky,m),check(nyest>=2*(ky+1)) &
- :: nyest = imax(ky+1+sqrt(m/2),2*(ky+1))
- integer intent(hide),depend(nxest,nyest) :: nmax=MAX(nxest,nyest)
- real*8 optional,check(0.0<eps && eps<1.0) :: eps = 1e-16
- integer intent(out) :: nx
- real*8 dimension(nmax),intent(out),depend(nmax) :: tx
- integer intent(out) :: ny
- real*8 dimension(nmax),intent(out),depend(nmax) :: ty
- real*8 dimension((nxest-kx-1)*(nyest-ky-1)), &
- depend(kx,ky,nxest,nyest),intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(lwrk1),intent(cache,out),depend(lwrk1) :: wrk1
- integer intent(hide),depend(m,kx,ky,nxest,nyest) &
- :: lwrk1=calc_surfit_lwrk1(m,kx,ky,nxest,nyest)
- real*8 dimension(lwrk2),intent(cache,hide),depend(lwrk2) :: wrk2
- integer optional,intent(in),depend(kx,ky,nxest,nyest) &
- :: lwrk2=calc_surfit_lwrk2(m,kx,ky,nxest,nyest)
- integer dimension(kwrk),depend(kwrk),intent(cache,hide) :: iwrk
- integer intent(hide),depend(m,nxest,nyest,kx,ky) &
- :: kwrk=m+(nxest-2*kx-1)*(nyest-2*ky-1)
- integer intent(out) :: ier
- end subroutine surfit_smth
-
- subroutine surfit_lsq(iopt,m,x,y,z,w,xb,xe,yb,ye,kx,ky,s,nxest,nyest,&
- nmax,eps,nx,tx,ny,ty,c,fp,wrk1,lwrk1,wrk2,lwrk2,&
- iwrk,kwrk,ier)
- ! tx,ty,c,fp,ier = surfit_lsq(x,y,z,tx,ty,[w,xb,xe,yb,ye,kx,ky,eps,lwrk2])
-
- fortranname surfit
-
- integer intent(hide) :: iopt=-1
- integer intent(hide),depend(x,kx,ky),check(m>=(kx+1)*(ky+1)) &
- :: m=len(x)
- real*8 dimension(m) :: x
- real*8 dimension(m),depend(m),check(len(y)==m) :: y
- real*8 dimension(m),depend(m),check(len(z)==m) :: z
- real*8 optional,dimension(m),depend(m),check(len(w)==m) :: w = 1.0
- real*8 optional,depend(x,tx,m,nx) :: xb=calc_b(x,m,tx,nx)
- real*8 optional,depend(x,tx,m,nx) :: xe=calc_e(x,m,tx,nx)
- real*8 optional,depend(y,ty,m,ny) :: yb=calc_b(y,m,ty,ny)
- real*8 optional,depend(y,ty,m,ny) :: ye=calc_e(y,m,ty,ny)
- integer check(1<=kx && kx<=5) :: kx = 3
- integer check(1<=ky && ky<=5) :: ky = 3
- real*8 intent(hide) :: s = 0.0
- integer intent(hide),depend(nx) :: nxest = nx
- integer intent(hide),depend(ny) :: nyest = ny
- integer intent(hide),depend(nx,ny) :: nmax=MAX(nx,ny)
- real*8 optional,check(0.0<eps && eps<1.0) :: eps = 1e-16
- integer intent(hide),depend(tx,kx),check(2*kx+2<=nx) :: nx = len(tx)
- real*8 dimension(nx),intent(in,out,overwrite) :: tx
- integer intent(hide),depend(ty,ky),check(2*ky+2<=ny) :: ny = len(ty)
- real*8 dimension(ny),intent(in,out,overwrite) :: ty
- real*8 dimension((nx-kx-1)*(ny-ky-1)),depend(kx,ky,nx,ny),intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(lwrk1),intent(cache,hide),depend(lwrk1) :: wrk1
- integer intent(hide),depend(m,kx,ky,nxest,nyest) &
- :: lwrk1=calc_surfit_lwrk1(m,kx,ky,nxest,nyest)
- real*8 dimension(lwrk2),intent(cache,hide),depend(lwrk2) :: wrk2
- integer optional,intent(in),depend(kx,ky,nxest,nyest) &
- :: lwrk2=calc_surfit_lwrk2(m,kx,ky,nxest,nyest)
- integer dimension(kwrk),depend(kwrk),intent(cache,hide) :: iwrk
- integer intent(hide),depend(m,nx,ny,kx,ky) &
- :: kwrk=m+(nx-2*kx-1)*(ny-2*ky-1)
- integer intent(out) :: ier
- end subroutine surfit_lsq
-
- subroutine regrid_smth(iopt,mx,x,my,y,z,xb,xe,yb,ye,kx,ky,s,&
- nxest,nyest,nx,tx,ny,ty,c,fp,wrk,lwrk,iwrk,kwrk,ier)
- ! nx,tx,ny,ty,c,fp,ier = regrid_smth(x,y,z,[xb,xe,yb,ye,kx,ky,s])
-
- fortranname regrid
-
- integer intent(hide) :: iopt=0
- integer intent(hide),depend(x,kx),check(mx>kx) :: mx=len(x)
- real*8 dimension(mx) :: x
- integer intent(hide),depend(y,ky),check(my>ky) :: my=len(y)
- real*8 dimension(my) :: y
- real*8 dimension(mx*my),depend(mx,my),check(len(z)==mx*my) :: z
- real*8 optional,depend(x,mx) :: xb=dmin(x,mx)
- real*8 optional,depend(x,mx) :: xe=dmax(x,mx)
- real*8 optional,depend(y,my) :: yb=dmin(y,my)
- real*8 optional,depend(y,my) :: ye=dmax(y,my)
- integer optional,check(1<=kx && kx<=5) :: kx = 3
- integer optional,check(1<=ky && ky<=5) :: ky = 3
- real*8 optional,check(0.0<=s) :: s = 0.0
- integer intent(hide),depend(kx,mx),check(nxest>=2*(kx+1)) &
- :: nxest = mx+kx+1
- integer intent(hide),depend(ky,my),check(nyest>=2*(ky+1)) &
- :: nyest = my+ky+1
- integer intent(out) :: nx
- real*8 dimension(nxest),intent(out),depend(nxest) :: tx
- integer intent(out) :: ny
- real*8 dimension(nyest),intent(out),depend(nyest) :: ty
- real*8 dimension((nxest-kx-1)*(nyest-ky-1)), &
- depend(kx,ky,nxest,nyest),intent(out) :: c
- real*8 intent(out) :: fp
- real*8 dimension(lwrk),intent(cache,hide),depend(lwrk) :: wrk
- integer intent(hide),depend(mx,my,kx,ky,nxest,nyest) &
- :: lwrk=calc_regrid_lwrk(mx,my,kx,ky,nxest,nyest)
- integer dimension(kwrk),depend(kwrk),intent(cache,hide) :: iwrk
- integer intent(hide),depend(mx,my,nxest,nyest) &
- :: kwrk=3+mx+my+nxest+nyest
- integer intent(out) :: ier
- end subroutine regrid_smth
-
- function dblint(tx,nx,ty,ny,c,kx,ky,xb,xe,yb,ye,wrk)
- ! iy = dblint(tx,ty,c,kx,ky,xb,xe,yb,ye)
- real*8 dimension(nx),intent(in) :: tx
- integer intent(hide),depend(tx) :: nx=len(tx)
- real*8 dimension(ny),intent(in) :: ty
- integer intent(hide),depend(ty) :: ny=len(ty)
- real*8 intent(in),dimension((nx-kx-1)*(ny-ky-1)),depend(nx,ny,kx,ky),&
- check(len(c)==(nx-kx-1)*(ny-ky-1)):: c
- integer :: kx
- integer :: ky
- real*8 intent(in) :: xb
- real*8 intent(in) :: xe
- real*8 intent(in) :: yb
- real*8 intent(in) :: ye
- real*8 dimension(nx+ny-kx-ky-2),depend(nx,ny,kx,ky),intent(cache,hide) :: wrk
- real*8 :: dblint
- end function dblint
- end interface
-end python module _dfitpack
-
Modified: branches/Interpolate1D/fitpack_wrapper.py
===================================================================
--- branches/Interpolate1D/fitpack_wrapper.py 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/fitpack_wrapper.py 2008-07-31 23:58:42 UTC (rev 4591)
@@ -1,8 +1,13 @@
"""
This module is used for spline interpolation, and functions
as a wrapper around the FITPACK Fortran interpolation
-package.
+package. Its functionality is contained in the Spline
+class.
+Spline is primarily meant to be called by Interpolate1d
+or inter1d, but is a stand-alone class in its own right.
+
+
The code has been modified from an older version of
scipy.interpolate, where it was directly called by the
user. As such, it includes functionality not available through
@@ -29,10 +34,6 @@
Can include least-squares fitting.
- See also:
-
- splrep, splev, sproot, spint, spalde - an older wrapping of FITPACK
- BivariateSpline - a similar class for bivariate spline interpolation
"""
def __init__(self, x=None, y=None, w=None, bbox = [None]*2, k=3, s=0.0):
@@ -43,16 +44,14 @@
Optional input:
w - positive 1-d sequence of weights
- bbox - 2-sequence specifying the boundary of
+ bbox - 2-sequence specifying the boundary of
the approximation interval.
By default, bbox=[x[0],x[-1]]
- k=3 - degree of the univariate spline.
+ k=3 - degree of the univariate spline.
s - positive smoothing factor defined for
estimation condition:
sum((w[i]*( y[i]-s(x[i]) ))**2,axis=0) <= s
- Default s=len(w) which should be a good value
- if 1/w[i] is an estimate of the standard
- deviation of y[i].
+ Default s=0
"""
self._k = k
Modified: branches/Interpolate1D/interpolate1d.py
===================================================================
--- branches/Interpolate1D/interpolate1d.py 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/interpolate1d.py 2008-07-31 23:58:42 UTC (rev 4591)
@@ -1,18 +1,22 @@
# FIXME: information strings giving mathematical descriptions of the actions
# of the functions.
-from interpolate_wrapper import linear, logarithmic, block, \
- block_average_above, atleast_1d_and_contiguous
+from interpolate_wrapper import atleast_1d_and_contiguous, \
+ linear, logarithmic, block, block_average_above, nearest
from fitpack_wrapper import Spline
import numpy as np
from numpy import array, arange, empty, float64, NaN
# dictionary of interpolation functions/classes/objects
method_register = \
- { 'linear' : linear,
+ { # functions
+ 'linear' : linear,
'logarithmic' : logarithmic,
'block' : block,
'block_average_above' : block_average_above,
+ 'nearest' : nearest,
+
+ # Splines
'Spline' : Spline, 'spline' : Spline,
'Quadratic' : Spline(k=2), 'quadratic' : Spline(k=2),
'Quad' : Spline(k=2), 'quad' : Spline(k=2),
Modified: branches/Interpolate1D/interpolate_wrapper.py
===================================================================
--- branches/Interpolate1D/interpolate_wrapper.py 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/interpolate_wrapper.py 2008-07-31 23:58:42 UTC (rev 4591)
@@ -6,9 +6,27 @@
import sys
import _interpolate # C extension. Does all the real work.
-def atleast_1d_and_contiguous(ary, typecode = np.float64):
- return np.atleast_1d( np.ascontiguousarray(ary, typecode) )
+def atleast_1d_and_contiguous(ary, dtype = np.float64):
+ return np.atleast_1d( np.ascontiguousarray(ary, dtype) )
+def nearest(x, y, new_x):
+ """ Rounds each new_x[i] to the closest value in x
+ and returns corresponding y.
+ """
+ shifted_x = np.concatenate(( np.array([x[0]-1]) , x[0:-1] ))
+
+ midpoints_of_x = atleast_1d_and_contiguous( .5*(x + shifted_x) )
+ new_x = atleast_1d_and_contiguous(new_x)
+
+ TINY = 1e-10
+ indices = np.searchsorted(midpoints_of_x, new_x+TINY)-1
+ indices = np.atleast_1d(np.clip(indices, 0, np.Inf).astype(np.int))
+ new_y = np.take(y, indices, axis=-1)
+
+ return new_y
+
+
+
def linear(x, y, new_x):
""" Linearly interpolates values in new_x based on the values in x and y
@@ -106,7 +124,6 @@
For each new_x[i], finds largest j such that
x[j] < new_x[j], and returns y[j].
"""
-
# find index of values in x that preceed values in x
# This code is a little strange -- we really want a routine that
# returns the index of values where x[j] < x[index]
Modified: branches/Interpolate1D/setup.py
===================================================================
--- branches/Interpolate1D/setup.py 2008-07-31 23:46:55 UTC (rev 4590)
+++ branches/Interpolate1D/setup.py 2008-07-31 23:58:42 UTC (rev 4591)
@@ -22,7 +22,7 @@
# Fortran routines (collectively "FITPACK" for spline interpolation)
config.add_extension('_dfitpack',
- sources=['fitpack.pyf'],
+ sources=['_fitpack.pyf'],
libraries=['_fitpack'],
)
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