Update readme

.gitignore

@@ -1,3 +1,6 @@
+*-f2pywrappers.f
+*module.c
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

README.md

@@ -1,34 +1,73 @@
 # pytspack
- Python Wrapper around the Fortran TSPACK.
-
- The primary purpose of TSPACK is to construct a smooth
- function which interpolates a discrete set of data points.
- The function may be required to have either one or two con-
- tinuous derivatives, and, in the C-2 case, several options
- are provided for selecting end conditions. If the accuracy
- of the data does not warrant interpolation, a smoothing func-
- tion (which does not pass through the data points) may be
- constructed instead. The fitting method is designed to avoid
- extraneous inflection points (associated with rapidly varying
- data values) and preserve local shape properties of the data
- (monotonicity and convexity), or to satisfy the more general
- constraints of bounds on function values or first derivatives.
- The package also provides a parametric representation for con-
- structing general planar curves and space curves.
-
- The fitting function h(x) (or each component h(t) in the
- case of a parametric curve) is defined locally, on each
- interval associated with a pair of adjacent abscissae (knots),
- by its values and first derivatives at the endpoints of the
- interval, along with a nonnegative tension factor SIGMA
- associated with the interval (h is a Hermite interpolatory
- tension spline). With SIGMA = 0, h is the cubic function
- defined by the endpoint values and derivatives, and, as SIGMA
- increases, h approaches the linear interpolant of the endpoint
- values. Since the linear interpolant preserves positivity,
- monotonicity, and convexity of the data, h can be forced to
- preserve these properties by choosing SIGMA sufficiently
- large. Also, since SIGMA varies with intervals, no more
- tension than necessary is used in each interval, resulting in
- a better fit and greater efficiency than is achieved with a
- single constant tension factor.
+
+Python Wrapper around Robert J. Renka's [TSPACK](https://www.netlib.no/netlib/toms/716).
+TSPACK
+
+> TSPACK is a curve-fitting package based on exponential tension splines with automatic selection of tension factors.
+
+## Installation
+
+If you are lucky,
+```
+pip install https://github.com/noaa-oar-arl/pytspack/archive/master.zip --no-deps
+```
+will *just work*.
+
+Otherwise, you can clone the repo and try to build the extension module
+using [`f2py`](https://numpy.org/doc/stable/f2py/index.html) manually...
+
+### Windows
+
+On Windows, with a [GNU Fortran via MSYS2](https://numpy.org/doc/stable/f2py/windows/msys2.html)
+setup, try the following:
+
+1. Clone the repo
+ ```powershell
+ git clone https://github.com/noaa-oar-arl/pytspack
+ cd pytspack
+ ```
+
+2. Build the extension, using one of these options
+
+ Using the `setup.py`:
+ ```
+ python setup.py build_ext --fcompiler=gnu95 --compiler=mingw32 --build-lib=./pytspack
+ ```
+
+ OR
+
+ Using `f2py` directly:
+ ```powershell
+ cd pytspack
+ python -m numpy.f2py -c --fcompiler=gnu95 --compiler=mingw32 -m tspack tspack.f
+ cd ..
+ ```
+
+3. Link pytspack to your active Python environment.
+ ```powershell
+ pip install -e .
+ ```
+
+### Linux
+
+We have seen some issues where some `gcc`s do not want to compile the `fortranobject.c` [^a]
+
+Follow the same general steps as above, but don't use `--compiler=mingw32`.
+
+On NOAA Hera, the default GCC is currently v4.
+Use `module load gnu` to get newer before attempting to install pytspack,
+or use
+```bash
+OPT='-std=c99' python -m numpy.f2py -c -m tspack tspack.f
+```
+to configure `gcc`.
+
+`OPT='-std=c99'` can also be prepended to [the `pip install` above](#installation),
+enabling an installation without cloning the repo.
+
+
+[^a]: As mentioned [here](https://mfix.netl.doe.gov/forum/t/strange-build-error-in-mfix-21-4/3923/3), for example.
+
+## More information
+
+For more information on TSPACK, see [the open-access paper](https://dl.acm.org/doi/10.1145/151271.151277) (Renka, 1993) or [the netlib page](https://www.netlib.no/netlib/toms/716).

pytspack/__init__.py

@@ -1,6 +1,24 @@
-import tspack
 from numpy import array, zeros
 
+try:
+ # Installed extension module
+ import tspack
+except Exception as e1:
+ try:
+ # Locally built extension module
+ from . import tspack
+ except Exception as e2:
+ raise RuntimeWarning(
+ "Unable to import the tspack extension module. "
+ f"Attempting to import installed tspack extension module failed ({e1}). "
+ f"Attempting to import local tspack extension module failed ({e2})."
+ )
+ else:
+ print(
+ f"Attempting to import installed tspack extension module failed ({e1}). "
+ "Using local."
+ )
+
 
 def hval(xp, x, y, yp, sigma):
  """Function which evaluates a Hermite interpolatory ten-
@@ -65,7 +83,9 @@ def tspsi(x, y, ncd=1, slopes=None, curvs=None, per=0, tension=None):
  sigma = 0.0 * x
 
  if slopes is not None and curvs is not None:
- raise ValueError("You can't constrain both the slopes and curvs at the endpoints")
+ raise ValueError(
+ "You can't constrain both the slopes and curvs at the endpoints"
+ )
  if slopes is not None:
  if type(slopes) is not type([]):
  raise TypeError("slopes must be a list: [slope0,slope1]")
@@ -102,12 +122,12 @@ def tspsi(x, y, ncd=1, slopes=None, curvs=None, per=0, tension=None):
  lwk = len(x)
  else:
  lwk = 2 * len(x)
- wk = zeros((lwk,), 'd')
+ wk = zeros((lwk,), "d")
 
  wk, yp, sigma, ier = tspack.tspsi(x, y, ncd, iendc, per, unifrm, wk, yp, sigma)
 
  if ier >= 0:
- return ((x, y, yp, sigma))
+ return (x, y, yp, sigma)
  elif ier == -1:
  raise RuntimeError("Error, N, NCD or IENDC outside valid range")
  elif ier == -2:
@@ -143,9 +163,11 @@ def tspss(x, y, w, per=0, tension=None, s=None, stol=None, full_output=0):
  lwk = 6 * len(x)
  else:
  lwk = 7 * len(x)
- wk = zeros((lwk,), 'd')
+ wk = zeros((lwk,), "d")
 
- wk, sigma, ys, yp, nit, ier = tspack.tspss(x, y, per, unifrm, w, s, stol, wk, sigma, ys, yp)
+ wk, sigma, ys, yp, nit, ier = tspack.tspss(
+ x, y, per, unifrm, w, s, stol, wk, sigma, ys, yp
+ )
 
  if ier == 0:
  mesg = "No errors and constraint is satisfied: chisquare ~ s"
@@ -162,9 +184,9 @@ def tspss(x, y, w, per=0, tension=None, s=None, stol=None, full_output=0):
  elif ier == -4:
  raise RuntimeError("Error, x-values are not strictly increasing")
  if full_output:
- return(xyds, nit, mesg)
+ return (xyds, nit, mesg)
  else:
- return(xyds)
+ return xyds
 
 
 def tsval1(x, xydt, degree=0, verbose=0):

setup.py

@@ -1,18 +1,21 @@
 from numpy.distutils.core import Extension
 
-ext2 = Extension(name='tspack',
- sources=['pytspack/tspack.pyf', 'pytspack/tspack.f'])
+ext = Extension(
+ name="tspack",
+ sources=["pytspack/tspack.pyf", "pytspack/tspack.f"],
+)
 
 if __name__ == "__main__":
  from numpy.distutils.core import setup
- setup(name='pytspack',
- version='0.1',
- description="Wrapper around Robert J. Renka's fortran TSPACK: Tension Spline Curve Fitting Package ",
- author="Barry D. Baker",
- lisense='MIT',
- author_email="[email protected]",
- source=['pytspack'],
- packages=['pytspack'],
- ext_modules=[ext2],
- install_requires=['numpy']
- )
+
+ setup(
+ name="pytspack",
+ version="0.1",
+ description="Wrapper around Robert J. Renka's fortran TSPACK: Tension Spline Curve Fitting Package",
+ author="Barry D. Baker",
+ license="MIT",
+ author_email="[email protected]",
+ packages=["pytspack"],
+ ext_modules=[ext],
+ install_requires=["numpy"],
+ )