util¶
The util module provides a collection of general purpose methods.
- nutils.util.tri_merge(tri, x, mergetol=0)¶
Create connected triangulation by connecting (near) identical points.
Based on a set of coordinates
x
, create a modified copy oftri
with any occurrence ofj
replaced byi
ifx[i]
equalsx[j]
within specified tolerance. The result is a triangulation that remains valid for any associated data vector that follows the same equality relations.Example:
>>> x = [0,0], [1,0], [0,1], [1,0], [1,1] # note: x[1] == x[3]) >>> tri = [0,1,2], [2,3,4] >>> tri_merge(tri, x) array([[0, 1, 2], [2, 1, 4]])
Requires scipy.
- Parameters:
x (
float
array) – Vertex coordinates.tri (
int
array) – Triangulation.mergetol (
float
(optional, default 0)) – Distance within which two points are considered equal. If mergetol == 0 then points are considered equal if and only if their coordinates are identical. If mergetol > 0 (required scipy) then points are considered equal if they are within euclidian distance < mergetol. If mergetol < 0 then tri is returned unchanged.
- Returns:
merged_tri
- Return type:
int
array
- class nutils.util.tri_interpolator(tri, x, mergetol=0)¶
Bases:
object
Interpolate function values defined in triangulation vertices.
Convenience object that implements 2D interpolation on top of matplotlib’s triangulation routines. Unlike matplotlib’s own
LinearTriInterpolator
, thetri_interpolator
allows for interpolation of multi-dimensional arrays, as well as repeated interpolations of different vertex values.The arguments are identical to
tri_merge()
.After instantiation of the interpolator object, interpolation coordinates are specified via the object’s getitem operator. The resulting callable performs the interpolation:
>>> trix = [0,0], [1,0], [0,1], [1,1] # vertex coordinates >>> triu = 0, 0, 10, 0 # vertex values >>> interpolate = tri_interpolator([[0,1,2],[1,3,2]], trix) >>> x = [.1,.1], [.1,.9], [.9,.9] # interpolation coordinates >>> u = interpolate[x](triu) # interpolated values
Requires matplotlib.
- __weakref__¶
list of weak references to the object (if defined)
- nutils.util.obj2str(obj)¶
compact, lossy string representation of arbitrary object
- class nutils.util.single_or_multiple(f)¶
Bases:
object
Method wrapper, converts first positional argument to tuple: tuples/lists are passed on as tuples, other objects are turned into tuple singleton. Return values should match the length of the argument list, and are unpacked if the original argument was not a tuple/list.
>>> class Test: ... @single_or_multiple ... def square(self, args): ... return [v**2 for v in args] ... >>> T = Test() >>> T.square(2) 4 >>> T.square([2,3]) (4, 9)
- Parameters:
f (
callable
) – Method that expects a tuple as first positional argument, and that returns a list/tuple of the same length.- Returns:
Wrapped method.
- __weakref__¶
list of weak references to the object (if defined)
- class nutils.util.positional_only(f)¶
Bases:
object
Change all positional-or-keyword arguments to positional-only.
Python introduces syntax to define positional-only parameters in version 3.8, but the same effect can be achieved in older versions by using a wrapper with a var-positional argument. The
positional_only()
decorator uses this technique to treat all positional-or-keyword arguments as positional-only. In order to avoid name clashes between the positional-only arguments and variable keyword arguments, the wrapper additionally introduces the convention that the last argument receives the variable keyword argument dictionary in case is has a default value of … (ellipsis).Example:
>>> @positional_only ... def f(x, *, y): ... pass >>> inspect.signature(f) <Signature (x, /, *, y)>
>>> @positional_only ... def f(x, *args, y, kwargs=...): ... pass >>> inspect.signature(f) <Signature (x, /, *args, y, **kwargs)>
- Parameters:
f (
callable
) – Function to be wrapped.
- __weakref__¶
list of weak references to the object (if defined)
- nutils.util.loadlib(**libname)¶
Find and load a dynamic library using
ctypes.CDLL
. For each (supported) platform the name of the library should be specified as a keyword argument, including the extension, where the keywords should match the possible values ofsys.platform
.Example
To load the Intel MKL runtime library, write:
loadlib(linux='libmkl_rt.so', darwin='libmkl_rt.dylib', win32='mkl_rt.dll')
- nutils.util.readtext(path)¶
Read file and return contents
- Parameters:
path (
os.PathLike
,str
orio.TextIOBase
) – Path-like or file-like object pointing to the data to be read.- Returns:
File data as
str
.
- nutils.util.binaryfile(path)¶
Open file for binary reading
- Parameters:
path (
os.PathLike
,str
orio.BufferedIOBase
) – Path-like or file-like object pointing to the data to be read.- Returns:
Context that returns a
io.BufferedReader
upon entry.
- class nutils.util.settable(value=None)¶
Bases:
object
Context-switchable data container.
A mutable container for a general Python object, which can be changed by entering the
sets
context. The current value can be accessed via thevalue
attribute.>>> myprop = settable(2) >>> myprop.value 2 >>> with myprop.sets(3): ... myprop.value 3 >>> myprop.value 2
- nutils.util.index(sequence, item)¶
Index of first occurrence.
Generalization of tuple.index.
- nutils.util.unique(items, key=None)¶
Deduplicate items in sequence.
Return a tuple (unique, indices) such that items[i] == unique[indices[i]] and unique does not contain duplicate items. An optional key is applied to all items before testing for equality.