[yt-svn] commit/yt: 2 new changesets
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Tue Dec 13 10:37:05 PST 2011
2 new commits in yt:
https://bitbucket.org/yt_analysis/yt/changeset/295fd38d485f/
changeset: 295fd38d485f
branch: yt
user: chummels
date: 2011-12-11 23:13:26
summary: Added quartiles function to math_utils. Quartiles is very similar to numpy.median (which returns the median value from an array), except quartiles returns a 2-element array with the 25% quartile and 75% quartile values for the number distribution.
affected #: 1 file
diff -r 3ec2c245c82714557c87d8bd6fe4d06fbcb83b3c -r 295fd38d485f8357753c3f8ed7e3864368f54d6a yt/utilities/math_utils.py
--- a/yt/utilities/math_utils.py
+++ b/yt/utilities/math_utils.py
@@ -515,3 +515,107 @@
vec2 /= norm2
vec3 = na.cross(vec1, vec2)
return vec1, vec2, vec3
+
+def quartiles(a, axis=None, out=None, overwrite_input=False):
+ """
+ Compute the quartile values (25% and 75%) along the specified axis
+ in the same way that the numpy.median calculates the median (50%) value
+ alone a specified axis. Check numpy.median for details, as it is
+ virtually the same algorithm.
+
+ Returns an array of the quartiles of the array elements [lower quartile,
+ upper quartile].
+
+ Parameters
+ ----------
+ a : array_like
+ Input array or object that can be converted to an array.
+ axis : {None, int}, optional
+ Axis along which the quartiles are computed. The default (axis=None)
+ is to compute the quartiles along a flattened version of the array.
+ out : ndarray, optional
+ Alternative output array in which to place the result. It must
+ have the same shape and buffer length as the expected output,
+ but the type (of the output) will be cast if necessary.
+ overwrite_input : {False, True}, optional
+ If True, then allow use of memory of input array (a) for
+ calculations. The input array will be modified by the call to
+ quartiles. This will save memory when you do not need to preserve
+ the contents of the input array. Treat the input as undefined,
+ but it will probably be fully or partially sorted. Default is
+ False. Note that, if `overwrite_input` is True and the input
+ is not already an ndarray, an error will be raised.
+
+ Returns
+ -------
+ quartiles : ndarray
+ A new 2D array holding the result (unless `out` is specified, in
+ which case that array is returned instead). If the input contains
+ integers, or floats of smaller precision than 64, then the output
+ data-type is float64. Otherwise, the output data-type is the same
+ as that of the input.
+
+ See Also
+ --------
+ numpy.median, numpy.mean, numpy.percentile
+
+ Notes
+ -----
+ Given a vector V of length N, the quartiles of V are the 25% and 75% values
+ of a sorted copy of V, ``V_sorted`` - i.e., ``V_sorted[(N-1)/4]`` and
+ ``3*V_sorted[(N-1)/4]``, when N is odd. When N is even, it is the average
+ of the two values bounding these values of ``V_sorted``.
+
+ Examples
+ --------
+ >>> a = na.arange(100).reshape(10,10)
+ >>> a
+ array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
+ [10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
+ [20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
+ [30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
+ [40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
+ [50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
+ [60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
+ [70, 71, 72, 73, 74, 75, 76, 77, 78, 79],
+ [80, 81, 82, 83, 84, 85, 86, 87, 88, 89],
+ [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])
+ >>> mu.quartiles(a)
+ array([ 24.5, 74.5])
+ >>> mu.quartiles(a,axis=0)
+ array([[ 15., 16., 17., 18., 19., 20., 21., 22., 23., 24.],
+ [ 65., 66., 67., 68., 69., 70., 71., 72., 73., 74.]])
+ >>> mu.quartiles(a,axis=1)
+ array([[ 1.5, 11.5, 21.5, 31.5, 41.5, 51.5, 61.5, 71.5, 81.5,
+ 91.5],
+ [ 6.5, 16.5, 26.5, 36.5, 46.5, 56.5, 66.5, 76.5, 86.5,
+ 96.5]])
+ """
+ if overwrite_input:
+ if axis is None:
+ sorted = a.ravel()
+ sorted.sort()
+ else:
+ a.sort(axis=axis)
+ sorted = a
+ else:
+ sorted = na.sort(a, axis=axis)
+ if axis is None:
+ axis = 0
+ indexer = [slice(None)] * sorted.ndim
+ indices = [int(sorted.shape[axis]/4), int(sorted.shape[axis]*.75)]
+ result = []
+ for index in indices:
+ if sorted.shape[axis] % 2 == 1:
+ # index with slice to allow mean (below) to work
+ indexer[axis] = slice(index, index+1)
+ else:
+ indexer[axis] = slice(index-1, index+1)
+ # special cases for small arrays
+ if sorted.shape[axis] == 2:
+ # index with slice to allow mean (below) to work
+ indexer[axis] = slice(index, index+1)
+ # Use mean in odd and even case to coerce data type
+ # and check, use out array.
+ result.append(na.mean(sorted[indexer], axis=axis, out=out))
+ return na.array(result)
https://bitbucket.org/yt_analysis/yt/changeset/4e4544676353/
changeset: 4e4544676353
branch: yt
user: chummels
date: 2011-12-11 23:19:58
summary: Adding ortho_find and quartiles to yt.mods api.
affected #: 1 file
diff -r 295fd38d485f8357753c3f8ed7e3864368f54d6a -r 4e4544676353d5163c5ef8314aeaf223a920b00e yt/mods.py
--- a/yt/mods.py
+++ b/yt/mods.py
@@ -122,6 +122,10 @@
from yt.convenience import all_pfs, max_spheres, load, projload
+# Import some helpful math utilities
+from yt.utilities.math_utils import \
+ ortho_find, quartiles
+
# We load plugins. Keep in mind, this can be fairly dangerous -
# the primary purpose is to allow people to have a set of functions
Repository URL: https://bitbucket.org/yt_analysis/yt/
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