Lines Matching refs:dimension
184 ## all handle lists of 'dimension's and keepdims
646 array (i.e., N-1). Dimension can equal None (ravel array first), an
647 integer (the dimension over which to operate), or a sequence (operate
2029 def ageometricmean(inarray, dimension=None, keepdims=0):
2033 the passed array. Use dimension=None to flatten array first. REMEMBER: if
2034 dimensiondimension 0 ('rows' in a 2D array) only, and
2035 if dimension is a sequence, it collapses over all specified dimensions. If
2039 Usage: ageometricmean(inarray,dimension=None,keepdims=0)
2040 Returns: geometric mean computed over dim(s) listed in dimension
2043 if dimension == None:
2048 elif type(dimension) in [IntType, FloatType]:
2049 size = inarray.shape[dimension]
2051 mult = N.multiply.reduce(mult, dimension)
2054 shp[dimension] = 1
2057 dims = list(dimension)
2071 def aharmonicmean(inarray, dimension=None, keepdims=0):
2075 the passed array. Use dimension=None to flatten array first. REMEMBER: if
2076 dimension=0, it collapses over dimension 0 ('rows' in a 2D array) only, and
2077 if dimension is a sequence, it collapses over all specified dimensions. If
2081 Usage: aharmonicmean(inarray,dimension=None,keepdims=0)
2082 Returns: harmonic mean computed over dim(s) in dimension
2085 if dimension == None:
2089 elif type(dimension) in [IntType, FloatType]:
2090 size = float(inarray.shape[dimension])
2091 s = N.add.reduce(1.0 / inarray, dimension)
2094 shp[dimension] = 1
2097 dims = list(dimension)
2124 def amean(inarray, dimension=None, keepdims=0):
2128 passed array. Use dimension=None to flatten array first. REMEMBER: if
2129 dimension=0, it collapses over dimension 0 ('rows' in a 2D array) only, and
2130 if dimension is a sequence, it collapses over all specified dimensions. If
2134 Usage: amean(inarray,dimension=None,keepdims=0)
2135 Returns: arithematic mean calculated over dim(s) in dimension
2139 if dimension == None:
2143 elif type(dimension) in [IntType, FloatType]:
2144 sum = asum(inarray, dimension)
2145 denom = float(inarray.shape[dimension])
2148 shp[dimension] = 1
2151 dims = list(dimension)
2190 def amedianscore(inarray, dimension=None):
2194 with 1D arrays, or on the FIRST dimension of 2D arrays (i.e., dimension can
2195 be None, to pre-flatten the array, or else dimension must equal 0).
2197 Usage: amedianscore(inarray,dimension=None)
2200 if dimension == None:
2202 dimension = 0
2203 inarray = N.sort(inarray, dimension)
2204 if inarray.shape[dimension] % 2 == 0: # if even number of elements
2205 indx = inarray.shape[dimension] / 2 # integer division correct
2208 indx = inarray.shape[dimension] / 2 # integer division correct
2209 median = N.take(inarray, [indx], dimension)
2214 def amode(a, dimension=None):
2219 array (dimension=None), or on a given dimension.
2221 Usage: amode(a, dimension=None)
2225 if dimension == None:
2227 dimension = 0
2230 testshape[dimension] = 1
2235 counts = asum(template, dimension, 1)
2315 def atmin(a, lowerlimit=None, dimension=None, inclusive=1):
2317 Returns the minimum value of a, along dimension, including only values less
2321 Usage: atmin(a,lowerlimit=None,dimension=None,inclusive=1)
2327 if dimension == None:
2329 dimension = 0
2334 return N.minimum.reduce(ta, dimension)
2336 def atmax(a, upperlimit, dimension=None, inclusive=1):
2338 Returns the maximum value of a, along dimension, including only values greater
2342 Usage: atmax(a,upperlimit,dimension=None,inclusive=1)
2348 if dimension == None:
2350 dimension = 0
2355 return N.maximum.reduce(ta, dimension)
2411 def amoment(a, moment=1, dimension=None):
2415 kurtosis. Dimension can equal None (ravel array first), an integer
2416 (the dimension over which to operate), or a sequence (operate over
2419 Usage: amoment(a,moment=1,dimension=None)
2420 Returns: appropriate moment along given dimension
2422 if dimension == None:
2424 dimension = 0
2428 mn = amean(a, dimension, 1) # 1=keepdims
2430 return amean(s, dimension)
2432 def avariation(a, dimension=None):
2435 Probability and Statistics, p.6. Dimension can equal None (ravel array
2436 first), an integer (the dimension over which to operate), or a
2439 Usage: avariation(a,dimension=None)
2441 return 100.0 * asamplestdev(a, dimension) / amean(a, dimension)
2443 def askew(a, dimension=None):
2447 Dimension can equal None (ravel array first), an integer (the
2448 dimension over which to operate), or a sequence (operate over multiple
2451 Usage: askew(a, dimension=None)
2452 Returns: skew of vals in a along dimension, returning ZERO where all vals equal
2454 denom = N.power(amoment(a, 2, dimension), 1.5)
2459 return N.where(zero, 0, amoment(a, 3, dimension) / denom)
2461 def akurtosis(a, dimension=None):
2465 to see if it's close enough. Dimension can equal None (ravel array
2466 first), an integer (the dimension over which to operate), or a
2469 Usage: akurtosis(a,dimension=None)
2470 Returns: kurtosis of values in a along dimension, and ZERO where all vals equal
2472 denom = N.power(amoment(a, 2, dimension), 2)
2477 return N.where(zero, 0, amoment(a, 4, dimension) / denom)
2479 def adescribe(inarray, dimension=None):
2481 Returns several descriptive statistics of the passed array. Dimension
2482 can equal None (ravel array first), an integer (the dimension over
2485 Usage: adescribe(inarray,dimension=None)
2488 if dimension == None:
2490 dimension = 0
2491 n = inarray.shape[dimension]
2493 m = amean(inarray, dimension)
2494 sd = astdev(inarray, dimension)
2495 skew = askew(inarray, dimension)
2496 kurt = akurtosis(inarray, dimension)
2503 def askewtest(a, dimension=None):
2506 distribution. Dimension can equal None (ravel array first), an
2507 integer (the dimension over which to operate), or a sequence (operate
2510 Usage: askewtest(a,dimension=None)
2513 if dimension == None:
2515 dimension = 0
2516 b2 = askew(a, dimension)
2517 n = float(a.shape[dimension])
2528 def akurtosistest(a, dimension=None):
2531 kurtosis=3(n-1)/(n+1)) Valid only for n>20. Dimension can equal None
2532 (ravel array first), an integer (the dimension over which to operate),
2535 Usage: akurtosistest(a,dimension=None)
2538 if dimension == None:
2540 dimension = 0
2541 n = float(a.shape[dimension])
2544 b2 = akurtosis(a, dimension)
2563 def anormaltest(a, dimension=None):
2566 curve. Can operate over multiple dimensions. Dimension can equal
2567 None (ravel array first), an integer (the dimension over which to
2570 Usage: anormaltest(a,dimension=None)
2573 if dimension == None:
2575 dimension = 0
2576 s, p = askewtest(a, dimension)
2577 k, p = akurtosistest(a, dimension)
2737 def asamplevar(inarray, dimension=None, keepdims=0):
2740 array (i.e., using N). Dimension can equal None (ravel array first),
2741 an integer (the dimension over which to operate), or a sequence
2745 Usage: asamplevar(inarray,dimension=None,keepdims=0)
2747 if dimension == None:
2749 dimension = 0
2750 if dimension == 1:
2751 mn = amean(inarray, dimension)[:, N.NewAxis]
2753 mn = amean(inarray, dimension, keepdims=1)
2755 if type(dimension) == ListType:
2757 for d in dimension:
2760 n = inarray.shape[dimension]
2761 svar = ass(deviations, dimension, keepdims) / float(n)
2764 def asamplestdev(inarray, dimension=None, keepdims=0):
2767 array (i.e., using N). Dimension can equal None (ravel array first),
2768 an integer (the dimension over which to operate), or a sequence
2772 Usage: asamplestdev(inarray,dimension=None,keepdims=0)
2774 return N.sqrt(asamplevar(inarray, dimension, keepdims))
2776 def asignaltonoise(instack, dimension=0):
2778 Calculates signal-to-noise. Dimension can equal None (ravel array
2779 first), an integer (the dimension over which to operate), or a
2782 Usage: asignaltonoise(instack,dimension=0):
2783 Returns: array containing the value of (mean/stdev) along dimension,
2786 m = mean(instack, dimension)
2787 sd = stdev(instack, dimension)
2790 def acov(x, y, dimension=None, keepdims=0):
2793 array (i.e., N-1). Dimension can equal None (ravel array first), an
2794 integer (the dimension over which to operate), or a sequence (operate
2798 Usage: acov(x,y,dimension=None,keepdims=0)
2800 if dimension == None:
2803 dimension = 0
2804 xmn = amean(x, dimension, 1) # keepdims
2806 ymn = amean(y, dimension, 1) # keepdims
2808 if type(dimension) == ListType:
2810 for d in dimension:
2813 n = x.shape[dimension]
2817 def avar(inarray, dimension=None, keepdims=0):
2820 array (i.e., N-1). Dimension can equal None (ravel array first), an
2821 integer (the dimension over which to operate), or a sequence (operate
2825 Usage: avar(inarray,dimension=None,keepdims=0)
2827 if dimension == None:
2829 dimension = 0
2830 mn = amean(inarray, dimension, 1)
2832 if type(dimension) == ListType:
2834 for d in dimension:
2837 n = inarray.shape[dimension]
2838 var = ass(deviations, dimension, keepdims) / float(n - 1)
2841 def astdev(inarray, dimension=None, keepdims=0):
2844 the passed array (i.e., N-1). Dimension can equal None (ravel array
2845 first), an integer (the dimension over which to operate), or a
2849 Usage: astdev(inarray,dimension=None,keepdims=0)
2851 return N.sqrt(avar(inarray, dimension, keepdims))
2853 def asterr(inarray, dimension=None, keepdims=0):
2856 passed array (i.e., N-1). Dimension can equal None (ravel array
2857 first), an integer (the dimension over which to operate), or a
2861 Usage: asterr(inarray,dimension=None,keepdims=0)
2863 if dimension == None:
2865 dimension = 0
2866 return astdev(inarray, dimension,
2867 keepdims) / float(N.sqrt(inarray.shape[dimension]))
2869 def asem(inarray, dimension=None, keepdims=0):
2872 in the passed array. Dimension can equal None (ravel array first), an
2873 integer (the dimension over which to operate), or a sequence (operate
2877 Usage: asem(inarray,dimension=None, keepdims=0)
2879 if dimension == None:
2881 dimension = 0
2882 if type(dimension) == ListType:
2884 for d in dimension:
2887 n = inarray.shape[dimension]
2888 s = asamplestdev(inarray, dimension, keepdims) / N.sqrt(n - 1)
2914 def azmap(scores, compare, dimension=0):
2920 Usage: azs(scores, compare, dimension=0)
2922 mns = amean(compare, dimension)
3359 dimension=None,
3368 to 'filename' using the given writemode (default=append). Dimension
3369 can equal None (ravel array first), or an integer (the dimension over
3372 Usage: attest_ind (a,b,dimension=None,printit=0,
3376 if dimension == None:
3379 dimension = 0
3380 x1 = amean(a, dimension)
3381 x2 = amean(b, dimension)
3382 v1 = avar(a, dimension)
3383 v2 = avar(b, dimension)
3384 n1 = a.shape[dimension]
3385 n2 = b.shape[dimension]
3445 dimension=None,
3454 to 'filename' using the given writemode (default=append). Dimension
3455 can equal None (ravel array first), or an integer (the dimension over
3458 Usage: attest_rel(a,b,dimension=None,printit=0,
3462 if dimension == None:
3465 dimension = 0
3468 x1 = amean(a, dimension)
3469 x2 = amean(b, dimension)
3470 v1 = avar(a, dimension)
3471 v2 = avar(b, dimension)
3472 n = a.shape[dimension]
3477 (n * N.add.reduce(d * d, dimension) - N.add.reduce(d, dimension)**2) /
3482 t = N.add.reduce(d, dimension) / denom # N-D COMPUTATION HERE!!!!!!
4167 def asum(a, dimension=None, keepdims=0):
4172 Dimension can equal None (ravel array first), an integer (the
4173 dimension over which to operate), or a sequence (operate over multiple
4177 Usage: asum(a, dimension=None, keepdims=0)
4178 Returns: array summed along 'dimension'(s), same _number_ of dims if keepdims=1
4182 if dimension == None:
4184 elif type(dimension) in [IntType, FloatType]:
4185 s = N.add.reduce(a, dimension)
4188 shp[dimension] = 1
4191 dims = list(dimension)
4204 def acumsum(a, dimension=None):
4207 passed array. Dimension can equal None (ravel array first), an
4208 integer (the dimension over which to operate), or a sequence (operate
4211 Usage: acumsum(a,dimension=None)
4213 if dimension == None:
4215 dimension = 0
4216 if type(dimension) in [ListType, TupleType, N.ndarray]:
4217 dimension = list(dimension)
4218 dimension.sort()
4219 dimension.reverse()
4220 for d in dimension:
4224 return N.add.accumulate(a, dimension)
4226 def ass(inarray, dimension=None, keepdims=0):
4230 the array. Dimension can equal None (ravel array first), an integer
4231 (the dimension over which to operate), or a sequence (operate over
4235 Usage: ass(inarray, dimension=None, keepdims=0)
4236 Returns: sum-along-'dimension' for (inarray*inarray)
4238 if dimension == None:
4240 dimension = 0
4241 return asum(inarray * inarray, dimension, keepdims)
4243 def asummult(array1, array2, dimension=None, keepdims=0):
4246 returns the sum (along 'dimension') of all resulting multiplications.
4247 Dimension can equal None (ravel array first), an integer (the
4248 dimension over which to operate), or a sequence (operate over multiple
4251 Usage: asummult(array1,array2,dimension=None,keepdims=0)
4253 if dimension == None:
4256 dimension = 0
4257 return asum(array1 * array2, dimension, keepdims)
4259 def asquare_of_sums(inarray, dimension=None, keepdims=0):
4262 result. Dimension can equal None (ravel array first), an integer (the
4263 dimension over which to operate), or a sequence (operate over multiple
4267 Usage: asquare_of_sums(inarray, dimension=None, keepdims=0)
4268 Returns: the square of the sum over dim(s) in dimension
4270 if dimension == None:
4272 dimension = 0
4273 s = asum(inarray, dimension, keepdims)
4279 def asumdiffsquared(a, b, dimension=None, keepdims=0):
4282 these differences, and returns the sum of these squares. Dimension
4283 can equal None (ravel array first), an integer (the dimension over
4290 if dimension == None:
4292 dimension = 0
4293 return asum((a - b)**2, dimension, keepdims)
