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| author | Charles Harris <charlesr.harris@gmail.com> | 2013-08-18 16:19:20 -0700 |
|---|---|---|
| committer | Charles Harris <charlesr.harris@gmail.com> | 2013-08-18 16:19:20 -0700 |
| commit | 6c729b4423857850e6553cf6c2d0fc8b026036dd (patch) | |
| tree | 330ce703eb02d20f96099c3fe0fc36ae33d4905b /numpy/lib | |
| parent | 13b0b272f764c14bc4ac34f5b19fd030d9c611a4 (diff) | |
| parent | fbd6510d58a47ea0d166c48a82793f05425406e4 (diff) | |
| download | numpy-6c729b4423857850e6553cf6c2d0fc8b026036dd.tar.gz | |
Merge pull request #3635 from charris/giant-style-cleanup
Giant style cleanup
Diffstat (limited to 'numpy/lib')
31 files changed, 878 insertions, 879 deletions
diff --git a/numpy/lib/__init__.py b/numpy/lib/__init__.py index 64a8550c6..73e4b2306 100644 --- a/numpy/lib/__init__.py +++ b/numpy/lib/__init__.py @@ -24,7 +24,7 @@ from .financial import * from .arrayterator import * from .arraypad import * -__all__ = ['emath','math'] +__all__ = ['emath', 'math'] __all__ += type_check.__all__ __all__ += index_tricks.__all__ __all__ += function_base.__all__ diff --git a/numpy/lib/financial.py b/numpy/lib/financial.py index 8cac117c9..ec642afd3 100644 --- a/numpy/lib/financial.py +++ b/numpy/lib/financial.py @@ -688,7 +688,7 @@ def npv(rate, values): """ values = np.asarray(values) - return (values / (1+rate)**np.arange(0,len(values))).sum(axis=0) + return (values / (1+rate)**np.arange(0, len(values))).sum(axis=0) def mirr(values, finance_rate, reinvest_rate): """ diff --git a/numpy/lib/format.py b/numpy/lib/format.py index fd459e84e..fd5496e96 100644 --- a/numpy/lib/format.py +++ b/numpy/lib/format.py @@ -352,7 +352,7 @@ def read_array_header_1_0(fp): # Sanity-check the values. if (not isinstance(d['shape'], tuple) or - not numpy.all([isinstance(x, (int,long)) for x in d['shape']])): + not numpy.all([isinstance(x, (int, long)) for x in d['shape']])): msg = "shape is not valid: %r" raise ValueError(msg % (d['shape'],)) if not isinstance(d['fortran_order'], bool): @@ -366,7 +366,7 @@ def read_array_header_1_0(fp): return d['shape'], d['fortran_order'], dtype -def write_array(fp, array, version=(1,0)): +def write_array(fp, array, version=(1, 0)): """ Write an array to an NPY file, including a header. @@ -485,7 +485,7 @@ def read_array(fp): def open_memmap(filename, mode='r+', dtype=None, shape=None, - fortran_order=False, version=(1,0)): + fortran_order=False, version=(1, 0)): """ Open a .npy file as a memory-mapped array. diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 4285bf793..91eace2ff 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -351,7 +351,7 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): # Compute the bin number each sample falls into. Ncount = {} for i in arange(D): - Ncount[i] = digitize(sample[:,i], edges[i]) + Ncount[i] = digitize(sample[:, i], edges[i]) # Using digitize, values that fall on an edge are put in the right bin. # For the rightmost bin, we want values equal to the right @@ -362,7 +362,7 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): if not np.isinf(mindiff): decimal = int(-log10(mindiff)) + 6 # Find which points are on the rightmost edge. - on_edge = where(around(sample[:,i], decimal) == around(edges[i][-1], + on_edge = where(around(sample[:, i], decimal) == around(edges[i][-1], decimal))[0] # Shift these points one bin to the left. Ncount[i][on_edge] -= 1 @@ -392,11 +392,11 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): hist = hist.reshape(sort(nbin)) for i in arange(nbin.size): j = ni.argsort()[i] - hist = hist.swapaxes(i,j) - ni[i],ni[j] = ni[j],ni[i] + hist = hist.swapaxes(i, j) + ni[i], ni[j] = ni[j], ni[i] # Remove outliers (indices 0 and -1 for each dimension). - core = D*[slice(1,-1)] + core = D*[slice(1, -1)] hist = hist[core] # Normalize if normed is True @@ -1196,7 +1196,7 @@ def sort_complex(a): array([ 1.+2.j, 2.-1.j, 3.-3.j, 3.-2.j, 3.+5.j]) """ - b = array(a,copy=True) + b = array(a, copy=True) b.sort() if not issubclass(b.dtype.type, _nx.complexfloating): if b.dtype.char in 'bhBH': @@ -1269,7 +1269,7 @@ def unique(x): if tmp.size == 0: return tmp tmp.sort() - idx = concatenate(([True],tmp[1:]!=tmp[:-1])) + idx = concatenate(([True], tmp[1:]!=tmp[:-1])) return tmp[idx] except AttributeError: items = sorted(set(x)) @@ -1736,7 +1736,7 @@ def cov(m, y=None, rowvar=1, bias=0, ddof=None): rowvar = 1 if rowvar: axis = 0 - tup = (slice(None),newaxis) + tup = (slice(None), newaxis) else: axis = 1 tup = (newaxis, slice(None)) @@ -1744,7 +1744,7 @@ def cov(m, y=None, rowvar=1, bias=0, ddof=None): if y is not None: y = array(y, copy=False, ndmin=2, dtype=float) - X = concatenate((X,y), axis) + X = concatenate((X, y), axis) X -= X.mean(axis=1-axis)[tup] if rowvar: @@ -1820,7 +1820,7 @@ def corrcoef(x, y=None, rowvar=1, bias=0, ddof=None): d = diag(c) except ValueError: # scalar covariance return 1 - return c/sqrt(multiply.outer(d,d)) + return c/sqrt(multiply.outer(d, d)) def blackman(M): """ @@ -1916,7 +1916,7 @@ def blackman(M): return array([]) if M == 1: return ones(1, float) - n = arange(0,M) + n = arange(0, M) return 0.42-0.5*cos(2.0*pi*n/(M-1)) + 0.08*cos(4.0*pi*n/(M-1)) def bartlett(M): @@ -2022,8 +2022,8 @@ def bartlett(M): return array([]) if M == 1: return ones(1, float) - n = arange(0,M) - return where(less_equal(n,(M-1)/2.0),2.0*n/(M-1),2.0-2.0*n/(M-1)) + n = arange(0, M) + return where(less_equal(n, (M-1)/2.0), 2.0*n/(M-1), 2.0-2.0*n/(M-1)) def hanning(M): """ @@ -2120,7 +2120,7 @@ def hanning(M): return array([]) if M == 1: return ones(1, float) - n = arange(0,M) + n = arange(0, M) return 0.5-0.5*cos(2.0*pi*n/(M-1)) def hamming(M): @@ -2216,8 +2216,8 @@ def hamming(M): if M < 1: return array([]) if M == 1: - return ones(1,float) - n = arange(0,M) + return ones(1, float) + n = arange(0, M) return 0.54-0.46*cos(2.0*pi*n/(M-1)) ## Code from cephes for i0 @@ -2285,7 +2285,7 @@ def _chbevl(x, vals): b0 = vals[0] b1 = 0.0 - for i in range(1,len(vals)): + for i in range(1, len(vals)): b2 = b1 b1 = b0 b0 = x*b1 - b2 + vals[i] @@ -2364,7 +2364,7 @@ def i0(x): ## End of cephes code for i0 -def kaiser(M,beta): +def kaiser(M, beta): """ Return the Kaiser window. @@ -2487,7 +2487,7 @@ def kaiser(M,beta): from numpy.dual import i0 if M == 1: return np.array([1.]) - n = arange(0,M) + n = arange(0, M) alpha = (M-1)/2.0 return i0(beta * sqrt(1-((n-alpha)/alpha)**2.0))/i0(float(beta)) @@ -2592,7 +2592,7 @@ def msort(a): ``np.msort(a)`` is equivalent to ``np.sort(a, axis=0)``. """ - b = array(a,subok=True,copy=True) + b = array(a, subok=True, copy=True) b.sort(0) return b @@ -2841,7 +2841,7 @@ def _compute_qth_percentile(sorted, q, axis, out): else: indexer[axis] = slice(i, i+2) j = i + 1 - weights = array([(j - index), (index - i)],float) + weights = array([(j - index), (index - i)], float) wshape = [1]*sorted.ndim wshape[axis] = 2 weights.shape = wshape @@ -2926,8 +2926,8 @@ def trapz(y, x=None, dx=1.0, axis=-1): nd = len(y.shape) slice1 = [slice(None)]*nd slice2 = [slice(None)]*nd - slice1[axis] = slice(1,None) - slice2[axis] = slice(None,-1) + slice1[axis] = slice(1, None) + slice2[axis] = slice(None, -1) try: ret = (d * (y[slice1] +y [slice2]) / 2.0).sum(axis) except ValueError: # Operations didn't work, cast to ndarray @@ -3212,7 +3212,7 @@ def delete(arr, obj, axis=None): if stop == N: pass else: - slobj[axis] = slice(stop-numtodel,None) + slobj[axis] = slice(stop-numtodel, None) slobj2 = [slice(None)]*ndim slobj2[axis] = slice(stop, None) new[slobj] = arr[slobj2] @@ -3253,9 +3253,9 @@ def delete(arr, obj, axis=None): new = empty(newshape, arr.dtype, arr.flags.fnc) slobj[axis] = slice(None, obj) new[slobj] = arr[slobj] - slobj[axis] = slice(obj,None) + slobj[axis] = slice(obj, None) slobj2 = [slice(None)]*ndim - slobj2[axis] = slice(obj+1,None) + slobj2[axis] = slice(obj+1, None) new[slobj] = arr[slobj2] else: if obj.size == 0 and not isinstance(_obj, np.ndarray): diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py index ca3d60869..570cd0f1d 100644 --- a/numpy/lib/index_tricks.py +++ b/numpy/lib/index_tricks.py @@ -6,8 +6,8 @@ __all__ = ['ravel_multi_index', 'ogrid', 'r_', 'c_', 's_', 'index_exp', 'ix_', - 'ndenumerate','ndindex', - 'fill_diagonal','diag_indices','diag_indices_from'] + 'ndenumerate', 'ndindex', + 'fill_diagonal', 'diag_indices', 'diag_indices_from'] import sys import numpy.core.numeric as _nx @@ -144,7 +144,7 @@ class nd_grid(object): """ def __init__(self, sparse=False): self.sparse = sparse - def __getitem__(self,key): + def __getitem__(self, key): try: size = [] typ = int @@ -180,7 +180,7 @@ class nd_grid(object): if self.sparse: slobj = [_nx.newaxis]*len(size) for k in range(len(size)): - slobj[k] = slice(None,None) + slobj[k] = slice(None, None) nn[k] = nn[k][slobj] slobj[k] = _nx.newaxis return nn @@ -195,12 +195,12 @@ class nd_grid(object): if step != 1: step = (key.stop-start)/float(step-1) stop = key.stop+step - return _nx.arange(0, length,1, float)*step + start + return _nx.arange(0, length, 1, float)*step + start else: return _nx.arange(start, stop, step) - def __getslice__(self,i,j): - return _nx.arange(i,j) + def __getslice__(self, i, j): + return _nx.arange(i, j) def __len__(self): return 0 @@ -237,12 +237,12 @@ class AxisConcatenator(object): self.trans1d = trans1d self.ndmin = ndmin - def __getitem__(self,key): + def __getitem__(self, key): trans1d = self.trans1d ndmin = self.ndmin if isinstance(key, str): frame = sys._getframe().f_back - mymat = matrix.bmat(key,frame.f_globals,frame.f_locals) + mymat = matrix.bmat(key, frame.f_globals, frame.f_locals) return mymat if not isinstance(key, tuple): key = (key,) @@ -265,10 +265,10 @@ class AxisConcatenator(object): else: newobj = _nx.arange(start, stop, step) if ndmin > 1: - newobj = array(newobj,copy=False,ndmin=ndmin) + newobj = array(newobj, copy=False, ndmin=ndmin) if trans1d != -1: - newobj = newobj.swapaxes(-1,trans1d) - elif isinstance(key[k],str): + newobj = newobj.swapaxes(-1, trans1d) + elif isinstance(key[k], str): if k != 0: raise ValueError("special directives must be the " "first entry.") @@ -293,7 +293,7 @@ class AxisConcatenator(object): except (ValueError, TypeError): raise ValueError("unknown special directive") elif type(key[k]) in ScalarType: - newobj = array(key[k],ndmin=ndmin) + newobj = array(key[k], ndmin=ndmin) scalars.append(k) scalar = True scalartypes.append(newobj.dtype) @@ -323,11 +323,11 @@ class AxisConcatenator(object): for k in scalars: objs[k] = objs[k].astype(final_dtype) - res = _nx.concatenate(tuple(objs),axis=self.axis) + res = _nx.concatenate(tuple(objs), axis=self.axis) return self._retval(res) - def __getslice__(self,i,j): - res = _nx.arange(i,j) + def __getslice__(self, i, j): + res = _nx.arange(i, j) return self._retval(res) def __len__(self): @@ -657,7 +657,7 @@ def fill_diagonal(a, val, wrap=False): Value to be written on the diagonal, its type must be compatible with that of the array a. - wrap : bool + wrap : bool For tall matrices in NumPy version up to 1.6.2, the diagonal "wrapped" after N columns. You can have this behavior with this option. This affect only tall matrices. diff --git a/numpy/lib/info.py b/numpy/lib/info.py index 94eeae503..3fbbab769 100644 --- a/numpy/lib/info.py +++ b/numpy/lib/info.py @@ -147,5 +147,5 @@ setdiff1d Set difference of 1D arrays with unique elements. """ from __future__ import division, absolute_import, print_function -depends = ['core','testing'] +depends = ['core', 'testing'] global_symbols = ['*'] diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 5402adc6d..48a012c9c 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -141,7 +141,7 @@ def poly(seq_of_zeros): roots = NX.asarray(seq_of_zeros, complex) pos_roots = sort_complex(NX.compress(roots.imag > 0, roots)) neg_roots = NX.conjugate(sort_complex( - NX.compress(roots.imag < 0,roots))) + NX.compress(roots.imag < 0, roots))) if (len(pos_roots) == len(neg_roots) and NX.alltrue(neg_roots == pos_roots)): a = a.real.copy() @@ -223,7 +223,7 @@ def roots(p): if N > 1: # build companion matrix and find its eigenvalues (the roots) A = diag(NX.ones((N-2,), p.dtype), -1) - A[0, :] = -p[1:] / p[0] + A[0,:] = -p[1:] / p[0] roots = eigvals(A) else: roots = NX.array([]) @@ -589,7 +589,7 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): if full : return c, resids, rank, s, rcond elif cov : - Vbase = inv(dot(lhs.T,lhs)) + Vbase = inv(dot(lhs.T, lhs)) Vbase /= NX.outer(scale, scale) # Some literature ignores the extra -2.0 factor in the denominator, but # it is included here because the covariance of Multivariate Student-T @@ -599,7 +599,7 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): if y.ndim == 1: return c, Vbase * fac else: - return c, Vbase[:,:,NX.newaxis] * fac + return c, Vbase[:,:, NX.newaxis] * fac else : return c @@ -828,7 +828,7 @@ def polymul(a1, a2): """ truepoly = (isinstance(a1, poly1d) or isinstance(a2, poly1d)) - a1,a2 = poly1d(a1),poly1d(a2) + a1, a2 = poly1d(a1), poly1d(a2) val = NX.convolve(a1, a2) if truepoly: val = poly1d(val) @@ -1200,7 +1200,7 @@ class poly1d(object): def __getattr__(self, key): if key in ['r', 'roots']: return roots(self.coeffs) - elif key in ['c','coef','coefficients']: + elif key in ['c', 'coef', 'coefficients']: return self.coeffs elif key in ['o']: return self.order @@ -1261,4 +1261,4 @@ class poly1d(object): # Stuff to do on module import -warnings.simplefilter('always',RankWarning) +warnings.simplefilter('always', RankWarning) diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py index 827e60d70..ae4ee56c6 100644 --- a/numpy/lib/recfunctions.py +++ b/numpy/lib/recfunctions.py @@ -900,7 +900,7 @@ def join_by(key, r1, r2, jointype='inner', r1postfix='1', r2postfix='2', (r1names, r2names) = (r1.dtype.names, r2.dtype.names) # Check the names for collision - if (set.intersection(set(r1names),set(r2names)).difference(key) and + if (set.intersection(set(r1names), set(r2names)).difference(key) and not (r1postfix or r2postfix)): msg = "r1 and r2 contain common names, r1postfix and r2postfix " msg += "can't be empty" diff --git a/numpy/lib/scimath.py b/numpy/lib/scimath.py index 2aa08d0ea..3da86d9c8 100644 --- a/numpy/lib/scimath.py +++ b/numpy/lib/scimath.py @@ -17,7 +17,7 @@ correctly handled. See their respective docstrings for specific examples. """ from __future__ import division, absolute_import, print_function -__all__ = ['sqrt', 'log', 'log2', 'logn','log10', 'power', 'arccos', +__all__ = ['sqrt', 'log', 'log2', 'logn', 'log10', 'power', 'arccos', 'arcsin', 'arctanh'] import numpy.core.numeric as nx @@ -84,7 +84,7 @@ def _tocomplex(arr): array([ 1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64) """ if issubclass(arr.dtype.type, (nt.single, nt.byte, nt.short, nt.ubyte, - nt.ushort,nt.csingle)): + nt.ushort, nt.csingle)): return arr.astype(nt.csingle) else: return arr.astype(nt.cdouble) diff --git a/numpy/lib/setup.py b/numpy/lib/setup.py index edc653f9f..153af314c 100644 --- a/numpy/lib/setup.py +++ b/numpy/lib/setup.py @@ -5,13 +5,13 @@ from os.path import join def configuration(parent_package='',top_path=None): from numpy.distutils.misc_util import Configuration - config = Configuration('lib',parent_package,top_path) + config = Configuration('lib', parent_package, top_path) - config.add_include_dirs(join('..','core','include')) + config.add_include_dirs(join('..', 'core', 'include')) config.add_extension('_compiled_base', - sources=[join('src','_compiled_base.c')] + sources=[join('src', '_compiled_base.c')] ) config.add_data_dir('benchmarks') diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py index c63f8140d..1363a3213 100644 --- a/numpy/lib/shape_base.py +++ b/numpy/lib/shape_base.py @@ -1,7 +1,7 @@ from __future__ import division, absolute_import, print_function -__all__ = ['column_stack','row_stack', 'dstack','array_split','split','hsplit', - 'vsplit','dsplit','apply_over_axes','expand_dims', +__all__ = ['column_stack', 'row_stack', 'dstack', 'array_split', 'split', 'hsplit', + 'vsplit', 'dsplit', 'apply_over_axes', 'expand_dims', 'apply_along_axis', 'kron', 'tile', 'get_array_wrap'] import numpy.core.numeric as _nx @@ -68,18 +68,18 @@ def apply_along_axis(func1d,axis,arr,*args): axis += nd if (axis >= nd): raise ValueError("axis must be less than arr.ndim; axis=%d, rank=%d." - % (axis,nd)) + % (axis, nd)) ind = [0]*(nd-1) - i = zeros(nd,'O') + i = zeros(nd, 'O') indlist = list(range(nd)) indlist.remove(axis) - i[axis] = slice(None,None) + i[axis] = slice(None, None) outshape = asarray(arr.shape).take(indlist) i.put(indlist, ind) res = func1d(arr[tuple(i.tolist())],*args) # if res is a number, then we have a smaller output array if isscalar(res): - outarr = zeros(outshape,asarray(res).dtype) + outarr = zeros(outshape, asarray(res).dtype) outarr[tuple(ind)] = res Ntot = product(outshape) k = 1 @@ -91,7 +91,7 @@ def apply_along_axis(func1d,axis,arr,*args): ind[n-1] += 1 ind[n] = 0 n -= 1 - i.put(indlist,ind) + i.put(indlist, ind) res = func1d(arr[tuple(i.tolist())],*args) outarr[tuple(ind)] = res k += 1 @@ -101,7 +101,7 @@ def apply_along_axis(func1d,axis,arr,*args): holdshape = outshape outshape = list(arr.shape) outshape[axis] = len(res) - outarr = zeros(outshape,asarray(res).dtype) + outarr = zeros(outshape, asarray(res).dtype) outarr[tuple(i.tolist())] = res k = 1 while k < Ntot: @@ -182,7 +182,7 @@ def apply_over_axes(func, a, axes): if res.ndim == val.ndim: val = res else: - res = expand_dims(res,axis) + res = expand_dims(res, axis) if res.ndim == val.ndim: val = res else: @@ -288,11 +288,11 @@ def column_stack(tup): """ arrays = [] for v in tup: - arr = array(v,copy=False,subok=True) + arr = array(v, copy=False, subok=True) if arr.ndim < 2: - arr = array(arr,copy=False,subok=True,ndmin=2).T + arr = array(arr, copy=False, subok=True, ndmin=2).T arrays.append(arr) - return _nx.concatenate(arrays,1) + return _nx.concatenate(arrays, 1) def dstack(tup): """ @@ -348,7 +348,7 @@ def _replace_zero_by_x_arrays(sub_arys): for i in range(len(sub_arys)): if len(_nx.shape(sub_arys[i])) == 0: sub_arys[i] = _nx.array([]) - elif _nx.sometrue(_nx.equal(_nx.shape(sub_arys[i]),0)): + elif _nx.sometrue(_nx.equal(_nx.shape(sub_arys[i]), 0)): sub_arys[i] = _nx.array([]) return sub_arys @@ -383,17 +383,17 @@ def array_split(ary,indices_or_sections,axis = 0): Nsections = int(indices_or_sections) if Nsections <= 0: raise ValueError('number sections must be larger than 0.') - Neach_section,extras = divmod(Ntotal,Nsections) + Neach_section, extras = divmod(Ntotal, Nsections) section_sizes = [0] + \ extras * [Neach_section+1] + \ (Nsections-extras) * [Neach_section] div_points = _nx.array(section_sizes).cumsum() sub_arys = [] - sary = _nx.swapaxes(ary,axis,0) + sary = _nx.swapaxes(ary, axis, 0) for i in range(Nsections): st = div_points[i]; end = div_points[i+1] - sub_arys.append(_nx.swapaxes(sary[st:end],axis,0)) + sub_arys.append(_nx.swapaxes(sary[st:end], axis, 0)) # there is a weird issue with array slicing that allows # 0x10 arrays and other such things. The following kludge is needed @@ -474,10 +474,10 @@ def split(ary,indices_or_sections,axis=0): N = ary.shape[axis] if N % sections: raise ValueError('array split does not result in an equal division') - res = array_split(ary,indices_or_sections,axis) + res = array_split(ary, indices_or_sections, axis) return res -def hsplit(ary,indices_or_sections): +def hsplit(ary, indices_or_sections): """ Split an array into multiple sub-arrays horizontally (column-wise). @@ -535,11 +535,11 @@ def hsplit(ary,indices_or_sections): if len(_nx.shape(ary)) == 0: raise ValueError('hsplit only works on arrays of 1 or more dimensions') if len(ary.shape) > 1: - return split(ary,indices_or_sections,1) + return split(ary, indices_or_sections, 1) else: - return split(ary,indices_or_sections,0) + return split(ary, indices_or_sections, 0) -def vsplit(ary,indices_or_sections): +def vsplit(ary, indices_or_sections): """ Split an array into multiple sub-arrays vertically (row-wise). @@ -588,9 +588,9 @@ def vsplit(ary,indices_or_sections): """ if len(_nx.shape(ary)) < 2: raise ValueError('vsplit only works on arrays of 2 or more dimensions') - return split(ary,indices_or_sections,0) + return split(ary, indices_or_sections, 0) -def dsplit(ary,indices_or_sections): +def dsplit(ary, indices_or_sections): """ Split array into multiple sub-arrays along the 3rd axis (depth). @@ -633,7 +633,7 @@ def dsplit(ary,indices_or_sections): """ if len(_nx.shape(ary)) < 3: raise ValueError('vsplit only works on arrays of 3 or more dimensions') - return split(ary,indices_or_sections,2) + return split(ary, indices_or_sections, 2) def get_array_prepare(*args): """Find the wrapper for the array with the highest priority. @@ -659,7 +659,7 @@ def get_array_wrap(*args): return wrappers[-1][-1] return None -def kron(a,b): +def kron(a, b): """ Kronecker product of two arrays. @@ -728,10 +728,10 @@ def kron(a,b): """ b = asanyarray(b) - a = array(a,copy=False,subok=True,ndmin=b.ndim) + a = array(a, copy=False, subok=True, ndmin=b.ndim) ndb, nda = b.ndim, a.ndim if (nda == 0 or ndb == 0): - return _nx.multiply(a,b) + return _nx.multiply(a, b) as_ = a.shape bs = b.shape if not a.flags.contiguous: @@ -745,7 +745,7 @@ def kron(a,b): else: bs = (1,)*(nda-ndb) + bs nd = nda - result = outer(a,b).reshape(as_+bs) + result = outer(a, b).reshape(as_+bs) axis = nd-1 for _ in range(nd): result = concatenate(result, axis=axis) @@ -819,14 +819,14 @@ def tile(A, reps): except TypeError: tup = (reps,) d = len(tup) - c = _nx.array(A,copy=False,subok=True,ndmin=d) + c = _nx.array(A, copy=False, subok=True, ndmin=d) shape = list(c.shape) - n = max(c.size,1) + n = max(c.size, 1) if (d < c.ndim): tup = (1,)*(c.ndim-d) + tup for i, nrep in enumerate(tup): if nrep!=1: - c = c.reshape(-1,n).repeat(nrep,0) + c = c.reshape(-1, n).repeat(nrep, 0) dim_in = shape[i] dim_out = dim_in*nrep shape[i] = dim_out diff --git a/numpy/lib/stride_tricks.py b/numpy/lib/stride_tricks.py index 7b6b06fdc..d092f92a8 100644 --- a/numpy/lib/stride_tricks.py +++ b/numpy/lib/stride_tricks.py @@ -115,6 +115,6 @@ def broadcast_arrays(*args): common_shape.append(1) # Construct the new arrays. - broadcasted = [as_strided(x, shape=sh, strides=st) for (x,sh,st) in + broadcasted = [as_strided(x, shape=sh, strides=st) for (x, sh, st) in zip(args, shapes, strides)] return broadcasted diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py index 4ba6529e4..7e8a7a6f3 100644 --- a/numpy/lib/tests/test_arraysetops.py +++ b/numpy/lib/tests/test_arraysetops.py @@ -61,8 +61,8 @@ class TestSetOps(TestCase): # test for structured arrays dt = [('', 'i'), ('', 'i')] - aa = np.array(list(zip(a,a)), dt) - bb = np.array(list(zip(b,b)), dt) + aa = np.array(list(zip(a, a)), dt) + bb = np.array(list(zip(b, b)), dt) check_all(aa, bb, i1, i2, dt) @@ -83,7 +83,7 @@ class TestSetOps(TestCase): c = intersect1d( a, b ) assert_array_equal( c, ed ) - assert_array_equal([], intersect1d([],[])) + assert_array_equal([], intersect1d([], [])) def test_setxor1d( self ): a = np.array( [5, 7, 1, 2] ) @@ -107,19 +107,19 @@ class TestSetOps(TestCase): c = setxor1d( a, b ) assert_array_equal( c, ec ) - assert_array_equal([], setxor1d([],[])) + assert_array_equal([], setxor1d([], [])) def test_ediff1d(self): zero_elem = np.array([]) one_elem = np.array([1]) - two_elem = np.array([1,2]) + two_elem = np.array([1, 2]) - assert_array_equal([],ediff1d(zero_elem)) - assert_array_equal([0],ediff1d(zero_elem,to_begin=0)) - assert_array_equal([0],ediff1d(zero_elem,to_end=0)) - assert_array_equal([-1,0],ediff1d(zero_elem,to_begin=-1,to_end=0)) - assert_array_equal([],ediff1d(one_elem)) - assert_array_equal([1],ediff1d(two_elem)) + assert_array_equal([], ediff1d(zero_elem)) + assert_array_equal([0], ediff1d(zero_elem, to_begin=0)) + assert_array_equal([0], ediff1d(zero_elem, to_end=0)) + assert_array_equal([-1, 0], ediff1d(zero_elem, to_begin=-1, to_end=0)) + assert_array_equal([], ediff1d(one_elem)) + assert_array_equal([1], ediff1d(two_elem)) def test_in1d(self): # we use two different sizes for the b array here to test the @@ -182,8 +182,8 @@ class TestSetOps(TestCase): assert_array_equal(in1d([], []), []) def test_in1d_char_array( self ): - a = np.array(['a', 'b', 'c','d','e','c','e','b']) - b = np.array(['a','c']) + a = np.array(['a', 'b', 'c', 'd', 'e', 'c', 'e', 'b']) + b = np.array(['a', 'c']) ec = np.array([True, False, True, False, False, True, False, False]) c = in1d(a, b) @@ -202,9 +202,9 @@ class TestSetOps(TestCase): def test_in1d_ravel(self): # Test that in1d ravels its input arrays. This is not documented # behavior however. The test is to ensure consistentency. - a = np.arange(6).reshape(2,3) - b = np.arange(3,9).reshape(3,2) - long_b = np.arange(3, 63).reshape(30,2) + a = np.arange(6).reshape(2, 3) + b = np.arange(3, 9).reshape(3, 2) + long_b = np.arange(3, 63).reshape(30, 2) ec = np.array([False, False, False, True, True, True]) assert_array_equal(in1d(a, b, assume_unique=True), ec) @@ -220,7 +220,7 @@ class TestSetOps(TestCase): c = union1d( a, b ) assert_array_equal( c, ec ) - assert_array_equal([], union1d([],[])) + assert_array_equal([], union1d([], [])) def test_setdiff1d( self ): a = np.array( [6, 5, 4, 7, 1, 2, 7, 4] ) @@ -236,12 +236,12 @@ class TestSetOps(TestCase): c = setdiff1d( a, b ) assert_array_equal( c, ec ) - assert_array_equal([], setdiff1d([],[])) + assert_array_equal([], setdiff1d([], [])) def test_setdiff1d_char_array(self): - a = np.array(['a','b','c']) - b = np.array(['a','b','s']) - assert_array_equal(setdiff1d(a,b),np.array(['c'])) + a = np.array(['a', 'b', 'c']) + b = np.array(['a', 'b', 's']) + assert_array_equal(setdiff1d(a, b), np.array(['c'])) def test_manyways( self ): a = np.array( [5, 7, 1, 2, 8] ) diff --git a/numpy/lib/tests/test_financial.py b/numpy/lib/tests/test_financial.py index 1a276a429..1894da8cb 100644 --- a/numpy/lib/tests/test_financial.py +++ b/numpy/lib/tests/test_financial.py @@ -5,7 +5,7 @@ import numpy as np class TestFinancial(TestCase): def test_rate(self): - assert_almost_equal(np.rate(10,0,-3500,10000), + assert_almost_equal(np.rate(10, 0, -3500, 10000), 0.1107, 4) def test_irr(self): @@ -14,127 +14,127 @@ class TestFinancial(TestCase): 0.0524, 2) def test_pv(self): - assert_almost_equal(np.pv(0.07,20,12000,0), + assert_almost_equal(np.pv(0.07, 20, 12000, 0), -127128.17, 2) def test_fv(self): - assert_almost_equal(np.fv(0.075, 20, -2000,0,0), + assert_almost_equal(np.fv(0.075, 20, -2000, 0, 0), 86609.36, 2) def test_pmt(self): - assert_almost_equal(np.pmt(0.08/12,5*12,15000), + assert_almost_equal(np.pmt(0.08/12, 5*12, 15000), -304.146, 3) def test_ppmt(self): - np.round(np.ppmt(0.1/12,1,60,55000),2) == 710.25 + np.round(np.ppmt(0.1/12, 1, 60, 55000), 2) == 710.25 def test_ipmt(self): - np.round(np.ipmt(0.1/12,1,24,2000),2) == 16.67 + np.round(np.ipmt(0.1/12, 1, 24, 2000), 2) == 16.67 def test_nper(self): - assert_almost_equal(np.nper(0.075,-2000,0,100000.), + assert_almost_equal(np.nper(0.075, -2000, 0, 100000.), 21.54, 2) def test_nper2(self): - assert_almost_equal(np.nper(0.0,-2000,0,100000.), + assert_almost_equal(np.nper(0.0, -2000, 0, 100000.), 50.0, 1) def test_npv(self): - assert_almost_equal(np.npv(0.05,[-15000,1500,2500,3500,4500,6000]), + assert_almost_equal(np.npv(0.05, [-15000, 1500, 2500, 3500, 4500, 6000]), 122.89, 2) def test_mirr(self): - val = [-4500,-800,800,800,600,600,800,800,700,3000] + val = [-4500, -800, 800, 800, 600, 600, 800, 800, 700, 3000] assert_almost_equal(np.mirr(val, 0.08, 0.055), 0.0666, 4) - val = [-120000,39000,30000,21000,37000,46000] + val = [-120000, 39000, 30000, 21000, 37000, 46000] assert_almost_equal(np.mirr(val, 0.10, 0.12), 0.126094, 6) - val = [100,200,-50,300,-200] + val = [100, 200, -50, 300, -200] assert_almost_equal(np.mirr(val, 0.05, 0.06), 0.3428, 4) - val = [39000,30000,21000,37000,46000] + val = [39000, 30000, 21000, 37000, 46000] assert_(np.isnan(np.mirr(val, 0.10, 0.12))) def test_when(self): #begin - assert_almost_equal(np.rate(10,20,-3500,10000,1), - np.rate(10,20,-3500,10000,'begin'), 4) + assert_almost_equal(np.rate(10, 20, -3500, 10000, 1), + np.rate(10, 20, -3500, 10000, 'begin'), 4) #end - assert_almost_equal(np.rate(10,20,-3500,10000), - np.rate(10,20,-3500,10000,'end'), 4) - assert_almost_equal(np.rate(10,20,-3500,10000,0), - np.rate(10,20,-3500,10000,'end'), 4) + assert_almost_equal(np.rate(10, 20, -3500, 10000), + np.rate(10, 20, -3500, 10000, 'end'), 4) + assert_almost_equal(np.rate(10, 20, -3500, 10000, 0), + np.rate(10, 20, -3500, 10000, 'end'), 4) # begin - assert_almost_equal(np.pv(0.07,20,12000,0,1), - np.pv(0.07,20,12000,0,'begin'), 2) + assert_almost_equal(np.pv(0.07, 20, 12000, 0, 1), + np.pv(0.07, 20, 12000, 0, 'begin'), 2) # end - assert_almost_equal(np.pv(0.07,20,12000,0), - np.pv(0.07,20,12000,0,'end'), 2) - assert_almost_equal(np.pv(0.07,20,12000,0,0), - np.pv(0.07,20,12000,0,'end'), 2) + assert_almost_equal(np.pv(0.07, 20, 12000, 0), + np.pv(0.07, 20, 12000, 0, 'end'), 2) + assert_almost_equal(np.pv(0.07, 20, 12000, 0, 0), + np.pv(0.07, 20, 12000, 0, 'end'), 2) # begin - assert_almost_equal(np.fv(0.075, 20, -2000,0,1), - np.fv(0.075, 20, -2000,0,'begin'), 4) + assert_almost_equal(np.fv(0.075, 20, -2000, 0, 1), + np.fv(0.075, 20, -2000, 0, 'begin'), 4) # end - assert_almost_equal(np.fv(0.075, 20, -2000,0), - np.fv(0.075, 20, -2000,0,'end'), 4) - assert_almost_equal(np.fv(0.075, 20, -2000,0,0), - np.fv(0.075, 20, -2000,0,'end'), 4) + assert_almost_equal(np.fv(0.075, 20, -2000, 0), + np.fv(0.075, 20, -2000, 0, 'end'), 4) + assert_almost_equal(np.fv(0.075, 20, -2000, 0, 0), + np.fv(0.075, 20, -2000, 0, 'end'), 4) # begin - assert_almost_equal(np.pmt(0.08/12,5*12,15000.,0,1), - np.pmt(0.08/12,5*12,15000.,0,'begin'), 4) + assert_almost_equal(np.pmt(0.08/12, 5*12, 15000., 0, 1), + np.pmt(0.08/12, 5*12, 15000., 0, 'begin'), 4) # end - assert_almost_equal(np.pmt(0.08/12,5*12,15000.,0), - np.pmt(0.08/12,5*12,15000.,0,'end'), 4) - assert_almost_equal(np.pmt(0.08/12,5*12,15000.,0,0), - np.pmt(0.08/12,5*12,15000.,0,'end'), 4) + assert_almost_equal(np.pmt(0.08/12, 5*12, 15000., 0), + np.pmt(0.08/12, 5*12, 15000., 0, 'end'), 4) + assert_almost_equal(np.pmt(0.08/12, 5*12, 15000., 0, 0), + np.pmt(0.08/12, 5*12, 15000., 0, 'end'), 4) # begin - assert_almost_equal(np.ppmt(0.1/12,1,60,55000,0,1), - np.ppmt(0.1/12,1,60,55000,0,'begin'), 4) + assert_almost_equal(np.ppmt(0.1/12, 1, 60, 55000, 0, 1), + np.ppmt(0.1/12, 1, 60, 55000, 0, 'begin'), 4) # end - assert_almost_equal(np.ppmt(0.1/12,1,60,55000,0), - np.ppmt(0.1/12,1,60,55000,0,'end'), 4) - assert_almost_equal(np.ppmt(0.1/12,1,60,55000,0,0), - np.ppmt(0.1/12,1,60,55000,0,'end'), 4) + assert_almost_equal(np.ppmt(0.1/12, 1, 60, 55000, 0), + np.ppmt(0.1/12, 1, 60, 55000, 0, 'end'), 4) + assert_almost_equal(np.ppmt(0.1/12, 1, 60, 55000, 0, 0), + np.ppmt(0.1/12, 1, 60, 55000, 0, 'end'), 4) # begin - assert_almost_equal(np.ipmt(0.1/12,1,24,2000,0,1), - np.ipmt(0.1/12,1,24,2000,0,'begin'), 4) + assert_almost_equal(np.ipmt(0.1/12, 1, 24, 2000, 0, 1), + np.ipmt(0.1/12, 1, 24, 2000, 0, 'begin'), 4) # end - assert_almost_equal(np.ipmt(0.1/12,1,24,2000,0), - np.ipmt(0.1/12,1,24,2000,0,'end'), 4) - assert_almost_equal(np.ipmt(0.1/12,1,24,2000,0,0), - np.ipmt(0.1/12,1,24,2000,0,'end'), 4) + assert_almost_equal(np.ipmt(0.1/12, 1, 24, 2000, 0), + np.ipmt(0.1/12, 1, 24, 2000, 0, 'end'), 4) + assert_almost_equal(np.ipmt(0.1/12, 1, 24, 2000, 0, 0), + np.ipmt(0.1/12, 1, 24, 2000, 0, 'end'), 4) # begin - assert_almost_equal(np.nper(0.075,-2000,0,100000.,1), - np.nper(0.075,-2000,0,100000.,'begin'), 4) + assert_almost_equal(np.nper(0.075, -2000, 0, 100000., 1), + np.nper(0.075, -2000, 0, 100000., 'begin'), 4) # end - assert_almost_equal(np.nper(0.075,-2000,0,100000.), - np.nper(0.075,-2000,0,100000.,'end'), 4) - assert_almost_equal(np.nper(0.075,-2000,0,100000.,0), - np.nper(0.075,-2000,0,100000.,'end'), 4) + assert_almost_equal(np.nper(0.075, -2000, 0, 100000.), + np.nper(0.075, -2000, 0, 100000., 'end'), 4) + assert_almost_equal(np.nper(0.075, -2000, 0, 100000., 0), + np.nper(0.075, -2000, 0, 100000., 'end'), 4) def test_broadcast(self): - assert_almost_equal(np.nper(0.075,-2000,0,100000.,[0,1]), - [ 21.5449442 , 20.76156441], 4) + assert_almost_equal(np.nper(0.075, -2000, 0, 100000., [0, 1]), + [ 21.5449442, 20.76156441], 4) - assert_almost_equal(np.ipmt(0.1/12,list(range(5)), 24, 2000), + assert_almost_equal(np.ipmt(0.1/12, list(range(5)), 24, 2000), [-17.29165168, -16.66666667, -16.03647345, -15.40102862, -14.76028842], 4) - assert_almost_equal(np.ppmt(0.1/12,list(range(5)), 24, 2000), - [-74.998201 , -75.62318601, -76.25337923, + assert_almost_equal(np.ppmt(0.1/12, list(range(5)), 24, 2000), + [-74.998201, -75.62318601, -76.25337923, -76.88882405, -77.52956425], 4) - assert_almost_equal(np.ppmt(0.1/12,list(range(5)), 24, 2000, 0, - [0,0,1,'end','begin']), - [-74.998201 , -75.62318601, -75.62318601, + assert_almost_equal(np.ppmt(0.1/12, list(range(5)), 24, 2000, 0, + [0, 0, 1, 'end', 'begin']), + [-74.998201, -75.62318601, -75.62318601, -76.88882405, -76.88882405], 4) if __name__ == "__main__": diff --git a/numpy/lib/tests/test_format.py b/numpy/lib/tests/test_format.py index 8b809891f..694dc4591 100644 --- a/numpy/lib/tests/test_format.py +++ b/numpy/lib/tests/test_format.py @@ -331,11 +331,11 @@ for scalar in scalars: # 1-D basic, # 2-D C-contiguous - basic.reshape((3,5)), + basic.reshape((3, 5)), # 2-D F-contiguous - basic.reshape((3,5)).T, + basic.reshape((3, 5)).T, # 2-D non-contiguous - basic.reshape((3,5))[::-1,::2], + basic.reshape((3, 5))[::-1, ::2], ]) # More complicated record arrays. @@ -354,8 +354,8 @@ Pdescr = [ # A plain list of tuples with values for testing: PbufferT = [ # x y z - ([3,2], [[6.,4.],[6.,4.]], 8), - ([4,3], [[7.,5.],[7.,5.]], 9), + ([3, 2], [[6., 4.], [6., 4.]], 8), + ([4, 3], [[7., 5.], [7., 5.]], 9), ] @@ -394,8 +394,8 @@ NbufferT = [ # x Info color info y z # value y2 Info2 name z2 Name Value # name value y3 z3 - ([3,2], (6j, 6., ('nn', [6j,4j], [6.,4.], [1,2]), 'NN', True), 'cc', ('NN', 6j), [[6.,4.],[6.,4.]], 8), - ([4,3], (7j, 7., ('oo', [7j,5j], [7.,5.], [2,1]), 'OO', False), 'dd', ('OO', 7j), [[7.,5.],[7.,5.]], 9), + ([3, 2], (6j, 6., ('nn', [6j, 4j], [6., 4.], [1, 2]), 'NN', True), 'cc', ('NN', 6j), [[6., 4.], [6., 4.]], 8), + ([4, 3], (7j, 7., ('oo', [7j, 5j], [7., 5.], [2, 1]), 'OO', False), 'dd', ('OO', 7j), [[7., 5.], [7., 5.]], 9), ] record_arrays = [ @@ -520,7 +520,7 @@ def test_bad_magic_args(): def test_large_header(): s = BytesIO() d = {'a':1,'b':2} - format.write_array_header_1_0(s,d) + format.write_array_header_1_0(s, d) s = BytesIO() d = {'a':1,'b':2,'c':'x'*256*256} @@ -538,18 +538,18 @@ def test_bad_header(): assert_raises(ValueError, format.read_array_header_1_0, s) # headers without the exact keys required should fail - d = {"shape":(1,2), + d = {"shape":(1, 2), "descr":"x"} s = BytesIO() - format.write_array_header_1_0(s,d) + format.write_array_header_1_0(s, d) assert_raises(ValueError, format.read_array_header_1_0, s) - d = {"shape":(1,2), + d = {"shape":(1, 2), "fortran_order":False, "descr":"x", "extrakey":-1} s = BytesIO() - format.write_array_header_1_0(s,d) + format.write_array_header_1_0(s, d) assert_raises(ValueError, format.read_array_header_1_0, s) if __name__ == "__main__": diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index 65519d0bc..28f094653 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -174,10 +174,10 @@ class TestInsert(TestCase): assert_equal(insert(a, 0, 1), [1, 1, 2, 3]) assert_equal(insert(a, 3, 1), [1, 2, 3, 1]) assert_equal(insert(a, [1, 1, 1], [1, 2, 3]), [1, 1, 2, 3, 2, 3]) - assert_equal(insert(a, 1,[1,2,3]), [1, 1, 2, 3, 2, 3]) - assert_equal(insert(a,[1,-1,3],9),[1,9,2,9,3,9]) - assert_equal(insert(a,slice(-1,None,-1), 9),[9,1,9,2,9,3]) - assert_equal(insert(a,[-1,1,3], [7,8,9]),[1,8,2,7,3,9]) + assert_equal(insert(a, 1, [1, 2, 3]), [1, 1, 2, 3, 2, 3]) + assert_equal(insert(a, [1, -1, 3], 9), [1, 9, 2, 9, 3, 9]) + assert_equal(insert(a, slice(-1, None, -1), 9), [9, 1, 9, 2, 9, 3]) + assert_equal(insert(a, [-1, 1, 3], [7, 8, 9]), [1, 8, 2, 7, 3, 9]) b = np.array([0, 1], dtype=np.float64) assert_equal(insert(b, 0, b[0]), [0., 0., 1.]) assert_equal(insert(b, [], []), b) @@ -185,42 +185,42 @@ class TestInsert(TestCase): #assert_equal(insert(a, np.array([True]*4), 9), [9,1,9,2,9,3,9]) with warnings.catch_warnings(record=True) as w: warnings.filterwarnings('always', '', FutureWarning) - assert_equal(insert(a, np.array([True]*4), 9), [1,9,9,9,9,2,3]) + assert_equal(insert(a, np.array([True]*4), 9), [1, 9, 9, 9, 9, 2, 3]) assert_(w[0].category is FutureWarning) def test_multidim(self): a = [[1, 1, 1]] r = [[2, 2, 2], [1, 1, 1]] - assert_equal(insert(a, 0, [1]), [1,1,1,1]) + assert_equal(insert(a, 0, [1]), [1, 1, 1, 1]) assert_equal(insert(a, 0, [2, 2, 2], axis=0), r) assert_equal(insert(a, 0, 2, axis=0), r) assert_equal(insert(a, 2, 2, axis=1), [[1, 1, 2, 1]]) a = np.array([[1, 1], [2, 2], [3, 3]]) - b = np.arange(1,4).repeat(3).reshape(3,3) - c = np.concatenate((a[:,0:1], np.arange(1,4).repeat(3).reshape(3,3).T, - a[:,1:2]), axis=1) - assert_equal(insert(a, [1], [[1],[2],[3]], axis=1), b) + b = np.arange(1, 4).repeat(3).reshape(3, 3) + c = np.concatenate((a[:, 0:1], np.arange(1, 4).repeat(3).reshape(3, 3).T, + a[:, 1:2]), axis=1) + assert_equal(insert(a, [1], [[1], [2], [3]], axis=1), b) assert_equal(insert(a, [1], [1, 2, 3], axis=1), c) # scalars behave differently, in this case exactly opposite: assert_equal(insert(a, 1, [1, 2, 3], axis=1), b) - assert_equal(insert(a, 1, [[1],[2],[3]], axis=1), c) + assert_equal(insert(a, 1, [[1], [2], [3]], axis=1), c) - a = np.arange(4).reshape(2,2) - assert_equal(insert(a[:,:1], 1, a[:,1], axis=1), a) + a = np.arange(4).reshape(2, 2) + assert_equal(insert(a[:, :1], 1, a[:, 1], axis=1), a) assert_equal(insert(a[:1,:], 1, a[1,:], axis=0), a) # negative axis value - a = np.arange(24).reshape((2,3,4)) - assert_equal(insert(a, 1, a[:,:,3], axis=-1), - insert(a, 1, a[:,:,3], axis=2)) - assert_equal(insert(a, 1, a[:,2,:], axis=-2), - insert(a, 1, a[:,2,:], axis=1)) + a = np.arange(24).reshape((2, 3, 4)) + assert_equal(insert(a, 1, a[:,:, 3], axis=-1), + insert(a, 1, a[:,:, 3], axis=2)) + assert_equal(insert(a, 1, a[:, 2,:], axis=-2), + insert(a, 1, a[:, 2,:], axis=1)) # invalid axis value - assert_raises(IndexError, insert, a, 1, a[:,2,:], axis=3) - assert_raises(IndexError, insert, a, 1, a[:,2,:], axis=-4) + assert_raises(IndexError, insert, a, 1, a[:, 2,:], axis=3) + assert_raises(IndexError, insert, a, 1, a[:, 2,:], axis=-4) def test_0d(self): # This is an error in the future @@ -236,9 +236,9 @@ class TestInsert(TestCase): a = np.arange(10).view(SubClass) assert_(isinstance(np.insert(a, 0, [0]), SubClass)) assert_(isinstance(np.insert(a, [], []), SubClass)) - assert_(isinstance(np.insert(a, [0,1], [1,2]), SubClass)) - assert_(isinstance(np.insert(a, slice(1,2), [1,2]), SubClass)) - assert_(isinstance(np.insert(a, slice(1,-2), []), SubClass)) + assert_(isinstance(np.insert(a, [0, 1], [1, 2]), SubClass)) + assert_(isinstance(np.insert(a, slice(1, 2), [1, 2]), SubClass)) + assert_(isinstance(np.insert(a, slice(1, -2), []), SubClass)) # This is an error in the future: a = np.array(1).view(SubClass) assert_(isinstance(np.insert(a, 0, [0]), SubClass)) @@ -355,10 +355,10 @@ class TestDiff(TestCase): def test_nd(self): x = 20 * rand(10, 20, 30) - out1 = x[:, :, 1:] - x[:, :, :-1] - out2 = out1[:, :, 1:] - out1[:, :, :-1] - out3 = x[1:, :, :] - x[:-1, :, :] - out4 = out3[1:, :, :] - out3[:-1, :, :] + out1 = x[:,:, 1:] - x[:,:, :-1] + out2 = out1[:,:, 1:] - out1[:,:, :-1] + out3 = x[1:,:,:] - x[:-1,:,:] + out4 = out3[1:,:,:] - out3[:-1,:,:] assert_array_equal(diff(x), out1) assert_array_equal(diff(x, n=2), out2) assert_array_equal(diff(x, axis=0), out3) @@ -368,7 +368,7 @@ class TestDiff(TestCase): class TestDelete(TestCase): def setUp(self): self.a = np.arange(5) - self.nd_a = np.arange(5).repeat(2).reshape(1,5,2) + self.nd_a = np.arange(5).repeat(2).reshape(1, 5, 2) def _check_inverse_of_slicing(self, indices): a_del = delete(self.a, indices) @@ -380,8 +380,8 @@ class TestDelete(TestCase): indices = indices[(indices >= 0) & (indices < 5)] assert_array_equal(setxor1d(a_del, self.a[indices,]), self.a, err_msg=msg) - xor = setxor1d(nd_a_del[0,:,0], self.nd_a[0,indices,0]) - assert_array_equal(xor, self.nd_a[0,:,0], err_msg=msg) + xor = setxor1d(nd_a_del[0,:, 0], self.nd_a[0, indices, 0]) + assert_array_equal(xor, self.nd_a[0,:, 0], err_msg=msg) def test_slices(self): lims = [-6, -2, 0, 1, 2, 4, 5] @@ -394,7 +394,7 @@ class TestDelete(TestCase): def test_fancy(self): # Deprecation/FutureWarning tests should be kept after change. - self._check_inverse_of_slicing(np.array([[0,1],[2,1]])) + self._check_inverse_of_slicing(np.array([[0, 1], [2, 1]])) assert_raises(DeprecationWarning, delete, self.a, [100]) assert_raises(DeprecationWarning, delete, self.a, [-100]) with warnings.catch_warnings(record=True) as w: @@ -422,9 +422,9 @@ class TestDelete(TestCase): a = self.a.view(SubClass) assert_(isinstance(delete(a, 0), SubClass)) assert_(isinstance(delete(a, []), SubClass)) - assert_(isinstance(delete(a, [0,1]), SubClass)) - assert_(isinstance(delete(a, slice(1,2)), SubClass)) - assert_(isinstance(delete(a, slice(1,-2)), SubClass)) + assert_(isinstance(delete(a, [0, 1]), SubClass)) + assert_(isinstance(delete(a, slice(1, 2)), SubClass)) + assert_(isinstance(delete(a, slice(1, -2)), SubClass)) class TestGradient(TestCase): def test_basic(self): @@ -598,7 +598,7 @@ class TestVectorize(TestCase): while _p: res = res*x + _p.pop(0) return res - vpolyval = np.vectorize(mypolyval, excluded=['p',1]) + vpolyval = np.vectorize(mypolyval, excluded=['p', 1]) ans = [3, 6] assert_array_equal(ans, vpolyval(x=[0, 1], p=[1, 2, 3])) assert_array_equal(ans, vpolyval([0, 1], p=[1, 2, 3])) @@ -776,18 +776,18 @@ class TestTrapz(TestCase): wz[0] /= 2 wz[-1] /= 2 - q = x[:, None, None] + y[None, :, None] + z[None, None, :] + q = x[:, None, None] + y[None,:, None] + z[None, None,:] qx = (q * wx[:, None, None]).sum(axis=0) - qy = (q * wy[None, :, None]).sum(axis=1) - qz = (q * wz[None, None, :]).sum(axis=2) + qy = (q * wy[None,:, None]).sum(axis=1) + qz = (q * wz[None, None,:]).sum(axis=2) # n-d `x` r = trapz(q, x=x[:, None, None], axis=0) assert_almost_equal(r, qx) - r = trapz(q, x=y[None, :, None], axis=1) + r = trapz(q, x=y[None,:, None], axis=1) assert_almost_equal(r, qy) - r = trapz(q, x=z[None, None, :], axis=2) + r = trapz(q, x=z[None, None,:], axis=2) assert_almost_equal(r, qz) # 1-d `x` @@ -1052,7 +1052,7 @@ class TestHistogramdd(TestCase): def test_identical_samples(self): x = np.zeros((10, 2), int) hist, edges = histogramdd(x, bins=2) - assert_array_equal(edges[0], np.array([-0.5, 0. , 0.5])) + assert_array_equal(edges[0], np.array([-0.5, 0., 0.5])) def test_empty(self): a, b = histogramdd([[], []], bins=([0, 1], [0, 1])) @@ -1114,23 +1114,23 @@ class TestCheckFinite(TestCase): class TestCorrCoef(TestCase): A = np.array([[ 0.15391142, 0.18045767, 0.14197213], [ 0.70461506, 0.96474128, 0.27906989], - [ 0.9297531 , 0.32296769, 0.19267156]]) - B = np.array([[ 0.10377691, 0.5417086 , 0.49807457], + [ 0.9297531, 0.32296769, 0.19267156]]) + B = np.array([[ 0.10377691, 0.5417086, 0.49807457], [ 0.82872117, 0.77801674, 0.39226705], - [ 0.9314666 , 0.66800209, 0.03538394]]) - res1 = np.array([[ 1. , 0.9379533 , -0.04931983], - [ 0.9379533 , 1. , 0.30007991], + [ 0.9314666, 0.66800209, 0.03538394]]) + res1 = np.array([[ 1., 0.9379533, -0.04931983], + [ 0.9379533, 1., 0.30007991], [-0.04931983, 0.30007991, 1. ]]) - res2 = np.array([[ 1. , 0.9379533 , -0.04931983, + res2 = np.array([[ 1., 0.9379533, -0.04931983, 0.30151751, 0.66318558, 0.51532523], - [ 0.9379533 , 1. , 0.30007991, + [ 0.9379533, 1., 0.30007991, - 0.04781421, 0.88157256, 0.78052386], - [-0.04931983, 0.30007991, 1. , + [-0.04931983, 0.30007991, 1., - 0.96717111, 0.71483595, 0.83053601], [ 0.30151751, -0.04781421, -0.96717111, - 1. , -0.51366032, -0.66173113], + 1., -0.51366032, -0.66173113], [ 0.66318558, 0.88157256, 0.71483595, - - 0.51366032, 1. , 0.98317823], + - 0.51366032, 1., 0.98317823], [ 0.51532523, 0.78052386, 0.83053601, - 0.66173113, 0.98317823, 1. ]]) @@ -1160,10 +1160,10 @@ class TestCov(TestCase): class Test_I0(TestCase): def test_simple(self): assert_almost_equal(i0(0.5), np.array(1.0634833707413234)) - A = np.array([ 0.49842636, 0.6969809 , 0.22011976, 0.0155549]) + A = np.array([ 0.49842636, 0.6969809, 0.22011976, 0.0155549]) assert_almost_equal(i0(A), np.array([ 1.06307822, 1.12518299, 1.01214991, 1.00006049])) - B = np.array([[ 0.827002 , 0.99959078], + B = np.array([[ 0.827002, 0.99959078], [ 0.89694769, 0.39298162], [ 0.37954418, 0.05206293], [ 0.36465447, 0.72446427], @@ -1173,7 +1173,7 @@ class Test_I0(TestCase): [ 1.21147086, 1.0389829 ], [ 1.03633899, 1.00067775], [ 1.03352052, 1.13557954], - [ 1.0588429 , 1.06432317]])) + [ 1.0588429, 1.06432317]])) class TestKaiser(TestCase): @@ -1182,10 +1182,10 @@ class TestKaiser(TestCase): assert_(np.isfinite(kaiser(1, 1.0))) assert_almost_equal(kaiser(2, 1.0), np.array([ 0.78984831, 0.78984831])) assert_almost_equal(kaiser(5, 1.0), - np.array([ 0.78984831, 0.94503323, 1. , + np.array([ 0.78984831, 0.94503323, 1., 0.94503323, 0.78984831])) assert_almost_equal(kaiser(5, 1.56789), - np.array([ 0.58285404, 0.88409679, 1. , + np.array([ 0.58285404, 0.88409679, 1., 0.88409679, 0.58285404])) def test_int_beta(self): diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py index 32b3c7036..9002331ce 100644 --- a/numpy/lib/tests/test_index_tricks.py +++ b/numpy/lib/tests/test_index_tricks.py @@ -8,42 +8,42 @@ from numpy import ( array, ones, r_, mgrid, unravel_index, zeros, where, class TestRavelUnravelIndex(TestCase): def test_basic(self): - assert_equal(np.unravel_index(2,(2,2)), (1,0)) - assert_equal(np.ravel_multi_index((1,0),(2,2)), 2) - assert_equal(np.unravel_index(254,(17,94)), (2,66)) - assert_equal(np.ravel_multi_index((2,66),(17,94)), 254) - assert_raises(ValueError, np.unravel_index, -1, (2,2)) - assert_raises(TypeError, np.unravel_index, 0.5, (2,2)) - assert_raises(ValueError, np.unravel_index, 4, (2,2)) - assert_raises(ValueError, np.ravel_multi_index, (-3,1), (2,2)) - assert_raises(ValueError, np.ravel_multi_index, (2,1), (2,2)) - assert_raises(ValueError, np.ravel_multi_index, (0,-3), (2,2)) - assert_raises(ValueError, np.ravel_multi_index, (0,2), (2,2)) - assert_raises(TypeError, np.ravel_multi_index, (0.1,0.), (2,2)) - - assert_equal(np.unravel_index((2*3 + 1)*6 + 4, (4,3,6)), [2,1,4]) - assert_equal(np.ravel_multi_index([2,1,4], (4,3,6)), (2*3 + 1)*6 + 4) - - arr = np.array([[3,6,6],[4,5,1]]) - assert_equal(np.ravel_multi_index(arr, (7,6)), [22,41,37]) - assert_equal(np.ravel_multi_index(arr, (7,6), order='F'), [31,41,13]) - assert_equal(np.ravel_multi_index(arr, (4,6), mode='clip'), [22,23,19]) - assert_equal(np.ravel_multi_index(arr, (4,4), mode=('clip','wrap')), - [12,13,13]) - assert_equal(np.ravel_multi_index((3,1,4,1), (6,7,8,9)), 1621) - - assert_equal(np.unravel_index(np.array([22, 41, 37]), (7,6)), - [[3, 6, 6],[4, 5, 1]]) - assert_equal(np.unravel_index(np.array([31, 41, 13]), (7,6), order='F'), + assert_equal(np.unravel_index(2, (2, 2)), (1, 0)) + assert_equal(np.ravel_multi_index((1, 0), (2, 2)), 2) + assert_equal(np.unravel_index(254, (17, 94)), (2, 66)) + assert_equal(np.ravel_multi_index((2, 66), (17, 94)), 254) + assert_raises(ValueError, np.unravel_index, -1, (2, 2)) + assert_raises(TypeError, np.unravel_index, 0.5, (2, 2)) + assert_raises(ValueError, np.unravel_index, 4, (2, 2)) + assert_raises(ValueError, np.ravel_multi_index, (-3, 1), (2, 2)) + assert_raises(ValueError, np.ravel_multi_index, (2, 1), (2, 2)) + assert_raises(ValueError, np.ravel_multi_index, (0, -3), (2, 2)) + assert_raises(ValueError, np.ravel_multi_index, (0, 2), (2, 2)) + assert_raises(TypeError, np.ravel_multi_index, (0.1, 0.), (2, 2)) + + assert_equal(np.unravel_index((2*3 + 1)*6 + 4, (4, 3, 6)), [2, 1, 4]) + assert_equal(np.ravel_multi_index([2, 1, 4], (4, 3, 6)), (2*3 + 1)*6 + 4) + + arr = np.array([[3, 6, 6], [4, 5, 1]]) + assert_equal(np.ravel_multi_index(arr, (7, 6)), [22, 41, 37]) + assert_equal(np.ravel_multi_index(arr, (7, 6), order='F'), [31, 41, 13]) + assert_equal(np.ravel_multi_index(arr, (4, 6), mode='clip'), [22, 23, 19]) + assert_equal(np.ravel_multi_index(arr, (4, 4), mode=('clip', 'wrap')), + [12, 13, 13]) + assert_equal(np.ravel_multi_index((3, 1, 4, 1), (6, 7, 8, 9)), 1621) + + assert_equal(np.unravel_index(np.array([22, 41, 37]), (7, 6)), [[3, 6, 6], [4, 5, 1]]) - assert_equal(np.unravel_index(1621, (6,7,8,9)), [3,1,4,1]) + assert_equal(np.unravel_index(np.array([31, 41, 13]), (7, 6), order='F'), + [[3, 6, 6], [4, 5, 1]]) + assert_equal(np.unravel_index(1621, (6, 7, 8, 9)), [3, 1, 4, 1]) def test_dtypes(self): # Test with different data types for dtype in [np.int16, np.uint16, np.int32, np.uint32, np.int64, np.uint64]: - coords = np.array([[1,0,1,2,3,4],[1,6,1,3,2,0]], dtype=dtype) - shape = (5,8) + coords = np.array([[1, 0, 1, 2, 3, 4], [1, 6, 1, 3, 2, 0]], dtype=dtype) + shape = (5, 8) uncoords = 8*coords[0]+coords[1] assert_equal(np.ravel_multi_index(coords, shape), uncoords) assert_equal(coords, np.unravel_index(uncoords, shape)) @@ -51,9 +51,9 @@ class TestRavelUnravelIndex(TestCase): assert_equal(np.ravel_multi_index(coords, shape, order='F'), uncoords) assert_equal(coords, np.unravel_index(uncoords, shape, order='F')) - coords = np.array([[1,0,1,2,3,4],[1,6,1,3,2,0],[1,3,1,0,9,5]], + coords = np.array([[1, 0, 1, 2, 3, 4], [1, 6, 1, 3, 2, 0], [1, 3, 1, 0, 9, 5]], dtype=dtype) - shape = (5,8,10) + shape = (5, 8, 10) uncoords = 10*(8*coords[0]+coords[1])+coords[2] assert_equal(np.ravel_multi_index(coords, shape), uncoords) assert_equal(coords, np.unravel_index(uncoords, shape)) @@ -63,12 +63,12 @@ class TestRavelUnravelIndex(TestCase): def test_clipmodes(self): # Test clipmodes - assert_equal(np.ravel_multi_index([5,1,-1,2], (4,3,7,12), mode='wrap'), - np.ravel_multi_index([1,1,6,2], (4,3,7,12))) - assert_equal(np.ravel_multi_index([5,1,-1,2], (4,3,7,12), - mode=('wrap','raise','clip','raise')), - np.ravel_multi_index([1,1,0,2], (4,3,7,12))) - assert_raises(ValueError, np.ravel_multi_index, [5,1,-1,2], (4,3,7,12)) + assert_equal(np.ravel_multi_index([5, 1, -1, 2], (4, 3, 7, 12), mode='wrap'), + np.ravel_multi_index([1, 1, 6, 2], (4, 3, 7, 12))) + assert_equal(np.ravel_multi_index([5, 1, -1, 2], (4, 3, 7, 12), + mode=('wrap', 'raise', 'clip', 'raise')), + np.ravel_multi_index([1, 1, 0, 2], (4, 3, 7, 12))) + assert_raises(ValueError, np.ravel_multi_index, [5, 1, -1, 2], (4, 3, 7, 12)) class TestGrid(TestCase): def test_basic(self): @@ -77,63 +77,63 @@ class TestGrid(TestCase): assert_(a.shape == (10,)) assert_(b.shape == (20,)) assert_(a[0] == -1) - assert_almost_equal(a[-1],1) + assert_almost_equal(a[-1], 1) assert_(b[0] == -1) - assert_almost_equal(b[1]-b[0],0.1,11) - assert_almost_equal(b[-1],b[0]+19*0.1,11) - assert_almost_equal(a[1]-a[0],2.0/9.0,11) + assert_almost_equal(b[1]-b[0], 0.1, 11) + assert_almost_equal(b[-1], b[0]+19*0.1, 11) + assert_almost_equal(a[1]-a[0], 2.0/9.0, 11) def test_linspace_equivalence(self): - y,st = np.linspace(2,10,retstep=1) - assert_almost_equal(st,8/49.0) - assert_array_almost_equal(y,mgrid[2:10:50j],13) + y, st = np.linspace(2, 10, retstep=1) + assert_almost_equal(st, 8/49.0) + assert_array_almost_equal(y, mgrid[2:10:50j], 13) def test_nd(self): - c = mgrid[-1:1:10j,-2:2:10j] - d = mgrid[-1:1:0.1,-2:2:0.2] - assert_(c.shape == (2,10,10)) - assert_(d.shape == (2,20,20)) - assert_array_equal(c[0][0,:],-ones(10,'d')) - assert_array_equal(c[1][:,0],-2*ones(10,'d')) - assert_array_almost_equal(c[0][-1,:],ones(10,'d'),11) - assert_array_almost_equal(c[1][:,-1],2*ones(10,'d'),11) - assert_array_almost_equal(d[0,1,:]-d[0,0,:], 0.1*ones(20,'d'),11) - assert_array_almost_equal(d[1,:,1]-d[1,:,0], 0.2*ones(20,'d'),11) + c = mgrid[-1:1:10j, -2:2:10j] + d = mgrid[-1:1:0.1, -2:2:0.2] + assert_(c.shape == (2, 10, 10)) + assert_(d.shape == (2, 20, 20)) + assert_array_equal(c[0][0,:], -ones(10, 'd')) + assert_array_equal(c[1][:, 0], -2*ones(10, 'd')) + assert_array_almost_equal(c[0][-1,:], ones(10, 'd'), 11) + assert_array_almost_equal(c[1][:, -1], 2*ones(10, 'd'), 11) + assert_array_almost_equal(d[0, 1,:]-d[0, 0,:], 0.1*ones(20, 'd'), 11) + assert_array_almost_equal(d[1,:, 1]-d[1,:, 0], 0.2*ones(20, 'd'), 11) class TestConcatenator(TestCase): def test_1d(self): - assert_array_equal(r_[1,2,3,4,5,6],array([1,2,3,4,5,6])) + assert_array_equal(r_[1, 2, 3, 4, 5, 6], array([1, 2, 3, 4, 5, 6])) b = ones(5) - c = r_[b,0,0,b] - assert_array_equal(c,[1,1,1,1,1,0,0,1,1,1,1,1]) + c = r_[b, 0, 0, b] + assert_array_equal(c, [1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1]) def test_mixed_type(self): g = r_[10.1, 1:10] assert_(g.dtype == 'f8') def test_more_mixed_type(self): - g = r_[-10.1, array([1]), array([2,3,4]), 10.0] + g = r_[-10.1, array([1]), array([2, 3, 4]), 10.0] assert_(g.dtype == 'f8') def test_2d(self): - b = rand(5,5) - c = rand(5,5) - d = r_['1',b,c] # append columns - assert_(d.shape == (5,10)) - assert_array_equal(d[:,:5],b) - assert_array_equal(d[:,5:],c) - d = r_[b,c] - assert_(d.shape == (10,5)) - assert_array_equal(d[:5,:],b) - assert_array_equal(d[5:,:],c) + b = rand(5, 5) + c = rand(5, 5) + d = r_['1', b, c] # append columns + assert_(d.shape == (5, 10)) + assert_array_equal(d[:, :5], b) + assert_array_equal(d[:, 5:], c) + d = r_[b, c] + assert_(d.shape == (10, 5)) + assert_array_equal(d[:5,:], b) + assert_array_equal(d[5:,:], c) class TestNdenumerate(TestCase): def test_basic(self): - a = array([[1,2], [3,4]]) + a = array([[1, 2], [3, 4]]) assert_equal(list(ndenumerate(a)), - [((0,0), 1), ((0,1), 2), ((1,0), 3), ((1,1), 4)]) + [((0, 0), 1), ((0, 1), 2), ((1, 0), 3), ((1, 1), 4)]) class TestIndexExpression(TestCase): @@ -144,17 +144,17 @@ class TestIndexExpression(TestCase): assert_equal(a[:-1], a[index_exp[:-1]]) def test_simple_1(self): - a = np.random.rand(4,5,6) + a = np.random.rand(4, 5, 6) - assert_equal(a[:,:3,[1,2]], a[index_exp[:,:3,[1,2]]]) - assert_equal(a[:,:3,[1,2]], a[s_[:,:3,[1,2]]]) + assert_equal(a[:, :3, [1, 2]], a[index_exp[:, :3, [1, 2]]]) + assert_equal(a[:, :3, [1, 2]], a[s_[:, :3, [1, 2]]]) def test_c_(): - a = np.c_[np.array([[1,2,3]]), 0, 0, np.array([[4,5,6]])] + a = np.c_[np.array([[1, 2, 3]]), 0, 0, np.array([[4, 5, 6]])] assert_equal(a, [[1, 2, 3, 0, 0, 4, 5, 6]]) def test_fill_diagonal(): - a = zeros((3, 3),int) + a = zeros((3, 3), int) fill_diagonal(a, 5) yield (assert_array_equal, a, array([[5, 0, 0], @@ -162,7 +162,7 @@ def test_fill_diagonal(): [0, 0, 5]])) #Test tall matrix - a = zeros((10, 3),int) + a = zeros((10, 3), int) fill_diagonal(a, 5) yield (assert_array_equal, a, array([[5, 0, 0], @@ -177,7 +177,7 @@ def test_fill_diagonal(): [0, 0, 0]])) #Test tall matrix wrap - a = zeros((10, 3),int) + a = zeros((10, 3), int) fill_diagonal(a, 5, True) yield (assert_array_equal, a, array([[5, 0, 0], @@ -192,7 +192,7 @@ def test_fill_diagonal(): [0, 5, 0]])) #Test wide matrix - a = zeros((3, 10),int) + a = zeros((3, 10), int) fill_diagonal(a, 5) yield (assert_array_equal, a, array([[5, 0, 0, 0, 0, 0, 0, 0, 0, 0], @@ -223,7 +223,7 @@ def test_diag_indices(): d3 = diag_indices(2, 3) # And use it to set the diagonal of a zeros array to 1: - a = zeros((2, 2, 2),int) + a = zeros((2, 2, 2), int) a[d3] = 1 yield (assert_array_equal, a, array([[[1, 0], @@ -256,7 +256,7 @@ def test_ndindex(): assert_equal(x, [()]) x = list(np.ndindex(())) - assert_equal(x, [()]) + assert_equal(x, [()]) if __name__ == "__main__": diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py index 4095dd813..af06cd45e 100644 --- a/numpy/lib/tests/test_io.py +++ b/numpy/lib/tests/test_io.py @@ -583,7 +583,7 @@ class TestLoadTxt(TestCase): ('block', int, (2, 2, 3))]) x = np.loadtxt(c, dtype=dt) a = np.array([('aaaa', 1.0, 8.0, - [[[1, 2, 3], [4, 5, 6]],[[7, 8, 9], [10, 11, 12]]])], + [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])], dtype=dt) assert_array_equal(x, a) @@ -1554,7 +1554,7 @@ M 33 21.99 def test_gft_using_filename(self): # Test that we can load data from a filename as well as a file object - wanted = np.arange(6).reshape((2,3)) + wanted = np.arange(6).reshape((2, 3)) if sys.version_info[0] >= 3: # python 3k is known to fail for '\r' linesep = ('\n', '\r\n') diff --git a/numpy/lib/tests/test_nanfunctions.py b/numpy/lib/tests/test_nanfunctions.py index 93a5ef855..292ffdf7a 100644 --- a/numpy/lib/tests/test_nanfunctions.py +++ b/numpy/lib/tests/test_nanfunctions.py @@ -17,7 +17,7 @@ _ndat = np.array( [[ 0.6244, np.nan, 0.2692, 0.0116, np.nan, 0.1170], [ 0.5351, 0.9403, np.nan, 0.2100, 0.4759, 0.2833], [ np.nan, np.nan, np.nan, 0.1042, np.nan, 0.5954], - [ 0.161 , np.nan, np.nan, 0.1859, 0.3146, np.nan]] + [ 0.161, np.nan, np.nan, 0.1859, 0.3146, np.nan]] ) # rows of _ndat with nans removed @@ -131,7 +131,7 @@ class TestNanFunctions_ArgminArgmax(TestCase): assert_(issubclass(w[0].category, NanWarning)) def test_empty(self): - mat = np.zeros((0,3)) + mat = np.zeros((0, 3)) for f in self.nanfuncs: for axis in [0, None]: assert_raises(ValueError, f, mat, axis=axis) @@ -253,7 +253,7 @@ class TestNanFunctions_Sum(TestCase): assert_(len(w) == 0, 'warning raised') def test_empty(self): - mat = np.zeros((0,3)) + mat = np.zeros((0, 3)) if np.__version__[:3] < '1.9': tgt = [np.nan]*3 res = nansum(mat, axis=0) @@ -398,7 +398,7 @@ class TestNanFunctions_MeanVarStd(TestCase): assert_(issubclass(w[0].category, NanWarning)) def test_empty(self): - mat = np.zeros((0,3)) + mat = np.zeros((0, 3)) for f in self.nanfuncs: for axis in [0, None]: with warnings.catch_warnings(record=True) as w: diff --git a/numpy/lib/tests/test_polynomial.py b/numpy/lib/tests/test_polynomial.py index fa166b7f1..617419eee 100644 --- a/numpy/lib/tests/test_polynomial.py +++ b/numpy/lib/tests/test_polynomial.py @@ -86,29 +86,29 @@ class TestDocs(TestCase): return rundocs() def test_roots(self): - assert_array_equal(np.roots([1,0,0]), [0,0]) + assert_array_equal(np.roots([1, 0, 0]), [0, 0]) def test_str_leading_zeros(self): - p = np.poly1d([4,3,2,1]) + p = np.poly1d([4, 3, 2, 1]) p[3] = 0 assert_equal(str(p), " 2\n" "3 x + 2 x + 1") - p = np.poly1d([1,2]) + p = np.poly1d([1, 2]) p[0] = 0 p[1] = 0 assert_equal(str(p), " \n0") def test_polyfit(self) : c = np.array([3., 2., 1.]) - x = np.linspace(0,2,7) - y = np.polyval(c,x) - err = [1,-1,1,-1,1,-1,1] - weights = np.arange(8,1,-1)**2/7.0 + x = np.linspace(0, 2, 7) + y = np.polyval(c, x) + err = [1, -1, 1, -1, 1, -1, 1] + weights = np.arange(8, 1, -1)**2/7.0 # check 1D case - m, cov = np.polyfit(x,y+err,2,cov=True) + m, cov = np.polyfit(x, y+err, 2, cov=True) est = [3.8571, 0.2857, 1.619] assert_almost_equal(est, m, decimal=4) val0 = [[2.9388, -5.8776, 1.6327], @@ -116,7 +116,7 @@ class TestDocs(TestCase): [1.6327, -4.2449, 2.3220]] assert_almost_equal(val0, cov, decimal=4) - m2, cov2 = np.polyfit(x,y+err,2,w=weights,cov=True) + m2, cov2 = np.polyfit(x, y+err, 2, w=weights, cov=True) assert_almost_equal([4.8927, -1.0177, 1.7768], m2, decimal=4) val = [[ 8.7929, -10.0103, 0.9756], [-10.0103, 13.6134, -1.8178], @@ -124,19 +124,19 @@ class TestDocs(TestCase): assert_almost_equal(val, cov2, decimal=4) # check 2D (n,1) case - y = y[:,np.newaxis] - c = c[:,np.newaxis] - assert_almost_equal(c, np.polyfit(x,y,2)) + y = y[:, np.newaxis] + c = c[:, np.newaxis] + assert_almost_equal(c, np.polyfit(x, y, 2)) # check 2D (n,2) case - yy = np.concatenate((y,y), axis=1) - cc = np.concatenate((c,c), axis=1) - assert_almost_equal(cc, np.polyfit(x,yy,2)) + yy = np.concatenate((y, y), axis=1) + cc = np.concatenate((c, c), axis=1) + assert_almost_equal(cc, np.polyfit(x, yy, 2)) - m, cov = np.polyfit(x,yy + np.array(err)[:,np.newaxis],2,cov=True) - assert_almost_equal(est, m[:,0], decimal=4) - assert_almost_equal(est, m[:,1], decimal=4) - assert_almost_equal(val0, cov[:,:,0], decimal=4) - assert_almost_equal(val0, cov[:,:,1], decimal=4) + m, cov = np.polyfit(x, yy + np.array(err)[:, np.newaxis], 2, cov=True) + assert_almost_equal(est, m[:, 0], decimal=4) + assert_almost_equal(est, m[:, 1], decimal=4) + assert_almost_equal(val0, cov[:,:, 0], decimal=4) + assert_almost_equal(val0, cov[:,:, 1], decimal=4) def test_objects(self): from decimal import Decimal @@ -153,14 +153,14 @@ class TestDocs(TestCase): def test_complex(self): p = np.poly1d([3j, 2j, 1j]) p2 = p.integ() - assert_((p2.coeffs == [1j,1j,1j,0]).all()) + assert_((p2.coeffs == [1j, 1j, 1j, 0]).all()) p2 = p.deriv() - assert_((p2.coeffs == [6j,2j]).all()) + assert_((p2.coeffs == [6j, 2j]).all()) def test_integ_coeffs(self): - p = np.poly1d([3,2,1]) - p2 = p.integ(3, k=[9,7,6]) - assert_((p2.coeffs == [1/4./5.,1/3./4.,1/2./3.,9/1./2.,7,6]).all()) + p = np.poly1d([3, 2, 1]) + p2 = p.integ(3, k=[9, 7, 6]) + assert_((p2.coeffs == [1/4./5., 1/3./4., 1/2./3., 9/1./2., 7, 6]).all()) def test_zero_dims(self): try: diff --git a/numpy/lib/tests/test_recfunctions.py b/numpy/lib/tests/test_recfunctions.py index ef22ca413..b175bcb64 100644 --- a/numpy/lib/tests/test_recfunctions.py +++ b/numpy/lib/tests/test_recfunctions.py @@ -660,13 +660,13 @@ class TestJoinBy2(TestCase): assert_equal(test, control) def test_two_keys_two_vars(self): - a = np.array(list(zip(np.tile([10,11],5),np.repeat(np.arange(5),2), - np.arange(50, 60), np.arange(10,20))), - dtype=[('k', int), ('a', int), ('b', int),('c',int)]) + a = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2), + np.arange(50, 60), np.arange(10, 20))), + dtype=[('k', int), ('a', int), ('b', int), ('c', int)]) - b = np.array(list(zip(np.tile([10,11],5),np.repeat(np.arange(5),2), - np.arange(65, 75), np.arange(0,10))), - dtype=[('k', int), ('a', int), ('b', int), ('c',int)]) + b = np.array(list(zip(np.tile([10, 11], 5), np.repeat(np.arange(5), 2), + np.arange(65, 75), np.arange(0, 10))), + dtype=[('k', int), ('a', int), ('b', int), ('c', int)]) control = np.array([(10, 0, 50, 65, 10, 0), (11, 0, 51, 66, 11, 1), (10, 1, 52, 67, 12, 2), (11, 1, 53, 68, 13, 3), @@ -675,7 +675,7 @@ class TestJoinBy2(TestCase): (10, 4, 58, 73, 18, 8), (11, 4, 59, 74, 19, 9)], dtype=[('k', int), ('a', int), ('b1', int), ('b2', int), ('c1', int), ('c2', int)]) - test = join_by(['a','k'], a, b, r1postfix='1', r2postfix='2', jointype='inner') + test = join_by(['a', 'k'], a, b, r1postfix='1', r2postfix='2', jointype='inner') assert_equal(test.dtype, control.dtype) assert_equal(test, control) diff --git a/numpy/lib/tests/test_regression.py b/numpy/lib/tests/test_regression.py index 1e9bacdf5..67808bd39 100644 --- a/numpy/lib/tests/test_regression.py +++ b/numpy/lib/tests/test_regression.py @@ -12,22 +12,22 @@ rlevel = 1 class TestRegression(TestCase): def test_poly1d(self,level=rlevel): """Ticket #28""" - assert_equal(np.poly1d([1]) - np.poly1d([1,0]), - np.poly1d([-1,1])) + assert_equal(np.poly1d([1]) - np.poly1d([1, 0]), + np.poly1d([-1, 1])) def test_cov_parameters(self,level=rlevel): """Ticket #91""" - x = np.random.random((3,3)) + x = np.random.random((3, 3)) y = x.copy() np.cov(x, rowvar=1) np.cov(y, rowvar=0) - assert_array_equal(x,y) + assert_array_equal(x, y) def test_mem_digitize(self,level=rlevel): """Ticket #95""" for i in range(100): - np.digitize([1,2,3,4],[1,3]) - np.digitize([0,1,2,3,4],[1,3]) + np.digitize([1, 2, 3, 4], [1, 3]) + np.digitize([0, 1, 2, 3, 4], [1, 3]) def test_unique_zero_sized(self,level=rlevel): """Ticket #205""" @@ -36,51 +36,51 @@ class TestRegression(TestCase): def test_mem_vectorise(self, level=rlevel): """Ticket #325""" vt = np.vectorize(lambda *args: args) - vt(np.zeros((1,2,1)), np.zeros((2,1,1)), np.zeros((1,1,2))) - vt(np.zeros((1,2,1)), np.zeros((2,1,1)), np.zeros((1,1,2)), np.zeros((2,2))) + vt(np.zeros((1, 2, 1)), np.zeros((2, 1, 1)), np.zeros((1, 1, 2))) + vt(np.zeros((1, 2, 1)), np.zeros((2, 1, 1)), np.zeros((1, 1, 2)), np.zeros((2, 2))) def test_mgrid_single_element(self, level=rlevel): """Ticket #339""" - assert_array_equal(np.mgrid[0:0:1j],[0]) - assert_array_equal(np.mgrid[0:0],[]) + assert_array_equal(np.mgrid[0:0:1j], [0]) + assert_array_equal(np.mgrid[0:0], []) def test_refcount_vectorize(self, level=rlevel): """Ticket #378""" - def p(x,y): return 123 + def p(x, y): return 123 v = np.vectorize(p) _assert_valid_refcount(v) def test_poly1d_nan_roots(self, level=rlevel): """Ticket #396""" - p = np.poly1d([np.nan,np.nan,1], r=0) - self.assertRaises(np.linalg.LinAlgError,getattr,p,"r") + p = np.poly1d([np.nan, np.nan, 1], r=0) + self.assertRaises(np.linalg.LinAlgError, getattr, p, "r") def test_mem_polymul(self, level=rlevel): """Ticket #448""" - np.polymul([],[1.]) + np.polymul([], [1.]) def test_mem_string_concat(self, level=rlevel): """Ticket #469""" x = np.array([]) - np.append(x,'asdasd\tasdasd') + np.append(x, 'asdasd\tasdasd') def test_poly_div(self, level=rlevel): """Ticket #553""" - u = np.poly1d([1,2,3]) - v = np.poly1d([1,2,3,4,5]) - q,r = np.polydiv(u,v) + u = np.poly1d([1, 2, 3]) + v = np.poly1d([1, 2, 3, 4, 5]) + q, r = np.polydiv(u, v) assert_equal(q*v + r, u) def test_poly_eq(self, level=rlevel): """Ticket #554""" - x = np.poly1d([1,2,3]) - y = np.poly1d([3,4]) + x = np.poly1d([1, 2, 3]) + y = np.poly1d([3, 4]) assert_(x != y) assert_(x == x) def test_mem_insert(self, level=rlevel): """Ticket #572""" - np.lib.place(1,1,1) + np.lib.place(1, 1, 1) def test_polyfit_build(self): """Ticket #628""" @@ -108,16 +108,16 @@ class TestRegression(TestCase): """Make polydiv work for complex types""" msg = "Wrong type, should be complex" x = np.ones(3, dtype=np.complex) - q,r = np.polydiv(x,x) + q, r = np.polydiv(x, x) assert_(q.dtype == np.complex, msg) msg = "Wrong type, should be float" x = np.ones(3, dtype=np.int) - q,r = np.polydiv(x,x) + q, r = np.polydiv(x, x) assert_(q.dtype == np.float, msg) def test_histogramdd_too_many_bins(self) : """Ticket 928.""" - assert_raises(ValueError, np.histogramdd, np.ones((1,10)), bins=2**10) + assert_raises(ValueError, np.histogramdd, np.ones((1, 10)), bins=2**10) def test_polyint_type(self) : """Ticket #944""" @@ -144,20 +144,20 @@ class TestRegression(TestCase): def dp(): n = 3 a = np.ones((n,)*5) - i = np.random.randint(0,n,size=thesize) - a[np.ix_(i,i,i,i,i)] = 0 + i = np.random.randint(0, n, size=thesize) + a[np.ix_(i, i, i, i, i)] = 0 def dp2(): n = 3 a = np.ones((n,)*5) - i = np.random.randint(0,n,size=thesize) - g = a[np.ix_(i,i,i,i,i)] + i = np.random.randint(0, n, size=thesize) + g = a[np.ix_(i, i, i, i, i)] self.assertRaises(ValueError, dp) self.assertRaises(ValueError, dp2) def test_void_coercion(self, level=rlevel): - dt = np.dtype([('a','f4'),('b','i4')]) - x = np.zeros((1,),dt) - assert_(np.r_[x,x].dtype == dt) + dt = np.dtype([('a', 'f4'), ('b', 'i4')]) + x = np.zeros((1,), dt) + assert_(np.r_[x, x].dtype == dt) def test_who_with_0dim_array(self, level=rlevel) : """ticket #1243""" @@ -194,9 +194,9 @@ class TestRegression(TestCase): """Ticket #1676""" from numpy.lib.recfunctions import append_fields F = False - base = np.array([1,2,3], dtype=np.int32) + base = np.array([1, 2, 3], dtype=np.int32) data = np.eye(3).astype(np.int32) - names = ['a','b','c'] + names = ['a', 'b', 'c'] dlist = [np.float64, np.int32, np.int32] try: a = append_fields(base, names, data, dlist) @@ -214,17 +214,17 @@ class TestRegression(TestCase): x = np.loadtxt(StringIO("0 1 2 3"), dtype=dt) assert_equal(x, np.array([((0, 1), (2, 3))], dtype=dt)) - dt = [("a", [("a", 'u1', (1,3)), ("b", 'u1')])] + dt = [("a", [("a", 'u1', (1, 3)), ("b", 'u1')])] x = np.loadtxt(StringIO("0 1 2 3"), dtype=dt) - assert_equal(x, np.array([(((0,1,2), 3),)], dtype=dt)) + assert_equal(x, np.array([(((0, 1, 2), 3),)], dtype=dt)) - dt = [("a", 'u1', (2,2))] + dt = [("a", 'u1', (2, 2))] x = np.loadtxt(StringIO("0 1 2 3"), dtype=dt) assert_equal(x, np.array([(((0, 1), (2, 3)),)], dtype=dt)) - dt = [("a", 'u1', (2,3,2))] + dt = [("a", 'u1', (2, 3, 2))] x = np.loadtxt(StringIO("0 1 2 3 4 5 6 7 8 9 10 11"), dtype=dt) - data = [((((0,1), (2,3), (4,5)), ((6,7), (8,9), (10,11))),)] + data = [((((0, 1), (2, 3), (4, 5)), ((6, 7), (8, 9), (10, 11))),)] assert_equal(x, np.array(data, dtype=dt)) def test_nansum_with_boolean(self): diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py index a92ddde83..157e1beb3 100644 --- a/numpy/lib/tests/test_shape_base.py +++ b/numpy/lib/tests/test_shape_base.py @@ -7,133 +7,133 @@ from numpy import matrix, asmatrix class TestApplyAlongAxis(TestCase): def test_simple(self): - a = ones((20,10),'d') - assert_array_equal(apply_along_axis(len,0,a),len(a)*ones(shape(a)[1])) + a = ones((20, 10), 'd') + assert_array_equal(apply_along_axis(len, 0, a), len(a)*ones(shape(a)[1])) def test_simple101(self,level=11): - a = ones((10,101),'d') - assert_array_equal(apply_along_axis(len,0,a),len(a)*ones(shape(a)[1])) + a = ones((10, 101), 'd') + assert_array_equal(apply_along_axis(len, 0, a), len(a)*ones(shape(a)[1])) def test_3d(self): - a = arange(27).reshape((3,3,3)) - assert_array_equal(apply_along_axis(sum,0,a), - [[27,30,33],[36,39,42],[45,48,51]]) + a = arange(27).reshape((3, 3, 3)) + assert_array_equal(apply_along_axis(sum, 0, a), + [[27, 30, 33], [36, 39, 42], [45, 48, 51]]) class TestApplyOverAxes(TestCase): def test_simple(self): - a = arange(24).reshape(2,3,4) - aoa_a = apply_over_axes(sum, a, [0,2]) - assert_array_equal(aoa_a, array([[[60],[92],[124]]])) + a = arange(24).reshape(2, 3, 4) + aoa_a = apply_over_axes(sum, a, [0, 2]) + assert_array_equal(aoa_a, array([[[60], [92], [124]]])) class TestArraySplit(TestCase): def test_integer_0_split(self): a = arange(10) try: - res = array_split(a,0) + res = array_split(a, 0) assert_(0) # it should have thrown a value error except ValueError: pass def test_integer_split(self): a = arange(10) - res = array_split(a,1) + res = array_split(a, 1) desired = [arange(10)] - compare_results(res,desired) - - res = array_split(a,2) - desired = [arange(5),arange(5,10)] - compare_results(res,desired) - - res = array_split(a,3) - desired = [arange(4),arange(4,7),arange(7,10)] - compare_results(res,desired) - - res = array_split(a,4) - desired = [arange(3),arange(3,6),arange(6,8),arange(8,10)] - compare_results(res,desired) - - res = array_split(a,5) - desired = [arange(2),arange(2,4),arange(4,6),arange(6,8),arange(8,10)] - compare_results(res,desired) - - res = array_split(a,6) - desired = [arange(2),arange(2,4),arange(4,6),arange(6,8),arange(8,9), - arange(9,10)] - compare_results(res,desired) - - res = array_split(a,7) - desired = [arange(2),arange(2,4),arange(4,6),arange(6,7),arange(7,8), - arange(8,9), arange(9,10)] - compare_results(res,desired) - - res = array_split(a,8) - desired = [arange(2),arange(2,4),arange(4,5),arange(5,6),arange(6,7), - arange(7,8), arange(8,9), arange(9,10)] - compare_results(res,desired) - - res = array_split(a,9) - desired = [arange(2),arange(2,3),arange(3,4),arange(4,5),arange(5,6), - arange(6,7), arange(7,8), arange(8,9), arange(9,10)] - compare_results(res,desired) - - res = array_split(a,10) - desired = [arange(1),arange(1,2),arange(2,3),arange(3,4), - arange(4,5),arange(5,6), arange(6,7), arange(7,8), - arange(8,9), arange(9,10)] - compare_results(res,desired) - - res = array_split(a,11) - desired = [arange(1),arange(1,2),arange(2,3),arange(3,4), - arange(4,5),arange(5,6), arange(6,7), arange(7,8), - arange(8,9), arange(9,10),array([])] - compare_results(res,desired) + compare_results(res, desired) + + res = array_split(a, 2) + desired = [arange(5), arange(5, 10)] + compare_results(res, desired) + + res = array_split(a, 3) + desired = [arange(4), arange(4, 7), arange(7, 10)] + compare_results(res, desired) + + res = array_split(a, 4) + desired = [arange(3), arange(3, 6), arange(6, 8), arange(8, 10)] + compare_results(res, desired) + + res = array_split(a, 5) + desired = [arange(2), arange(2, 4), arange(4, 6), arange(6, 8), arange(8, 10)] + compare_results(res, desired) + + res = array_split(a, 6) + desired = [arange(2), arange(2, 4), arange(4, 6), arange(6, 8), arange(8, 9), + arange(9, 10)] + compare_results(res, desired) + + res = array_split(a, 7) + desired = [arange(2), arange(2, 4), arange(4, 6), arange(6, 7), arange(7, 8), + arange(8, 9), arange(9, 10)] + compare_results(res, desired) + + res = array_split(a, 8) + desired = [arange(2), arange(2, 4), arange(4, 5), arange(5, 6), arange(6, 7), + arange(7, 8), arange(8, 9), arange(9, 10)] + compare_results(res, desired) + + res = array_split(a, 9) + desired = [arange(2), arange(2, 3), arange(3, 4), arange(4, 5), arange(5, 6), + arange(6, 7), arange(7, 8), arange(8, 9), arange(9, 10)] + compare_results(res, desired) + + res = array_split(a, 10) + desired = [arange(1), arange(1, 2), arange(2, 3), arange(3, 4), + arange(4, 5), arange(5, 6), arange(6, 7), arange(7, 8), + arange(8, 9), arange(9, 10)] + compare_results(res, desired) + + res = array_split(a, 11) + desired = [arange(1), arange(1, 2), arange(2, 3), arange(3, 4), + arange(4, 5), arange(5, 6), arange(6, 7), arange(7, 8), + arange(8, 9), arange(9, 10), array([])] + compare_results(res, desired) def test_integer_split_2D_rows(self): - a = array([arange(10),arange(10)]) - res = array_split(a,3,axis=0) - desired = [array([arange(10)]),array([arange(10)]),array([])] - compare_results(res,desired) + a = array([arange(10), arange(10)]) + res = array_split(a, 3, axis=0) + desired = [array([arange(10)]), array([arange(10)]), array([])] + compare_results(res, desired) def test_integer_split_2D_cols(self): - a = array([arange(10),arange(10)]) - res = array_split(a,3,axis=-1) - desired = [array([arange(4),arange(4)]), - array([arange(4,7),arange(4,7)]), - array([arange(7,10),arange(7,10)])] - compare_results(res,desired) + a = array([arange(10), arange(10)]) + res = array_split(a, 3, axis=-1) + desired = [array([arange(4), arange(4)]), + array([arange(4, 7), arange(4, 7)]), + array([arange(7, 10), arange(7, 10)])] + compare_results(res, desired) def test_integer_split_2D_default(self): """ This will fail if we change default axis """ - a = array([arange(10),arange(10)]) - res = array_split(a,3) - desired = [array([arange(10)]),array([arange(10)]),array([])] - compare_results(res,desired) + a = array([arange(10), arange(10)]) + res = array_split(a, 3) + desired = [array([arange(10)]), array([arange(10)]), array([])] + compare_results(res, desired) #perhaps should check higher dimensions def test_index_split_simple(self): a = arange(10) - indices = [1,5,7] - res = array_split(a,indices,axis=-1) - desired = [arange(0,1),arange(1,5),arange(5,7),arange(7,10)] - compare_results(res,desired) + indices = [1, 5, 7] + res = array_split(a, indices, axis=-1) + desired = [arange(0, 1), arange(1, 5), arange(5, 7), arange(7, 10)] + compare_results(res, desired) def test_index_split_low_bound(self): a = arange(10) - indices = [0,5,7] - res = array_split(a,indices,axis=-1) - desired = [array([]),arange(0,5),arange(5,7),arange(7,10)] - compare_results(res,desired) + indices = [0, 5, 7] + res = array_split(a, indices, axis=-1) + desired = [array([]), arange(0, 5), arange(5, 7), arange(7, 10)] + compare_results(res, desired) def test_index_split_high_bound(self): a = arange(10) - indices = [0,5,7,10,12] - res = array_split(a,indices,axis=-1) - desired = [array([]),arange(0,5),arange(5,7),arange(7,10), - array([]),array([])] - compare_results(res,desired) + indices = [0, 5, 7, 10, 12] + res = array_split(a, indices, axis=-1) + desired = [array([]), arange(0, 5), arange(5, 7), arange(7, 10), + array([]), array([])] + compare_results(res, desired) class TestSplit(TestCase): @@ -143,14 +143,14 @@ class TestSplit(TestCase): *""" def test_equal_split(self): a = arange(10) - res = split(a,2) - desired = [arange(5),arange(5,10)] - compare_results(res,desired) + res = split(a, 2) + desired = [arange(5), arange(5, 10)] + compare_results(res, desired) def test_unequal_split(self): a = arange(10) try: - res = split(a,3) + res = split(a, 3) assert_(0) # should raise an error except ValueError: pass @@ -159,27 +159,27 @@ class TestSplit(TestCase): class TestDstack(TestCase): def test_0D_array(self): a = array(1); b = array(2); - res=dstack([a,b]) - desired = array([[[1,2]]]) - assert_array_equal(res,desired) + res=dstack([a, b]) + desired = array([[[1, 2]]]) + assert_array_equal(res, desired) def test_1D_array(self): a = array([1]); b = array([2]); - res=dstack([a,b]) - desired = array([[[1,2]]]) - assert_array_equal(res,desired) + res=dstack([a, b]) + desired = array([[[1, 2]]]) + assert_array_equal(res, desired) def test_2D_array(self): - a = array([[1],[2]]); b = array([[1],[2]]); - res=dstack([a,b]) - desired = array([[[1,1]],[[2,2,]]]) - assert_array_equal(res,desired) + a = array([[1], [2]]); b = array([[1], [2]]); + res=dstack([a, b]) + desired = array([[[1, 1]], [[2, 2,]]]) + assert_array_equal(res, desired) def test_2D_array2(self): - a = array([1,2]); b = array([1,2]); - res=dstack([a,b]) - desired = array([[[1,1],[2,2]]]) - assert_array_equal(res,desired) + a = array([1, 2]); b = array([1, 2]); + res=dstack([a, b]) + desired = array([[[1, 1], [2, 2]]]) + assert_array_equal(res, desired) """ array_split has more comprehensive test of splitting. only do simple test on hsplit, vsplit, and dsplit @@ -190,75 +190,75 @@ class TestHsplit(TestCase): def test_0D_array(self): a= array(1) try: - hsplit(a,2) + hsplit(a, 2) assert_(0) except ValueError: pass def test_1D_array(self): - a= array([1,2,3,4]) - res = hsplit(a,2) - desired = [array([1,2]),array([3,4])] - compare_results(res,desired) + a= array([1, 2, 3, 4]) + res = hsplit(a, 2) + desired = [array([1, 2]), array([3, 4])] + compare_results(res, desired) def test_2D_array(self): - a= array([[1,2,3,4], - [1,2,3,4]]) - res = hsplit(a,2) - desired = [array([[1,2],[1,2]]),array([[3,4],[3,4]])] - compare_results(res,desired) + a= array([[1, 2, 3, 4], + [1, 2, 3, 4]]) + res = hsplit(a, 2) + desired = [array([[1, 2], [1, 2]]), array([[3, 4], [3, 4]])] + compare_results(res, desired) class TestVsplit(TestCase): """ only testing for integer splits. """ def test_1D_array(self): - a= array([1,2,3,4]) + a= array([1, 2, 3, 4]) try: - vsplit(a,2) + vsplit(a, 2) assert_(0) except ValueError: pass def test_2D_array(self): - a= array([[1,2,3,4], - [1,2,3,4]]) - res = vsplit(a,2) - desired = [array([[1,2,3,4]]),array([[1,2,3,4]])] - compare_results(res,desired) + a= array([[1, 2, 3, 4], + [1, 2, 3, 4]]) + res = vsplit(a, 2) + desired = [array([[1, 2, 3, 4]]), array([[1, 2, 3, 4]])] + compare_results(res, desired) class TestDsplit(TestCase): """ only testing for integer splits. """ def test_2D_array(self): - a= array([[1,2,3,4], - [1,2,3,4]]) + a= array([[1, 2, 3, 4], + [1, 2, 3, 4]]) try: - dsplit(a,2) + dsplit(a, 2) assert_(0) except ValueError: pass def test_3D_array(self): - a= array([[[1,2,3,4], - [1,2,3,4]], - [[1,2,3,4], - [1,2,3,4]]]) - res = dsplit(a,2) - desired = [array([[[1,2],[1,2]],[[1,2],[1,2]]]), - array([[[3,4],[3,4]],[[3,4],[3,4]]])] - compare_results(res,desired) + a= array([[[1, 2, 3, 4], + [1, 2, 3, 4]], + [[1, 2, 3, 4], + [1, 2, 3, 4]]]) + res = dsplit(a, 2) + desired = [array([[[1, 2], [1, 2]], [[1, 2], [1, 2]]]), + array([[[3, 4], [3, 4]], [[3, 4], [3, 4]]])] + compare_results(res, desired) class TestSqueeze(TestCase): def test_basic(self): - a = rand(20,10,10,1,1) - b = rand(20,1,10,1,20) - c = rand(1,1,20,10) - assert_array_equal(squeeze(a),reshape(a,(20,10,10))) - assert_array_equal(squeeze(b),reshape(b,(20,10,20))) - assert_array_equal(squeeze(c),reshape(c,(20,10))) + a = rand(20, 10, 10, 1, 1) + b = rand(20, 1, 10, 1, 20) + c = rand(1, 1, 20, 10) + assert_array_equal(squeeze(a), reshape(a, (20, 10, 10))) + assert_array_equal(squeeze(b), reshape(b, (20, 10, 20))) + assert_array_equal(squeeze(c), reshape(c, (20, 10))) # Squeezing to 0-dim should still give an ndarray a = [[[1.5]]] @@ -270,44 +270,44 @@ class TestSqueeze(TestCase): class TestKron(TestCase): def test_return_type(self): - a = ones([2,2]) + a = ones([2, 2]) m = asmatrix(a) - assert_equal(type(kron(a,a)), ndarray) - assert_equal(type(kron(m,m)), matrix) - assert_equal(type(kron(a,m)), matrix) - assert_equal(type(kron(m,a)), matrix) + assert_equal(type(kron(a, a)), ndarray) + assert_equal(type(kron(m, m)), matrix) + assert_equal(type(kron(a, m)), matrix) + assert_equal(type(kron(m, a)), matrix) class myarray(ndarray): __array_priority__ = 0.0 ma = myarray(a.shape, a.dtype, a.data) - assert_equal(type(kron(a,a)), ndarray) - assert_equal(type(kron(ma,ma)), myarray) - assert_equal(type(kron(a,ma)), ndarray) - assert_equal(type(kron(ma,a)), myarray) + assert_equal(type(kron(a, a)), ndarray) + assert_equal(type(kron(ma, ma)), myarray) + assert_equal(type(kron(a, ma)), ndarray) + assert_equal(type(kron(ma, a)), myarray) class TestTile(TestCase): def test_basic(self): - a = array([0,1,2]) - b = [[1,2],[3,4]] - assert_equal(tile(a,2), [0,1,2,0,1,2]) - assert_equal(tile(a,(2,2)), [[0,1,2,0,1,2],[0,1,2,0,1,2]]) - assert_equal(tile(a,(1,2)), [[0,1,2,0,1,2]]) - assert_equal(tile(b, 2), [[1,2,1,2],[3,4,3,4]]) - assert_equal(tile(b,(2,1)),[[1,2],[3,4],[1,2],[3,4]]) - assert_equal(tile(b,(2,2)),[[1,2,1,2],[3,4,3,4], - [1,2,1,2],[3,4,3,4]]) + a = array([0, 1, 2]) + b = [[1, 2], [3, 4]] + assert_equal(tile(a, 2), [0, 1, 2, 0, 1, 2]) + assert_equal(tile(a, (2, 2)), [[0, 1, 2, 0, 1, 2], [0, 1, 2, 0, 1, 2]]) + assert_equal(tile(a, (1, 2)), [[0, 1, 2, 0, 1, 2]]) + assert_equal(tile(b, 2), [[1, 2, 1, 2], [3, 4, 3, 4]]) + assert_equal(tile(b, (2, 1)), [[1, 2], [3, 4], [1, 2], [3, 4]]) + assert_equal(tile(b, (2, 2)), [[1, 2, 1, 2], [3, 4, 3, 4], + [1, 2, 1, 2], [3, 4, 3, 4]]) def test_empty(self): a = array([[[]]]) - d = tile(a,(3,2,5)).shape - assert_equal(d,(3,2,0)) + d = tile(a, (3, 2, 5)).shape + assert_equal(d, (3, 2, 0)) def test_kroncompare(self): import numpy.random as nr - reps=[(2,),(1,2),(2,1),(2,2),(2,3,2),(3,2)] - shape=[(3,),(2,3),(3,4,3),(3,2,3),(4,3,2,4),(2,2)] + reps=[(2,), (1, 2), (2, 1), (2, 2), (2, 3, 2), (3, 2)] + shape=[(3,), (2, 3), (3, 4, 3), (3, 2, 3), (4, 3, 2, 4), (2, 2)] for s in shape: - b = nr.randint(0,10,size=s) + b = nr.randint(0, 10, size=s) for r in reps: a = ones(r, b.dtype) large = tile(b, r) @@ -331,9 +331,9 @@ class TestMayShareMemory(TestCase): # Utility -def compare_results(res,desired): +def compare_results(res, desired): for i in range(len(desired)): - assert_array_equal(res[i],desired[i]) + assert_array_equal(res[i], desired[i]) if __name__ == "__main__": diff --git a/numpy/lib/tests/test_stride_tricks.py b/numpy/lib/tests/test_stride_tricks.py index f815b247f..5d06e0a8c 100644 --- a/numpy/lib/tests/test_stride_tricks.py +++ b/numpy/lib/tests/test_stride_tricks.py @@ -52,10 +52,10 @@ def test_same(): assert_array_equal(y, by) def test_one_off(): - x = np.array([[1,2,3]]) - y = np.array([[1],[2],[3]]) + x = np.array([[1, 2, 3]]) + y = np.array([[1], [2], [3]]) bx, by = broadcast_arrays(x, y) - bx0 = np.array([[1,2,3],[1,2,3],[1,2,3]]) + bx0 = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3]]) by0 = bx0.T assert_array_equal(bx0, bx) assert_array_equal(by0, by) @@ -67,13 +67,13 @@ def test_same_input_shapes(): (), (1,), (3,), - (0,1), - (0,3), - (1,0), - (3,0), - (1,3), - (3,1), - (3,3), + (0, 1), + (0, 3), + (1, 0), + (3, 0), + (1, 3), + (3, 1), + (3, 3), ] for shape in data: input_shapes = [shape] @@ -92,18 +92,18 @@ def test_two_compatible_by_ones_input_shapes(): """ data = [ [[(1,), (3,)], (3,)], - [[(1,3), (3,3)], (3,3)], - [[(3,1), (3,3)], (3,3)], - [[(1,3), (3,1)], (3,3)], - [[(1,1), (3,3)], (3,3)], - [[(1,1), (1,3)], (1,3)], - [[(1,1), (3,1)], (3,1)], - [[(1,0), (0,0)], (0,0)], - [[(0,1), (0,0)], (0,0)], - [[(1,0), (0,1)], (0,0)], - [[(1,1), (0,0)], (0,0)], - [[(1,1), (1,0)], (1,0)], - [[(1,1), (0,1)], (0,1)], + [[(1, 3), (3, 3)], (3, 3)], + [[(3, 1), (3, 3)], (3, 3)], + [[(1, 3), (3, 1)], (3, 3)], + [[(1, 1), (3, 3)], (3, 3)], + [[(1, 1), (1, 3)], (1, 3)], + [[(1, 1), (3, 1)], (3, 1)], + [[(1, 0), (0, 0)], (0, 0)], + [[(0, 1), (0, 0)], (0, 0)], + [[(1, 0), (0, 1)], (0, 0)], + [[(1, 1), (0, 0)], (0, 0)], + [[(1, 1), (1, 0)], (1, 0)], + [[(1, 1), (0, 1)], (0, 1)], ] for input_shapes, expected_shape in data: assert_shapes_correct(input_shapes, expected_shape) @@ -116,25 +116,25 @@ def test_two_compatible_by_prepending_ones_input_shapes(): """ data = [ [[(), (3,)], (3,)], - [[(3,), (3,3)], (3,3)], - [[(3,), (3,1)], (3,3)], - [[(1,), (3,3)], (3,3)], - [[(), (3,3)], (3,3)], - [[(1,1), (3,)], (1,3)], - [[(1,), (3,1)], (3,1)], - [[(1,), (1,3)], (1,3)], - [[(), (1,3)], (1,3)], - [[(), (3,1)], (3,1)], + [[(3,), (3, 3)], (3, 3)], + [[(3,), (3, 1)], (3, 3)], + [[(1,), (3, 3)], (3, 3)], + [[(), (3, 3)], (3, 3)], + [[(1, 1), (3,)], (1, 3)], + [[(1,), (3, 1)], (3, 1)], + [[(1,), (1, 3)], (1, 3)], + [[(), (1, 3)], (1, 3)], + [[(), (3, 1)], (3, 1)], [[(), (0,)], (0,)], - [[(0,), (0,0)], (0,0)], - [[(0,), (0,1)], (0,0)], - [[(1,), (0,0)], (0,0)], - [[(), (0,0)], (0,0)], - [[(1,1), (0,)], (1,0)], - [[(1,), (0,1)], (0,1)], - [[(1,), (1,0)], (1,0)], - [[(), (1,0)], (1,0)], - [[(), (0,1)], (0,1)], + [[(0,), (0, 0)], (0, 0)], + [[(0,), (0, 1)], (0, 0)], + [[(1,), (0, 0)], (0, 0)], + [[(), (0, 0)], (0, 0)], + [[(1, 1), (0,)], (1, 0)], + [[(1,), (0, 1)], (0, 1)], + [[(1,), (1, 0)], (1, 0)], + [[(), (1, 0)], (1, 0)], + [[(), (0, 1)], (0, 1)], ] for input_shapes, expected_shape in data: assert_shapes_correct(input_shapes, expected_shape) @@ -146,9 +146,9 @@ def test_incompatible_shapes_raise_valueerror(): """ data = [ [(3,), (4,)], - [(2,3), (2,)], + [(2, 3), (2,)], [(3,), (3,), (4,)], - [(1,3,4), (2,3,3)], + [(1, 3, 4), (2, 3, 3)], ] for input_shapes in data: assert_incompatible_shapes_raise(input_shapes) @@ -160,38 +160,38 @@ def test_same_as_ufunc(): """ data = [ [[(1,), (3,)], (3,)], - [[(1,3), (3,3)], (3,3)], - [[(3,1), (3,3)], (3,3)], - [[(1,3), (3,1)], (3,3)], - [[(1,1), (3,3)], (3,3)], - [[(1,1), (1,3)], (1,3)], - [[(1,1), (3,1)], (3,1)], - [[(1,0), (0,0)], (0,0)], - [[(0,1), (0,0)], (0,0)], - [[(1,0), (0,1)], (0,0)], - [[(1,1), (0,0)], (0,0)], - [[(1,1), (1,0)], (1,0)], - [[(1,1), (0,1)], (0,1)], + [[(1, 3), (3, 3)], (3, 3)], + [[(3, 1), (3, 3)], (3, 3)], + [[(1, 3), (3, 1)], (3, 3)], + [[(1, 1), (3, 3)], (3, 3)], + [[(1, 1), (1, 3)], (1, 3)], + [[(1, 1), (3, 1)], (3, 1)], + [[(1, 0), (0, 0)], (0, 0)], + [[(0, 1), (0, 0)], (0, 0)], + [[(1, 0), (0, 1)], (0, 0)], + [[(1, 1), (0, 0)], (0, 0)], + [[(1, 1), (1, 0)], (1, 0)], + [[(1, 1), (0, 1)], (0, 1)], [[(), (3,)], (3,)], - [[(3,), (3,3)], (3,3)], - [[(3,), (3,1)], (3,3)], - [[(1,), (3,3)], (3,3)], - [[(), (3,3)], (3,3)], - [[(1,1), (3,)], (1,3)], - [[(1,), (3,1)], (3,1)], - [[(1,), (1,3)], (1,3)], - [[(), (1,3)], (1,3)], - [[(), (3,1)], (3,1)], + [[(3,), (3, 3)], (3, 3)], + [[(3,), (3, 1)], (3, 3)], + [[(1,), (3, 3)], (3, 3)], + [[(), (3, 3)], (3, 3)], + [[(1, 1), (3,)], (1, 3)], + [[(1,), (3, 1)], (3, 1)], + [[(1,), (1, 3)], (1, 3)], + [[(), (1, 3)], (1, 3)], + [[(), (3, 1)], (3, 1)], [[(), (0,)], (0,)], - [[(0,), (0,0)], (0,0)], - [[(0,), (0,1)], (0,0)], - [[(1,), (0,0)], (0,0)], - [[(), (0,0)], (0,0)], - [[(1,1), (0,)], (1,0)], - [[(1,), (0,1)], (0,1)], - [[(1,), (1,0)], (1,0)], - [[(), (1,0)], (1,0)], - [[(), (0,1)], (0,1)], + [[(0,), (0, 0)], (0, 0)], + [[(0,), (0, 1)], (0, 0)], + [[(1,), (0, 0)], (0, 0)], + [[(), (0, 0)], (0, 0)], + [[(1, 1), (0,)], (1, 0)], + [[(1,), (0, 1)], (0, 1)], + [[(1,), (1, 0)], (1, 0)], + [[(), (1, 0)], (1, 0)], + [[(), (0, 1)], (0, 1)], ] for input_shapes, expected_shape in data: assert_same_as_ufunc(input_shapes[0], input_shapes[1], diff --git a/numpy/lib/tests/test_twodim_base.py b/numpy/lib/tests/test_twodim_base.py index 7e590c1db..4ec5c34a2 100644 --- a/numpy/lib/tests/test_twodim_base.py +++ b/numpy/lib/tests/test_twodim_base.py @@ -14,46 +14,46 @@ from numpy.compat import asbytes, asbytes_nested def get_mat(n): data = arange(n) - data = add.outer(data,data) + data = add.outer(data, data) return data class TestEye(TestCase): def test_basic(self): - assert_equal(eye(4),array([[1,0,0,0], - [0,1,0,0], - [0,0,1,0], - [0,0,0,1]])) - assert_equal(eye(4,dtype='f'),array([[1,0,0,0], - [0,1,0,0], - [0,0,1,0], - [0,0,0,1]],'f')) - assert_equal(eye(3) == 1, eye(3,dtype=bool)) + assert_equal(eye(4), array([[1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, 1, 0], + [0, 0, 0, 1]])) + assert_equal(eye(4, dtype='f'), array([[1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, 1, 0], + [0, 0, 0, 1]], 'f')) + assert_equal(eye(3) == 1, eye(3, dtype=bool)) def test_diag(self): - assert_equal(eye(4,k=1),array([[0,1,0,0], - [0,0,1,0], - [0,0,0,1], - [0,0,0,0]])) - assert_equal(eye(4,k=-1),array([[0,0,0,0], - [1,0,0,0], - [0,1,0,0], - [0,0,1,0]])) + assert_equal(eye(4, k=1), array([[0, 1, 0, 0], + [0, 0, 1, 0], + [0, 0, 0, 1], + [0, 0, 0, 0]])) + assert_equal(eye(4, k=-1), array([[0, 0, 0, 0], + [1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, 1, 0]])) def test_2d(self): - assert_equal(eye(4,3),array([[1,0,0], - [0,1,0], - [0,0,1], - [0,0,0]])) - assert_equal(eye(3,4),array([[1,0,0,0], - [0,1,0,0], - [0,0,1,0]])) + assert_equal(eye(4, 3), array([[1, 0, 0], + [0, 1, 0], + [0, 0, 1], + [0, 0, 0]])) + assert_equal(eye(3, 4), array([[1, 0, 0, 0], + [0, 1, 0, 0], + [0, 0, 1, 0]])) def test_diag2d(self): - assert_equal(eye(3,4,k=2),array([[0,0,1,0], - [0,0,0,1], - [0,0,0,0]])) - assert_equal(eye(4,3,k=-2),array([[0,0,0], - [0,0,0], - [1,0,0], - [0,1,0]])) + assert_equal(eye(3, 4, k=2), array([[0, 0, 1, 0], + [0, 0, 0, 1], + [0, 0, 0, 0]])) + assert_equal(eye(4, 3, k=-2), array([[0, 0, 0], + [0, 0, 0], + [1, 0, 0], + [0, 1, 0]])) def test_eye_bounds(self): assert_equal(eye(2, 2, 1), [[0, 1], [0, 0]]) @@ -93,7 +93,7 @@ class TestDiag(TestCase): vals = (100 * get_mat(5) + 1).astype('l') b = zeros((5,)) for k in range(5): - b[k] = vals[k,k] + b[k] = vals[k, k] assert_equal(diag(vals), b) b = b * 0 for k in range(3): @@ -123,61 +123,61 @@ class TestFliplr(TestCase): def test_basic(self): self.assertRaises(ValueError, fliplr, ones(4)) a = get_mat(4) - b = a[:,::-1] - assert_equal(fliplr(a),b) - a = [[0,1,2], - [3,4,5]] - b = [[2,1,0], - [5,4,3]] - assert_equal(fliplr(a),b) + b = a[:, ::-1] + assert_equal(fliplr(a), b) + a = [[0, 1, 2], + [3, 4, 5]] + b = [[2, 1, 0], + [5, 4, 3]] + assert_equal(fliplr(a), b) class TestFlipud(TestCase): def test_basic(self): a = get_mat(4) b = a[::-1,:] - assert_equal(flipud(a),b) - a = [[0,1,2], - [3,4,5]] - b = [[3,4,5], - [0,1,2]] - assert_equal(flipud(a),b) + assert_equal(flipud(a), b) + a = [[0, 1, 2], + [3, 4, 5]] + b = [[3, 4, 5], + [0, 1, 2]] + assert_equal(flipud(a), b) class TestRot90(TestCase): def test_basic(self): self.assertRaises(ValueError, rot90, ones(4)) - a = [[0,1,2], - [3,4,5]] - b1 = [[2,5], - [1,4], - [0,3]] - b2 = [[5,4,3], - [2,1,0]] - b3 = [[3,0], - [4,1], - [5,2]] - b4 = [[0,1,2], - [3,4,5]] - - for k in range(-3,13,4): - assert_equal(rot90(a,k=k),b1) - for k in range(-2,13,4): - assert_equal(rot90(a,k=k),b2) - for k in range(-1,13,4): - assert_equal(rot90(a,k=k),b3) - for k in range(0,13,4): - assert_equal(rot90(a,k=k),b4) + a = [[0, 1, 2], + [3, 4, 5]] + b1 = [[2, 5], + [1, 4], + [0, 3]] + b2 = [[5, 4, 3], + [2, 1, 0]] + b3 = [[3, 0], + [4, 1], + [5, 2]] + b4 = [[0, 1, 2], + [3, 4, 5]] + + for k in range(-3, 13, 4): + assert_equal(rot90(a, k=k), b1) + for k in range(-2, 13, 4): + assert_equal(rot90(a, k=k), b2) + for k in range(-1, 13, 4): + assert_equal(rot90(a, k=k), b3) + for k in range(0, 13, 4): + assert_equal(rot90(a, k=k), b4) def test_axes(self): - a = ones((50,40,3)) - assert_equal(rot90(a).shape,(40,50,3)) + a = ones((50, 40, 3)) + assert_equal(rot90(a).shape, (40, 50, 3)) class TestHistogram2d(TestCase): def test_simple(self): x = array([ 0.41702200, 0.72032449, 0.00011437481, 0.302332573, 0.146755891]) y = array([ 0.09233859, 0.18626021, 0.34556073, 0.39676747, 0.53881673]) - xedges = np.linspace(0,1,10) - yedges = np.linspace(0,1,10) + xedges = np.linspace(0, 1, 10) + yedges = np.linspace(0, 1, 10) H = histogram2d(x, y, (xedges, yedges))[0] answer = array([[0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0], @@ -191,40 +191,40 @@ class TestHistogram2d(TestCase): assert_array_equal(H.T, answer) H = histogram2d(x, y, xedges)[0] assert_array_equal(H.T, answer) - H,xedges,yedges = histogram2d(list(range(10)),list(range(10))) - assert_array_equal(H, eye(10,10)) - assert_array_equal(xedges, np.linspace(0,9,11)) - assert_array_equal(yedges, np.linspace(0,9,11)) + H, xedges, yedges = histogram2d(list(range(10)), list(range(10))) + assert_array_equal(H, eye(10, 10)) + assert_array_equal(xedges, np.linspace(0, 9, 11)) + assert_array_equal(yedges, np.linspace(0, 9, 11)) def test_asym(self): x = array([1, 1, 2, 3, 4, 4, 4, 5]) y = array([1, 3, 2, 0, 1, 2, 3, 4]) - H, xed, yed = histogram2d(x,y, (6, 5), range = [[0,6],[0,5]], normed=True) - answer = array([[0.,0,0,0,0], - [0,1,0,1,0], - [0,0,1,0,0], - [1,0,0,0,0], - [0,1,1,1,0], - [0,0,0,0,1]]) + H, xed, yed = histogram2d(x, y, (6, 5), range = [[0, 6], [0, 5]], normed=True) + answer = array([[0., 0, 0, 0, 0], + [0, 1, 0, 1, 0], + [0, 0, 1, 0, 0], + [1, 0, 0, 0, 0], + [0, 1, 1, 1, 0], + [0, 0, 0, 0, 1]]) assert_array_almost_equal(H, answer/8., 3) - assert_array_equal(xed, np.linspace(0,6,7)) - assert_array_equal(yed, np.linspace(0,5,6)) + assert_array_equal(xed, np.linspace(0, 6, 7)) + assert_array_equal(yed, np.linspace(0, 5, 6)) def test_norm(self): - x = array([1,2,3,1,2,3,1,2,3]) - y = array([1,1,1,2,2,2,3,3,3]) - H, xed, yed = histogram2d(x,y,[[1,2,3,5], [1,2,3,5]], normed=True) - answer=array([[1,1,.5], - [1,1,.5], - [.5,.5,.25]])/9. + x = array([1, 2, 3, 1, 2, 3, 1, 2, 3]) + y = array([1, 1, 1, 2, 2, 2, 3, 3, 3]) + H, xed, yed = histogram2d(x, y, [[1, 2, 3, 5], [1, 2, 3, 5]], normed=True) + answer=array([[1, 1, .5], + [1, 1, .5], + [.5, .5, .25]])/9. assert_array_almost_equal(H, answer, 3) def test_all_outliers(self): r = rand(100)+1. - H, xed, yed = histogram2d(r, r, (4, 5), range=([0,1], [0,1])) + H, xed, yed = histogram2d(r, r, (4, 5), range=([0, 1], [0, 1])) assert_array_equal(H, 0) def test_empty(self): - a, edge1, edge2 = histogram2d([],[], bins=([0,1],[0,1])) + a, edge1, edge2 = histogram2d([], [], bins=([0, 1], [0, 1])) assert_array_max_ulp(a, array([[ 0.]])) a, edge1, edge2 = histogram2d([], [], bins=4) @@ -233,11 +233,11 @@ class TestHistogram2d(TestCase): class TestTri(TestCase): def test_dtype(self): - out = array([[1,0,0], - [1,1,0], - [1,1,1]]) - assert_array_equal(tri(3),out) - assert_array_equal(tri(3,dtype=bool),out.astype(bool)) + out = array([[1, 0, 0], + [1, 1, 0], + [1, 1, 1]]) + assert_array_equal(tri(3), out) + assert_array_equal(tri(3, dtype=bool), out.astype(bool)) def test_tril_triu(): @@ -327,15 +327,15 @@ class TestTriuIndices(object): class TestTrilIndicesFrom(object): def test_exceptions(self): assert_raises(ValueError, tril_indices_from, np.ones((2,))) - assert_raises(ValueError, tril_indices_from, np.ones((2,2,2))) - assert_raises(ValueError, tril_indices_from, np.ones((2,3))) + assert_raises(ValueError, tril_indices_from, np.ones((2, 2, 2))) + assert_raises(ValueError, tril_indices_from, np.ones((2, 3))) class TestTriuIndicesFrom(object): def test_exceptions(self): assert_raises(ValueError, triu_indices_from, np.ones((2,))) - assert_raises(ValueError, triu_indices_from, np.ones((2,2,2))) - assert_raises(ValueError, triu_indices_from, np.ones((2,3))) + assert_raises(ValueError, triu_indices_from, np.ones((2, 2, 2))) + assert_raises(ValueError, triu_indices_from, np.ones((2, 3))) if __name__ == "__main__": diff --git a/numpy/lib/tests/test_type_check.py b/numpy/lib/tests/test_type_check.py index 8b01a974a..3ca093e16 100644 --- a/numpy/lib/tests/test_type_check.py +++ b/numpy/lib/tests/test_type_check.py @@ -20,11 +20,11 @@ def assert_all(x): class TestCommonType(TestCase): def test_basic(self): - ai32 = array([[1,2],[3,4]], dtype=int32) - af32 = array([[1,2],[3,4]], dtype=float32) - af64 = array([[1,2],[3,4]], dtype=float64) - acs = array([[1+5j,2+6j],[3+7j,4+8j]], dtype=csingle) - acd = array([[1+5j,2+6j],[3+7j,4+8j]], dtype=cdouble) + ai32 = array([[1, 2], [3, 4]], dtype=int32) + af32 = array([[1, 2], [3, 4]], dtype=float32) + af64 = array([[1, 2], [3, 4]], dtype=float64) + acs = array([[1+5j, 2+6j], [3+7j, 4+8j]], dtype=csingle) + acd = array([[1+5j, 2+6j], [3+7j, 4+8j]], dtype=cdouble) assert_(common_type(af32) == float32) assert_(common_type(af64) == float64) assert_(common_type(acs) == csingle) @@ -36,50 +36,50 @@ class TestMintypecode(TestCase): def test_default_1(self): for itype in '1bcsuwil': - assert_equal(mintypecode(itype),'d') - assert_equal(mintypecode('f'),'f') - assert_equal(mintypecode('d'),'d') - assert_equal(mintypecode('F'),'F') - assert_equal(mintypecode('D'),'D') + assert_equal(mintypecode(itype), 'd') + assert_equal(mintypecode('f'), 'f') + assert_equal(mintypecode('d'), 'd') + assert_equal(mintypecode('F'), 'F') + assert_equal(mintypecode('D'), 'D') def test_default_2(self): for itype in '1bcsuwil': - assert_equal(mintypecode(itype+'f'),'f') - assert_equal(mintypecode(itype+'d'),'d') - assert_equal(mintypecode(itype+'F'),'F') - assert_equal(mintypecode(itype+'D'),'D') - assert_equal(mintypecode('ff'),'f') - assert_equal(mintypecode('fd'),'d') - assert_equal(mintypecode('fF'),'F') - assert_equal(mintypecode('fD'),'D') - assert_equal(mintypecode('df'),'d') - assert_equal(mintypecode('dd'),'d') + assert_equal(mintypecode(itype+'f'), 'f') + assert_equal(mintypecode(itype+'d'), 'd') + assert_equal(mintypecode(itype+'F'), 'F') + assert_equal(mintypecode(itype+'D'), 'D') + assert_equal(mintypecode('ff'), 'f') + assert_equal(mintypecode('fd'), 'd') + assert_equal(mintypecode('fF'), 'F') + assert_equal(mintypecode('fD'), 'D') + assert_equal(mintypecode('df'), 'd') + assert_equal(mintypecode('dd'), 'd') #assert_equal(mintypecode('dF',savespace=1),'F') - assert_equal(mintypecode('dF'),'D') - assert_equal(mintypecode('dD'),'D') - assert_equal(mintypecode('Ff'),'F') + assert_equal(mintypecode('dF'), 'D') + assert_equal(mintypecode('dD'), 'D') + assert_equal(mintypecode('Ff'), 'F') #assert_equal(mintypecode('Fd',savespace=1),'F') - assert_equal(mintypecode('Fd'),'D') - assert_equal(mintypecode('FF'),'F') - assert_equal(mintypecode('FD'),'D') - assert_equal(mintypecode('Df'),'D') - assert_equal(mintypecode('Dd'),'D') - assert_equal(mintypecode('DF'),'D') - assert_equal(mintypecode('DD'),'D') + assert_equal(mintypecode('Fd'), 'D') + assert_equal(mintypecode('FF'), 'F') + assert_equal(mintypecode('FD'), 'D') + assert_equal(mintypecode('Df'), 'D') + assert_equal(mintypecode('Dd'), 'D') + assert_equal(mintypecode('DF'), 'D') + assert_equal(mintypecode('DD'), 'D') def test_default_3(self): - assert_equal(mintypecode('fdF'),'D') + assert_equal(mintypecode('fdF'), 'D') #assert_equal(mintypecode('fdF',savespace=1),'F') - assert_equal(mintypecode('fdD'),'D') - assert_equal(mintypecode('fFD'),'D') - assert_equal(mintypecode('dFD'),'D') - - assert_equal(mintypecode('ifd'),'d') - assert_equal(mintypecode('ifF'),'F') - assert_equal(mintypecode('ifD'),'D') - assert_equal(mintypecode('idF'),'D') + assert_equal(mintypecode('fdD'), 'D') + assert_equal(mintypecode('fFD'), 'D') + assert_equal(mintypecode('dFD'), 'D') + + assert_equal(mintypecode('ifd'), 'd') + assert_equal(mintypecode('ifF'), 'F') + assert_equal(mintypecode('ifD'), 'D') + assert_equal(mintypecode('idF'), 'D') #assert_equal(mintypecode('idF',savespace=1),'F') - assert_equal(mintypecode('idD'),'D') + assert_equal(mintypecode('idD'), 'D') class TestIsscalar(TestCase): @@ -97,72 +97,72 @@ class TestReal(TestCase): def test_real(self): y = rand(10,) - assert_array_equal(y,real(y)) + assert_array_equal(y, real(y)) def test_cmplx(self): y = rand(10,)+1j*rand(10,) - assert_array_equal(y.real,real(y)) + assert_array_equal(y.real, real(y)) class TestImag(TestCase): def test_real(self): y = rand(10,) - assert_array_equal(0,imag(y)) + assert_array_equal(0, imag(y)) def test_cmplx(self): y = rand(10,)+1j*rand(10,) - assert_array_equal(y.imag,imag(y)) + assert_array_equal(y.imag, imag(y)) class TestIscomplex(TestCase): def test_fail(self): - z = array([-1,0,1]) + z = array([-1, 0, 1]) res = iscomplex(z) - assert_(not sometrue(res,axis=0)) + assert_(not sometrue(res, axis=0)) def test_pass(self): - z = array([-1j,1,0]) + z = array([-1j, 1, 0]) res = iscomplex(z) - assert_array_equal(res,[1,0,0]) + assert_array_equal(res, [1, 0, 0]) class TestIsreal(TestCase): def test_pass(self): - z = array([-1,0,1j]) + z = array([-1, 0, 1j]) res = isreal(z) - assert_array_equal(res,[1,1,0]) + assert_array_equal(res, [1, 1, 0]) def test_fail(self): - z = array([-1j,1,0]) + z = array([-1j, 1, 0]) res = isreal(z) - assert_array_equal(res,[0,1,1]) + assert_array_equal(res, [0, 1, 1]) class TestIscomplexobj(TestCase): def test_basic(self): - z = array([-1,0,1]) + z = array([-1, 0, 1]) assert_(not iscomplexobj(z)) - z = array([-1j,0,-1]) + z = array([-1j, 0, -1]) assert_(iscomplexobj(z)) class TestIsrealobj(TestCase): def test_basic(self): - z = array([-1,0,1]) + z = array([-1, 0, 1]) assert_(isrealobj(z)) - z = array([-1j,0,-1]) + z = array([-1j, 0, -1]) assert_(not isrealobj(z)) class TestIsnan(TestCase): def test_goodvalues(self): - z = array((-1.,0.,1.)) + z = array((-1., 0., 1.)) res = isnan(z) == 0 - assert_all(alltrue(res,axis=0)) + assert_all(alltrue(res, axis=0)) def test_posinf(self): with errstate(divide='ignore'): @@ -193,9 +193,9 @@ class TestIsnan(TestCase): class TestIsfinite(TestCase): def test_goodvalues(self): - z = array((-1.,0.,1.)) + z = array((-1., 0., 1.)) res = isfinite(z) == 1 - assert_all(alltrue(res,axis=0)) + assert_all(alltrue(res, axis=0)) def test_posinf(self): with errstate(divide='ignore', invalid='ignore'): @@ -226,9 +226,9 @@ class TestIsfinite(TestCase): class TestIsinf(TestCase): def test_goodvalues(self): - z = array((-1.,0.,1.)) + z = array((-1., 0., 1.)) res = isinf(z) == 0 - assert_all(alltrue(res,axis=0)) + assert_all(alltrue(res, axis=0)) def test_posinf(self): with errstate(divide='ignore', invalid='ignore'): @@ -259,7 +259,7 @@ class TestIsposinf(TestCase): def test_generic(self): with errstate(divide='ignore', invalid='ignore'): - vals = isposinf(array((-1.,0,1))/0.) + vals = isposinf(array((-1., 0, 1))/0.) assert_(vals[0] == 0) assert_(vals[1] == 0) assert_(vals[2] == 1) @@ -269,7 +269,7 @@ class TestIsneginf(TestCase): def test_generic(self): with errstate(divide='ignore', invalid='ignore'): - vals = isneginf(array((-1.,0,1))/0.) + vals = isneginf(array((-1., 0, 1))/0.) assert_(vals[0] == 1) assert_(vals[1] == 0) assert_(vals[2] == 0) @@ -279,7 +279,7 @@ class TestNanToNum(TestCase): def test_generic(self): with errstate(divide='ignore', invalid='ignore'): - vals = nan_to_num(array((-1.,0,1))/0.) + vals = nan_to_num(array((-1., 0, 1))/0.) assert_all(vals[0] < -1e10) and assert_all(isfinite(vals[0])) assert_(vals[1] == 0) assert_all(vals[2] > 1e10) and assert_all(isfinite(vals[2])) @@ -319,19 +319,19 @@ class TestRealIfClose(TestCase): a = rand(10) b = real_if_close(a+1e-15j) assert_all(isrealobj(b)) - assert_array_equal(a,b) + assert_array_equal(a, b) b = real_if_close(a+1e-7j) assert_all(iscomplexobj(b)) - b = real_if_close(a+1e-7j,tol=1e-6) + b = real_if_close(a+1e-7j, tol=1e-6) assert_all(isrealobj(b)) class TestArrayConversion(TestCase): def test_asfarray(self): - a = asfarray(array([1,2,3])) - assert_equal(a.__class__,ndarray) - assert_(issubdtype(a.dtype,float)) + a = asfarray(array([1, 2, 3])) + assert_equal(a.__class__, ndarray) + assert_(issubdtype(a.dtype, float)) if __name__ == "__main__": run_module_suite() diff --git a/numpy/lib/tests/test_ufunclike.py b/numpy/lib/tests/test_ufunclike.py index 50f3229e8..31dbdba1a 100644 --- a/numpy/lib/tests/test_ufunclike.py +++ b/numpy/lib/tests/test_ufunclike.py @@ -54,7 +54,7 @@ class TestUfunclike(TestCase): a = nx.array([1.1, -1.1]) m = MyArray(a, metadata='foo') f = ufl.fix(m) - assert_array_equal(f, nx.array([1,-1])) + assert_array_equal(f, nx.array([1, -1])) assert_(isinstance(f, MyArray)) assert_equal(f.metadata, 'foo') diff --git a/numpy/lib/twodim_base.py b/numpy/lib/twodim_base.py index a39f60220..91df1f4f8 100644 --- a/numpy/lib/twodim_base.py +++ b/numpy/lib/twodim_base.py @@ -3,9 +3,9 @@ """ from __future__ import division, absolute_import, print_function -__all__ = ['diag','diagflat','eye','fliplr','flipud','rot90','tri','triu', - 'tril','vander','histogram2d','mask_indices', - 'tril_indices','tril_indices_from','triu_indices','triu_indices_from', +__all__ = ['diag', 'diagflat', 'eye', 'fliplr', 'flipud', 'rot90', 'tri', 'triu', + 'tril', 'vander', 'histogram2d', 'mask_indices', + 'tril_indices', 'tril_indices_from', 'triu_indices', 'triu_indices_from', ] from numpy.core.numeric import asanyarray, equal, subtract, arange, \ @@ -113,7 +113,7 @@ def flipud(m): m = asanyarray(m) if m.ndim < 1: raise ValueError("Input must be >= 1-d.") - return m[::-1,...] + return m[::-1, ...] def rot90(m, k=1): """ @@ -160,12 +160,12 @@ def rot90(m, k=1): if k == 0: return m elif k == 1: - return fliplr(m).swapaxes(0,1) + return fliplr(m).swapaxes(0, 1) elif k == 2: return fliplr(flipud(m)) else: # k == 3 - return fliplr(m.swapaxes(0,1)) + return fliplr(m.swapaxes(0, 1)) def eye(N, M=None, k=0, dtype=float): """ @@ -276,7 +276,7 @@ def diag(v, k=0): s = v.shape if len(s) == 1: n = s[0]+abs(k) - res = zeros((n,n), v.dtype) + res = zeros((n, n), v.dtype) if k >= 0: i = k else: @@ -334,12 +334,12 @@ def diagflat(v, k=0): v = asarray(v).ravel() s = len(v) n = s + abs(k) - res = zeros((n,n), v.dtype) + res = zeros((n, n), v.dtype) if (k >= 0): - i = arange(0,n-k) + i = arange(0, n-k) fi = i+k+i*n else: - i = arange(0,n+k) + i = arange(0, n+k) fi = i+(i-k)*n res.flat[fi] = v if not wrap: @@ -385,7 +385,7 @@ def tri(N, M=None, k=0, dtype=float): """ if M is None: M = N - m = greater_equal(subtract.outer(arange(N), arange(M)),-k) + m = greater_equal(subtract.outer(arange(N), arange(M)), -k) return m.astype(dtype) def tril(m, k=0): @@ -421,7 +421,7 @@ def tril(m, k=0): """ m = asanyarray(m) - out = multiply(tri(m.shape[0], m.shape[1], k=k, dtype=m.dtype),m) + out = multiply(tri(m.shape[0], m.shape[1], k=k, dtype=m.dtype), m) return out def triu(m, k=0): @@ -510,9 +510,9 @@ def vander(x, N=None): x = asarray(x) if N is None: N=len(x) - X = ones( (len(x),N), x.dtype) + X = ones( (len(x), N), x.dtype) for i in range(N - 1): - X[:,i] = x**(N - i - 1) + X[:, i] = x**(N - i - 1) return X @@ -650,7 +650,7 @@ def histogram2d(x, y, bins=10, range=None, normed=False, weights=None): if N != 1 and N != 2: xedges = yedges = asarray(bins, float) bins = [xedges, yedges] - hist, edges = histogramdd([x,y], bins, range, normed, weights) + hist, edges = histogramdd([x, y], bins, range, normed, weights) return hist, edges[0], edges[1] @@ -719,7 +719,7 @@ def mask_indices(n, mask_func, k=0): array([1, 2, 5]) """ - m = ones((n,n), int) + m = ones((n, n), int) a = mask_func(m, k) return where(a != 0) @@ -929,4 +929,4 @@ def triu_indices_from(arr, k=0): """ if not (arr.ndim == 2 and arr.shape[0] == arr.shape[1]): raise ValueError("input array must be 2-d and square") - return triu_indices(arr.shape[0],k) + return triu_indices(arr.shape[0], k) diff --git a/numpy/lib/type_check.py b/numpy/lib/type_check.py index da9e13847..1ed5bf32a 100644 --- a/numpy/lib/type_check.py +++ b/numpy/lib/type_check.py @@ -3,9 +3,9 @@ """ from __future__ import division, absolute_import, print_function -__all__ = ['iscomplexobj','isrealobj','imag','iscomplex', - 'isreal','nan_to_num','real','real_if_close', - 'typename','asfarray','mintypecode','asscalar', +__all__ = ['iscomplexobj', 'isrealobj', 'imag', 'iscomplex', + 'isreal', 'nan_to_num', 'real', 'real_if_close', + 'typename', 'asfarray', 'mintypecode', 'asscalar', 'common_type'] import numpy.core.numeric as _nx @@ -68,7 +68,7 @@ def mintypecode(typechars,typeset='GDFgdf',default='d'): l = [] for t in intersection: i = _typecodes_by_elsize.index(t) - l.append((i,t)) + l.append((i, t)) l.sort() return l[0][1] @@ -102,7 +102,7 @@ def asfarray(a, dtype=_nx.float_): dtype = _nx.obj2sctype(dtype) if not issubclass(dtype, _nx.inexact): dtype = _nx.float_ - return asarray(a,dtype=dtype) + return asarray(a, dtype=dtype) def real(val): """ @@ -603,4 +603,3 @@ def common_type(*arrays): return array_type[1][precision] else: return array_type[0][precision] - diff --git a/numpy/lib/user_array.py b/numpy/lib/user_array.py index d675d3702..f62f6db59 100644 --- a/numpy/lib/user_array.py +++ b/numpy/lib/user_array.py @@ -12,7 +12,7 @@ from numpy.core import ( bitwise_xor, invert, less, less_equal, not_equal, equal, greater, greater_equal, shape, reshape, arange, sin, sqrt, transpose ) -from numpy.compat import long +from numpy.compat import long class container(object): def __init__(self, data, dtype=None, copy=True): @@ -39,9 +39,9 @@ class container(object): def __setitem__(self, index, value): - self.array[index] = asarray(value,self.dtype) + self.array[index] = asarray(value, self.dtype) def __setslice__(self, i, j, value): - self.array[i:j] = asarray(value,self.dtype) + self.array[i:j] = asarray(value, self.dtype) def __abs__(self): return self._rc(absolute(self.array)) @@ -65,16 +65,16 @@ class container(object): return self def __mul__(self, other): - return self._rc(multiply(self.array,asarray(other))) + return self._rc(multiply(self.array, asarray(other))) __rmul__ = __mul__ def __imul__(self, other): multiply(self.array, other, self.array) return self def __div__(self, other): - return self._rc(divide(self.array,asarray(other))) + return self._rc(divide(self.array, asarray(other))) def __rdiv__(self, other): - return self._rc(divide(asarray(other),self.array)) + return self._rc(divide(asarray(other), self.array)) def __idiv__(self, other): divide(self.array, other, self.array) return self @@ -88,32 +88,32 @@ class container(object): return self def __divmod__(self, other): - return (self._rc(divide(self.array,other)), + return (self._rc(divide(self.array, other)), self._rc(remainder(self.array, other))) def __rdivmod__(self, other): return (self._rc(divide(other, self.array)), self._rc(remainder(other, self.array))) - def __pow__(self,other): - return self._rc(power(self.array,asarray(other))) - def __rpow__(self,other): - return self._rc(power(asarray(other),self.array)) - def __ipow__(self,other): + def __pow__(self, other): + return self._rc(power(self.array, asarray(other))) + def __rpow__(self, other): + return self._rc(power(asarray(other), self.array)) + def __ipow__(self, other): power(self.array, other, self.array) return self - def __lshift__(self,other): + def __lshift__(self, other): return self._rc(left_shift(self.array, other)) - def __rshift__(self,other): + def __rshift__(self, other): return self._rc(right_shift(self.array, other)) - def __rlshift__(self,other): + def __rlshift__(self, other): return self._rc(left_shift(other, self.array)) - def __rrshift__(self,other): + def __rrshift__(self, other): return self._rc(right_shift(other, self.array)) - def __ilshift__(self,other): + def __ilshift__(self, other): left_shift(self.array, other, self.array) return self - def __irshift__(self,other): + def __irshift__(self, other): right_shift(self.array, other, self.array) return self @@ -163,12 +163,12 @@ class container(object): def __hex__(self): return self._scalarfunc(hex) def __oct__(self): return self._scalarfunc(oct) - def __lt__(self,other): return self._rc(less(self.array,other)) - def __le__(self,other): return self._rc(less_equal(self.array,other)) - def __eq__(self,other): return self._rc(equal(self.array,other)) - def __ne__(self,other): return self._rc(not_equal(self.array,other)) - def __gt__(self,other): return self._rc(greater(self.array,other)) - def __ge__(self,other): return self._rc(greater_equal(self.array,other)) + def __lt__(self, other): return self._rc(less(self.array, other)) + def __le__(self, other): return self._rc(less_equal(self.array, other)) + def __eq__(self, other): return self._rc(equal(self.array, other)) + def __ne__(self, other): return self._rc(not_equal(self.array, other)) + def __gt__(self, other): return self._rc(greater(self.array, other)) + def __ge__(self, other): return self._rc(greater_equal(self.array, other)) def copy(self): return self._rc(self.array.copy()) @@ -185,7 +185,7 @@ class container(object): def __array_wrap__(self, *args): return self.__class__(args[0]) - def __setattr__(self,attr,value): + def __setattr__(self, attr, value): if attr == 'array': object.__setattr__(self, attr, value) return @@ -195,7 +195,7 @@ class container(object): object.__setattr__(self, attr, value) # Only called after other approaches fail. - def __getattr__(self,attr): + def __getattr__(self, attr): if (attr == 'array'): return object.__getattribute__(self, attr) return self.array.__getattribute__(attr) @@ -204,19 +204,19 @@ class container(object): # Test of class container ############################################################# if __name__ == '__main__': - temp=reshape(arange(10000),(100,100)) + temp=reshape(arange(10000), (100, 100)) ua=container(temp) # new object created begin test print(dir(ua)) - print(shape(ua),ua.shape) # I have changed Numeric.py + print(shape(ua), ua.shape) # I have changed Numeric.py - ua_small=ua[:3,:5] + ua_small=ua[:3, :5] print(ua_small) - ua_small[0,0]=10 # this did not change ua[0,0], which is not normal behavior - print(ua_small[0,0],ua[0,0]) + ua_small[0, 0]=10 # this did not change ua[0,0], which is not normal behavior + print(ua_small[0, 0], ua[0, 0]) print(sin(ua_small)/3.*6.+sqrt(ua_small**2)) - print(less(ua_small,103),type(less(ua_small,103))) - print(type(ua_small*reshape(arange(15),shape(ua_small)))) - print(reshape(ua_small,(5,3))) + print(less(ua_small, 103), type(less(ua_small, 103))) + print(type(ua_small*reshape(arange(15), shape(ua_small)))) + print(reshape(ua_small, (5, 3))) print(transpose(ua_small)) diff --git a/numpy/lib/utils.py b/numpy/lib/utils.py index f54946722..1b968f1fc 100644 --- a/numpy/lib/utils.py +++ b/numpy/lib/utils.py @@ -320,7 +320,7 @@ def who(vardict=None): sta = [] cache = {} for name in vardict.keys(): - if isinstance(vardict[name],ndarray): + if isinstance(vardict[name], ndarray): var = vardict[name] idv = id(var) if idv in cache.keys(): @@ -351,9 +351,9 @@ def who(vardict=None): totalbytes += int(val[2]) if len(sta) > 0: - sp1 = max(10,maxname) - sp2 = max(10,maxshape) - sp3 = max(10,maxbyte) + sp1 = max(10, maxname) + sp2 = max(10, maxshape) + sp3 = max(10, maxbyte) prval = "Name %s Shape %s Bytes %s Type" % (sp1*' ', sp2*' ', sp3*' ') print(prval + "\n" + "="*(len(prval)+5) + "\n") @@ -409,7 +409,7 @@ def _makenamedict(module='numpy'): break thisdict = totraverse.pop(0) for x in thisdict.keys(): - if isinstance(thisdict[x],types.ModuleType): + if isinstance(thisdict[x], types.ModuleType): modname = thisdict[x].__name__ if modname not in dictlist: moddict = thisdict[x].__dict__ @@ -470,7 +470,7 @@ def info(object=None,maxwidth=76,output=sys.stdout,toplevel='numpy'): # Local import to speed up numpy's import time. import pydoc, inspect - if hasattr(object,'_ppimport_importer') or \ + if hasattr(object, '_ppimport_importer') or \ hasattr(object, '_ppimport_module'): object = object._ppimport_module elif hasattr(object, '_ppimport_attr'): @@ -537,7 +537,7 @@ def info(object=None,maxwidth=76,output=sys.stdout,toplevel='numpy'): print(" " + argstr + "\n", file=output) doc1 = inspect.getdoc(object) if doc1 is None: - if hasattr(object,'__init__'): + if hasattr(object, '__init__'): print(inspect.getdoc(object.__init__), file=output) else: print(inspect.getdoc(object), file=output) @@ -565,7 +565,7 @@ def info(object=None,maxwidth=76,output=sys.stdout,toplevel='numpy'): else: arguments = "()" - if hasattr(object,'name'): + if hasattr(object, 'name'): name = "%s" % object.name else: name = "<name>" @@ -972,7 +972,7 @@ class SafeEval(object): if sys.version_info[0] < 3: def visit(self, node, **kw): cls = node.__class__ - meth = getattr(self,'visit'+cls.__name__,self.default) + meth = getattr(self, 'visit'+cls.__name__, self.default) return meth(node, **kw) def default(self, node, **kw): @@ -987,7 +987,7 @@ class SafeEval(object): return node.value def visitDict(self, node,**kw): - return dict([(self.visit(k),self.visit(v)) for k,v in node.items]) + return dict([(self.visit(k), self.visit(v)) for k, v in node.items]) def visitTuple(self, node, **kw): return tuple([self.visit(i) for i in node.nodes]) |