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T2pF$58xE{DUfbw>!ejn_*XD3A literal 0 HcmV?d00001 diff --git a/lib/scitools/easyviz/utils.py b/lib/scitools/easyviz/utils.py index e13d878..e9cfbc9 100644 --- a/lib/scitools/easyviz/utils.py +++ b/lib/scitools/easyviz/utils.py @@ -11,7 +11,7 @@ def available_backends(): files.remove('__init__.py') backends = [f for f in files if f.endswith('_.py')] available = [] - print '\nChecking if you have all the Easyviz backends...' + print('\nChecking if you have all the Easyviz backends...') for b in backends: module = 'scitools.easyviz.' + b[:-3] try: diff --git a/lib/scitools/numpytools.py b/lib/scitools/numpytools.py index 31f5b6f..e2d7f86 100644 --- a/lib/scitools/numpytools.py +++ b/lib/scitools/numpytools.py @@ -190,7 +190,7 @@ # check the environment variable NUMPYARRAY: if basic_NumPy is None: - if os.environ.has_key('NUMPYARRAY'): + if 'NUMPYARRAY' in os.environ: if os.environ['NUMPYARRAY'] == 'numpy': basic_NumPy = 'numpy' elif os.environ['NUMPYARRAY'] == 'numarray': @@ -224,30 +224,30 @@ if basic_NumPy == 'numpy': try: # fix backward compatibility with Numeric names: - import numpy - oldversion = (numpy.version.version[0] == '0') + import numpy + oldversion = (numpy.version.version[0] == '0') majorversion = int(numpy.version.version[0]) minorversion = int(numpy.version.version[2]) - for _Numeric_name, _dummy1, _numpy_name in _NumPy_modules[1:]: - if oldversion and (_Numeric_name in ['RNG', 'FFT']): - n, module = _numpy_name.split('.') - exec "from %s import %s as %s" %(n, module, _Numeric_name) - elif oldversion and (_Numeric_name == 'MLab'): - from numpy.lib import mlab as MLab + for _Numeric_name, _dummy1, _numpy_name in _NumPy_modules[1:]: + if oldversion and (_Numeric_name in ['RNG', 'FFT']): + n, module = _numpy_name.split('.') + exec("from %s import %s as %s" %(n, module, _Numeric_name)) + elif oldversion and (_Numeric_name == 'MLab'): + from numpy.lib import mlab as MLab elif (oldversion or (majorversion == 1 and minorversion < 1)) \ and (_Numeric_name == 'MA'): import numpy.core.ma; MA = numpy.core.ma - elif _numpy_name != '': - exec 'import %s; %s = %s' % \ - (_numpy_name, _Numeric_name, _numpy_name) + elif _numpy_name != '': + exec('import %s; %s = %s' % \ + (_numpy_name, _Numeric_name, _numpy_name)) - del _Numeric_name, _dummy1, _numpy_name, _NumPy_modules + del _Numeric_name, _dummy1, _numpy_name, _NumPy_modules - from numpy import * - if not oldversion: - # get the old names too (NewAxis, Float, etc.): - from numpy.oldnumeric import * - del oldversion + from numpy import * + if not oldversion: + # get the old names too (NewAxis, Float, etc.): + from numpy.oldnumeric import * + del oldversion # define new names compatible with Numeric: LinearAlgebra.solve_linear_equations = linalg.solve LinearAlgebra.inverse = linalg.inv @@ -256,8 +256,8 @@ LinearAlgebra.eigenvectors = linalg.eig except ImportError as e: - raise ImportError('%s\nnumpy import failed!\n'\ - 'see doc of %s module for how to choose Numeric instead' % \ + raise ImportError('%s\nnumpy import failed!\n' + 'see doc of %s module for how to choose Numeric instead' % (e, __name__)) @@ -297,8 +297,8 @@ def arrmin(a): try: for _Numeric_name, _numarray_name, _dummy1 in _NumPy_modules[1:]: if _numarray_name: - exec 'import %s; %s = %s' % \ - (_numarray_name, _Numeric_name, _numarray_name) + exec('import %s; %s = %s' % \ + (_numarray_name, _Numeric_name, _numarray_name)) # RNG is not supported, make an object that gives an error message: class __Dummy: @@ -311,8 +311,8 @@ def __getattr__(self, name): from numarray import * except ImportError as e: - raise ImportError('%s\nnumarray import failed!\n'\ - 'see doc of %s module for how to choose Numeric instead' % \ + raise ImportError('%s\nnumarray import failed!\n' + 'see doc of %s module for how to choose Numeric instead' % (e, __name__)) def array_output_precision(no_of_decimals): @@ -351,7 +351,7 @@ def arrmin(a): try: for _Numeric_name, _dummy1, _dummy2 in _NumPy_modules[1:]: if _Numeric_name != 'MA': # exclude MA, see comment above - exec 'import %s' % _Numeric_name + exec('import %s' % _Numeric_name) del _Numeric_name, _dummy1, _dummy2, _NumPy_modules from Numeric import * @@ -404,8 +404,8 @@ def numpy_eigenvectors(A): del _problems except ImportError as e: - raise ImportError('%s\nNumeric import failed!\n'\ - 'see doc of %s module for how to choose numarray instead' % \ + raise ImportError('%s\nNumeric import failed!\n' + 'see doc of %s module for how to choose numarray instead' % (e, __name__)) @@ -496,10 +496,10 @@ def NumPy_type(a): # Check for non NumPy types first if isinstance(a, tuple): - return "tuple" + return "tuple" elif isinstance(a, list): - return "list" - exec "import %s" % basic_NumPy # Why isn't basic_NumPy imported? + return "list" + exec("import %s" % basic_NumPy) # Why isn't basic_NumPy imported? if isinstance(a, eval(types[basic_NumPy])): return basic_NumPy @@ -743,9 +743,8 @@ def meshgrid(x=None, y=None, z=None, sparse=False, indexing='xy', sequence on the left-hand side and instead adjust a keyword argument. """ - import types def fixed(coor): - return isinstance(coor, (float, complex, int, types.NoneType)) + return isinstance(coor, (float, complex, int, type(None))) if not fixed(x): x = asarray(x) @@ -919,11 +918,11 @@ def Gram_Schmidt1(vecs, row_wise_storage=True): basis[:,0] /= sqrt(dot(basis[:,0], basis[:,0])) for i in range(1, m): - v = basis[:,i]/sqrt(dot(basis[:,i], basis[:,i])) - U = basis[:,:i] - P = eye - dot(U, dot(inv(dot(transpose(U), U)), transpose(U))) - basis[:, i] = dot(P, v) - basis[:, i] /= sqrt(dot(basis[:, i], basis[:, i])) + v = basis[:,i]/sqrt(dot(basis[:,i], basis[:,i])) + U = basis[:,:i] + P = eye - dot(U, dot(inv(dot(transpose(U), U)), transpose(U))) + basis[:, i] = dot(P, v) + basis[:, i] /= sqrt(dot(basis[:, i], basis[:, i])) return transpose(basis) if row_wise_storage else basis @@ -968,10 +967,10 @@ def Gram_Schmidt(vecs, row_wise_storage=True, tol=1E-10, m, n = A.shape V = zeros((m,n)) - for j in xrange(n): + for j in range(n): v0 = A[:,j] v = v0.copy() - for i in xrange(j): + for i in range(j): vi = V[:,i] if (abs(vi) > tol).any(): @@ -979,11 +978,11 @@ def Gram_Schmidt(vecs, row_wise_storage=True, tol=1E-10, V[:,j] = v if remove_null_vectors: - indices = [i for i in xrange(n) if (abs(V[:,i]) < tol).all()] + indices = [i for i in range(n) if (abs(V[:,i]) < tol).all()] V = V[ix_(range(m), indices)] if normalize: - for j in xrange(V.shape[1]): + for j in range(V.shape[1]): V[:,j] /= linalg.norm(V[:,j]) if remove_noise: @@ -1126,7 +1125,7 @@ def plot(self, center=0, xmin=-1, xmax=1): class DiracDelta: - """ + r""" Smoothed Dirac delta function: $\frac{1}{2\epsilon}(1 + \cos(\pi x/\epsilon)$ when $x\in [-\epsilon, \epsilon]$ and 0 elsewhere. @@ -1860,15 +1859,15 @@ def nested_loops(a): no_value = kwargs.get('no_value', False) for line in offset_code1: - exec line + exec(line) for line in offset_code2: - exec line + exec(line) code = 'def nested_loops(a):\n' indentation = ' '*4 indent = '' + indentation for dim in range(len(a.shape)): code += indent + \ - 'for i%d in xrange(%d, a.shape[%d]-%d):\n' \ + 'for i%d in range(%d, a.shape[%d]-%d):\n' \ % (dim, eval('offset%d_start' % dim), dim, eval('offset%d_stop' % dim)) indent += indentation @@ -1877,7 +1876,7 @@ def nested_loops(a): code += indent + 'yield ' + index else: code += indent + 'yield ' + 'a[%s]' % index + ', (' + index + ')' - exec code + exec(code) return nested_loops, code def compute_histogram(samples, nbins=50, piecewise_constant=True): @@ -1941,9 +1940,9 @@ def factorial(n, method='reduce'): ========================== ===================== """ - if not isinstance(n, (int, long, float)): + if not isinstance(n, (int, float)): raise TypeError('factorial(n): n must be integer not %s' % type(n)) - n = long(n) + n = int(n) if n == 0 or n == 1: return 1 @@ -1963,22 +1962,22 @@ def factorial(n, method='reduce'): return fc(n) elif method == 'lambda functional': fc = lambda n: n<=0 or \ - reduce(lambda a,b: long(a)*long(b), xrange(1,n+1)) + reduce(lambda a,b: int(a)*int(b), range(1,n+1)) return fc(n) elif method == 'lambda list comprehension': fc = lambda n: [j for j in [1] for i in range(2,n+1) \ for j in [j*i]] [-1] return fc(n) elif method == 'reduce': - return reduce(operator.mul, xrange(2, n+1)) + return reduce(operator.mul, range(2, n+1)) elif method == 'scipy': try: import scipy.misc.common as sc return sc.factorial(n) except ImportError: - print 'numpyutils.factorial: scipy is not available' - print 'default method="reduce" is used instead' - return reduce(operator.mul, xrange(2, n+1)) + print('numpyutils.factorial: scipy is not available') + print('default method="reduce" is used instead') + return reduce(operator.mul, range(2, n+1)) # or return factorial(n) else: raise ValueError('factorial: method="%s" is not supported' % method) @@ -1999,7 +1998,7 @@ def asarray_cpwarn(a, dtype=None, message='warning', comment=''): msg = '%s copy of array %s, from %s to %s' % \ (comment, a.shape, type(a), type(a_new)) if message == 'warning': - print 'Warning: %s' % msg + print('Warning: %s' % msg) elif message == 'exception': raise TypeError(msg) return a_new @@ -2033,7 +2032,7 @@ def iseq(start=0, stop=None, inc=1): if stop is None: # allow isequence(3) to be 0, 1, 2, 3 # take 1st arg as stop, start as 0, and inc=1 stop = start; start = 0; inc = 1 - return xrange(start, stop+inc, inc) + return range(start, stop+inc, inc) sequence = seq # backward compatibility isequence = iseq # backward compatibility @@ -2201,7 +2200,7 @@ def arr(shape=None, element_type=float, return linspace(interval[0], interval[1], shape) except MemoryError as e: # print more information (size of data): - print e, 'of size %s' % shape + print(e, 'of size %s' % shape) else: # no data, no file, just make zeros @@ -2216,7 +2215,7 @@ def arr(shape=None, element_type=float, return zeros(shape, dtype=element_type, order=order) except MemoryError as e: # print more information (size of data): - print e, 'of size %s' % shape + print(e, 'of size %s' % shape) def _test(): _test_FloatComparison() @@ -2227,24 +2226,24 @@ def _test(): results = [78.7464284904401239, 15.1547572288924073, 351, 13, 26] for f, r in zip(functions, results): if not float_eq(f(a), r): - print '%s failed: result=%g, not %g' % (f.__name__, f(a), r) + print('%s failed: result=%g, not %g' % (f.__name__, f(a), r)) # Gram-Schmidt: A = array([[1,2,3], [3,4,5], [6,4,1]], float) V1 = Gram_Schmidt(A, normalize=True) V2 = Gram_Schmidt1(A) if not float_eq(V1, V2): - print 'The two Gram_Schmidt versions did not give equal results' - print 'Gram_Schmidt:\n', V1 - print 'Gram_Schmidt1:\n', V2 + print('The two Gram_Schmidt versions did not give equal results') + print('Gram_Schmidt:\n', V1) + print('Gram_Schmidt1:\n', V2) # Null space: K = array([[1,2,3], [1,2,3], [0,0,0], [-1, -2, -3]], float) #K = random.random(3*7).reshape(7,3) # does not work... - print 'K=\n', K - print 'null(K)=\n', null(K) + print('K=\n', K) + print('null(K)=\n', null(K)) r = K*null(K) - print 'K*null(K):', r + print('K*null(K):', r) if __name__ == '__main__': @@ -2303,14 +2302,14 @@ def verify(N, namecheck = ['fft','mlab','ma','ra','la']): Verify that some packages imported by numpytools works for Numeric, numarray, or numpy. """ - print "\nUsing %s in %s" % (N.basic_NumPy, N.__name__) + print("\nUsing %s in %s" % (N.basic_NumPy, N.__name__)) for name in namecheck: if hasattr(N, name): - print "%s.%s : %s " % ( + print("%s.%s : %s " % ( N.__name__, name, - eval("N.%s.__name__" % name)) - print "" + eval("N.%s.__name__" % name))) + print("") def _test1(): """Call verify function for N as Numeric, numarray, and numpy.""" @@ -2403,12 +2402,12 @@ def testMeshGrid_DenseFromNodenseMeshgridOutput(self): try: __import__(arg[2:]) except: - print "You don't have %s installed" %arg[2:] + print("You don't have %s installed" % arg[2:]) continue sys.argv[-1] = arg - print '\nNow testing with system arg %10s\n%s' %(arg, '='*38) - print N, dir(N) + print('\nNow testing with system arg %10s\n%s' % (arg, '='*38)) + print(N, dir(N)) reload(N); verify(N) suite = unittest.makeSuite(numpytoolsTest) unittest.TextTestRunner(verbosity=2).run(suite)