From 93db239e1156ad1db8edbb13c1ecde973ce009c0 Mon Sep 17 00:00:00 2001 From: Rémi Flamary Date: Mon, 19 Nov 2018 11:17:07 +0100 Subject: remove W605 errors --- ot/bregman.py | 18 +++++++++--------- ot/externals/funcsigs.py | 46 +++++++++++++++++++++++----------------------- ot/gpu/bregman.py | 6 +++--- ot/stochastic.py | 20 ++++++++++---------- setup.cfg | 2 +- 5 files changed, 46 insertions(+), 46 deletions(-) diff --git a/ot/bregman.py b/ot/bregman.py index d1057ff..43340f7 100644 --- a/ot/bregman.py +++ b/ot/bregman.py @@ -370,9 +370,9 @@ def sinkhorn_knopp(a, b, M, reg, numItermax=1000, v = np.divide(b, KtransposeU) u = 1. / np.dot(Kp, v) - if (np.any(KtransposeU == 0) or - np.any(np.isnan(u)) or np.any(np.isnan(v)) or - np.any(np.isinf(u)) or np.any(np.isinf(v))): + if (np.any(KtransposeU == 0) + or np.any(np.isnan(u)) or np.any(np.isnan(v)) + or np.any(np.isinf(u)) or np.any(np.isinf(v))): # we have reached the machine precision # come back to previous solution and quit loop print('Warning: numerical errors at iteration', cpt) @@ -683,13 +683,13 @@ def sinkhorn_stabilized(a, b, M, reg, numItermax=1000, tau=1e3, stopThr=1e-9, def get_K(alpha, beta): """log space computation""" - return np.exp(-(M - alpha.reshape((na, 1)) - - beta.reshape((1, nb))) / reg) + return np.exp(-(M - alpha.reshape((na, 1)) + - beta.reshape((1, nb))) / reg) def get_Gamma(alpha, beta, u, v): """log space gamma computation""" - return np.exp(-(M - alpha.reshape((na, 1)) - beta.reshape((1, nb))) / - reg + np.log(u.reshape((na, 1))) + np.log(v.reshape((1, nb)))) + return np.exp(-(M - alpha.reshape((na, 1)) - beta.reshape((1, nb))) + / reg + np.log(u.reshape((na, 1))) + np.log(v.reshape((1, nb)))) # print(np.min(K)) @@ -899,8 +899,8 @@ def sinkhorn_epsilon_scaling(a, b, M, reg, numItermax=100, epsilon0=1e4, numInne def get_K(alpha, beta): """log space computation""" - return np.exp(-(M - alpha.reshape((na, 1)) - - beta.reshape((1, nb))) / reg) + return np.exp(-(M - alpha.reshape((na, 1)) + - beta.reshape((1, nb))) / reg) # print(np.min(K)) def get_reg(n): # exponential decreasing diff --git a/ot/externals/funcsigs.py b/ot/externals/funcsigs.py index c73fdc9..106bde7 100644 --- a/ot/externals/funcsigs.py +++ b/ot/externals/funcsigs.py @@ -126,8 +126,8 @@ def signature(obj): new_params[arg_name] = param.replace(default=arg_value, _partial_kwarg=True) - elif (param.kind not in (_VAR_KEYWORD, _VAR_POSITIONAL) and - not param._partial_kwarg): + elif (param.kind not in (_VAR_KEYWORD, _VAR_POSITIONAL) + and not param._partial_kwarg): new_params.pop(arg_name) return sig.replace(parameters=new_params.values()) @@ -333,11 +333,11 @@ class Parameter(object): raise TypeError(msg) def __eq__(self, other): - return (issubclass(other.__class__, Parameter) and - self._name == other._name and - self._kind == other._kind and - self._default == other._default and - self._annotation == other._annotation) + return (issubclass(other.__class__, Parameter) + and self._name == other._name + and self._kind == other._kind + and self._default == other._default + and self._annotation == other._annotation) def __ne__(self, other): return not self.__eq__(other) @@ -372,8 +372,8 @@ class BoundArguments(object): def args(self): args = [] for param_name, param in self._signature.parameters.items(): - if (param.kind in (_VAR_KEYWORD, _KEYWORD_ONLY) or - param._partial_kwarg): + if (param.kind in (_VAR_KEYWORD, _KEYWORD_ONLY) + or param._partial_kwarg): # Keyword arguments mapped by 'functools.partial' # (Parameter._partial_kwarg is True) are mapped # in 'BoundArguments.kwargs', along with VAR_KEYWORD & @@ -402,8 +402,8 @@ class BoundArguments(object): kwargs_started = False for param_name, param in self._signature.parameters.items(): if not kwargs_started: - if (param.kind in (_VAR_KEYWORD, _KEYWORD_ONLY) or - param._partial_kwarg): + if (param.kind in (_VAR_KEYWORD, _KEYWORD_ONLY) + or param._partial_kwarg): kwargs_started = True else: if param_name not in self.arguments: @@ -432,9 +432,9 @@ class BoundArguments(object): raise TypeError(msg) def __eq__(self, other): - return (issubclass(other.__class__, BoundArguments) and - self.signature == other.signature and - self.arguments == other.arguments) + return (issubclass(other.__class__, BoundArguments) + and self.signature == other.signature + and self.arguments == other.arguments) def __ne__(self, other): return not self.__eq__(other) @@ -612,9 +612,9 @@ class Signature(object): raise TypeError(msg) def __eq__(self, other): - if (not issubclass(type(other), Signature) or - self.return_annotation != other.return_annotation or - len(self.parameters) != len(other.parameters)): + if (not issubclass(type(other), Signature) + or self.return_annotation != other.return_annotation + or len(self.parameters) != len(other.parameters)): return False other_positions = dict((param, idx) @@ -635,8 +635,8 @@ class Signature(object): except KeyError: return False else: - if (idx != other_idx or - param != other.parameters[param_name]): + if (idx != other_idx + or param != other.parameters[param_name]): return False return True @@ -688,8 +688,8 @@ class Signature(object): raise TypeError(msg) parameters_ex = (param,) break - elif (param.kind == _VAR_KEYWORD or - param.default is not _empty): + elif (param.kind == _VAR_KEYWORD + or param.default is not _empty): # That's fine too - we have a default value for this # parameter. So, lets start parsing `kwargs`, starting # with the current parameter @@ -755,8 +755,8 @@ class Signature(object): # if it has a default value, or it is an '*args'-like # parameter, left alone by the processing of positional # arguments. - if (not partial and param.kind != _VAR_POSITIONAL and - param.default is _empty): + if (not partial and param.kind != _VAR_POSITIONAL + and param.default is _empty): raise TypeError('{arg!r} parameter lacking default value'. format(arg=param_name)) diff --git a/ot/gpu/bregman.py b/ot/gpu/bregman.py index 978b307..3031ed9 100644 --- a/ot/gpu/bregman.py +++ b/ot/gpu/bregman.py @@ -146,9 +146,9 @@ def sinkhorn_knopp(a, b, M, reg, numItermax=1000, stopThr=1e-9, v = np.divide(b, KtransposeU) u = 1. / np.dot(Kp, v) - if (np.any(KtransposeU == 0) or - np.any(np.isnan(u)) or np.any(np.isnan(v)) or - np.any(np.isinf(u)) or np.any(np.isinf(v))): + if (np.any(KtransposeU == 0) + or np.any(np.isnan(u)) or np.any(np.isnan(v)) + or np.any(np.isinf(u)) or np.any(np.isinf(v))): # we have reached the machine precision # come back to previous solution and quit loop print('Warning: numerical errors at iteration', cpt) diff --git a/ot/stochastic.py b/ot/stochastic.py index ec53015..1376884 100644 --- a/ot/stochastic.py +++ b/ot/stochastic.py @@ -418,8 +418,8 @@ def solve_semi_dual_entropic(a, b, M, reg, method, numItermax=10000, lr=None, return None opt_alpha = c_transform_entropic(b, M, reg, opt_beta) - pi = (np.exp((opt_alpha[:, None] + opt_beta[None, :] - M[:, :]) / reg) * - a[:, None] * b[None, :]) + pi = (np.exp((opt_alpha[:, None] + opt_beta[None, :] - M[:, :]) / reg) + * a[:, None] * b[None, :]) if log: log = {} @@ -520,15 +520,15 @@ def batch_grad_dual(a, b, M, reg, alpha, beta, batch_size, batch_alpha, arXiv preprint arxiv:1711.02283. ''' - G = - (np.exp((alpha[batch_alpha, None] + beta[None, batch_beta] - - M[batch_alpha, :][:, batch_beta]) / reg) * + G = - (np.exp((alpha[batch_alpha, None] + beta[None, batch_beta] + - M[batch_alpha, :][:, batch_beta]) / reg) * a[batch_alpha, None] * b[None, batch_beta]) grad_beta = np.zeros(np.shape(M)[1]) grad_alpha = np.zeros(np.shape(M)[0]) - grad_beta[batch_beta] = (b[batch_beta] * len(batch_alpha) / np.shape(M)[0] + - G.sum(0)) - grad_alpha[batch_alpha] = (a[batch_alpha] * len(batch_beta) / - np.shape(M)[1] + G.sum(1)) + grad_beta[batch_beta] = (b[batch_beta] * len(batch_alpha) / np.shape(M)[0] + + G.sum(0)) + grad_alpha[batch_alpha] = (a[batch_alpha] * len(batch_beta) + / np.shape(M)[1] + G.sum(1)) return grad_alpha, grad_beta @@ -702,8 +702,8 @@ def solve_dual_entropic(a, b, M, reg, batch_size, numItermax=10000, lr=1, opt_alpha, opt_beta = sgd_entropic_regularization(a, b, M, reg, batch_size, numItermax, lr) - pi = (np.exp((opt_alpha[:, None] + opt_beta[None, :] - M[:, :]) / reg) * - a[:, None] * b[None, :]) + pi = (np.exp((opt_alpha[:, None] + opt_beta[None, :] - M[:, :]) / reg) + * a[:, None] * b[None, :]) if log: log = {} log['alpha'] = opt_alpha diff --git a/setup.cfg b/setup.cfg index b2a2415..24512d2 100644 --- a/setup.cfg +++ b/setup.cfg @@ -3,4 +3,4 @@ description-file = README.md [flake8] exclude = __init__.py -ignore = E265,E501 +ignore = E265,E501,W605 -- cgit v1.2.3