我们从Python开源项目中，提取了以下14个代码示例，用于说明如何使用numpy.sometrue()。
def UpdatePointLabel(self, mDataDict): """Updates the pointLabel point on screen with data contained in mDataDict. mDataDict will be passed to your function set by SetPointLabelFunc. It can contain anything you want to display on the screen at the scaledXY point you specify. This function can be called from parent window with onClick, onMotion events etc. """ if self.last_PointLabel != None: # compare pointXY if np.sometrue(mDataDict["pointXY"] != self.last_PointLabel["pointXY"]): # closest changed self._drawPointLabel(self.last_PointLabel) # erase old self._drawPointLabel(mDataDict) # plot new else: # just plot new with no erase self._drawPointLabel(mDataDict) # plot new # save for next erase self.last_PointLabel = mDataDict # event handlers **********************************
def test_fail(self): z = np.array([-1, 0, 1]) res = iscomplex(z) assert_(not np.sometrue(res, axis=0))
def test_nd(self): y1 = [[0, 0, 0], [0, 1, 0], [1, 1, 0]] assert_(np.any(y1)) assert_array_equal(np.sometrue(y1, axis=0), [1, 1, 0]) assert_array_equal(np.sometrue(y1, axis=1), [0, 1, 1])
def adjustHigherOrder(self, evidence, order, maximumDiscount): def criterion(discount): disc = tuple(num.maximum(0.0, discount)) sm = self.modelFactory.sequenceModel(evidence, disc) ll = self.develSample.logLik(sm, self.shallUseMaximumApproximation) crit = - ll \ - sum(num.minimum(discount, 0)) \ + sum(num.maximum(discount - maximumDiscount, 0)) print discount, ll, crit # TESTING return crit initialGuess = self.discounts[-1] firstDirection = None if initialGuess is None: initialGuess = 0.1 * num.arange(1, order+2, dtype=num.float64) elif len(initialGuess) < order+1: oldGuess = initialGuess oldSize = len(initialGuess) initialGuess = num.zeros(order+1, dtype=num.float64) initialGuess[:oldSize] = oldGuess initialGuess[oldSize:] = oldGuess[-1] elif len(initialGuess) > order+1: initialGuess = initialGuess[:order+1] else: previous = self.discounts[-2] if previous is not None and len(previous) == order+1: firstDirection = initialGuess - previous if not num.sometrue(num.abs(firstDirection) > 1e-4): firstDirection = None directions = num.identity(order+1, dtype=num.float64) directions = directions[::-1] if firstDirection is not None: directions = num.concatenate((firstDirection[num.newaxis,:], directions)) directions *= 0.1 print directions # TESTING discount, ll = Minimization.directionSetMinimization( criterion, initialGuess, directions, tolerance=1e-4) discount = num.maximum(0.0, discount) return discount, -ll
