Conditional moment test. X is a flat numpy array. """betahat, alphahat, shat = ar1_functions.fit(X) n = len(X) xL = X[:(n-1)]# All but the last onexF = X[1:]# All but the first oneZ = (xF - betahat - alphahat * xL)**2XX = sm.add_constant(xL) out = sm.OLS...
deftest_manova_no_formula():# Same as previous test only skipping formula interfaceexog =add_constant(pd.get_dummies(X[['Loc']], drop_first=True)) endog = X[['Basal','Occ','Max']] mod = MANOVA(endog, exog) intercept = np.zeros((1,3)) intercept[0,0] =1loc = np.zeros((2...
to_numpy_array(), self.mp2_initial_point ) @@ -293,7 +293,7 @@ def test_vqe_ucc_factory_with_reps(self): solver = VQEUCCFactory(Estimator(), ansatz, SLSQP()) calc = GroundStateEigensolver(self.qubit_converter, solver) res = calc.solve(self.electronic_structure_problem) # pylint:...
/bin/bash#Description: Verify the numpy backend integration for ZBL model#Test 1: Check for numpy-specific implementationsecho"Checking for numpy backend implementations..."rg -l"numpy"--type py#Test 2: Look for other ZBL-related filesecho"Checking for other ZBL-related files..."fd -e py ...
logaddexp( self.kde_constant + kde_logliks, self.uniform_constant + fix_lls ) return logliks Example #20Source File: test_umath.py From pySINDy with MIT License 5 votes def test_logaddexp_values(self): x = [1, 2, 3, 4, 5] y = [5, 4, 3, 2, 1] z = [6, 6, 6, ...
import numpy as np import tensorflow as tf a=np.array([1,2,3]) b=tf.constant([2]) c=a-b d=tf.add(a,b) e=b.numpy() A、a是NumPy数组,b,c,d,e都是TensorFlow张量 B、b是TensorFlow张量,其他都是NumPy数组 C、a,b,c,d,e中有3个NumPy数组 D、a,b,c,d,e中有3个TensorFlow张量 点...
head: numpy array - [num_classes] Weighting the loss of each class Optional: Prioritize some classes Returns: loss: Loss tensor of type float. """ with tf.name_scope('loss'): logits = tf.reshape(logits, (-1, num_classes)) epsilon = tf.constant(value=1e-4) logits = logits + ...
[::-1] # HWC to CHW, BGR to RGB img = np.ascontiguousarray(img) return path, img, img0, self.cap, s def new_video(self, path): self.frame = 0 self.cap = cv2.VideoCapture(path) self.frames = int(self.cap.get(cv2.CAP_PROP_FRAME_COUNT)) def __len__(self): return self....
PySpark SQL functions lit() and typedLit() are used to add a new column to DataFrame by assigning a literal or constant value. Both these functions return
4. 使用tf.convert_to_tensor(x) 将数据转换为tensorflow格式 参数说明:x表示输入的参数为其他类型的 代码:下面将np.array格式的数据转换为tensor格式,并使用sess.run进行运行 #4.使用tf.convert_to_tensor将数据转换为tensorimportnumpy as np x= np.array([1, 2, 3]) ...