The transpose of any expression can be obtained using the syntaxĮxpr.T. The operators + and - are always affine functions. Operators The infix operators +, -,, /, are treated as functions. CVXPY uses the function information in this section and the DCP rules to mark expressions with a sign and curvature. O dimensional : () 1 dimensional : ( 1 ,) Transpose ¶ This section of the tutorial describes the atomic functions that can be applied to CVXPY expressions. Indexing drops dimensions while slicing preserves dimensions. While expr selects both rows and columns. If expr is a matrix, then expr selects rows, More generally, expr selects every kthĮlement of expr, starting at i and ending at j-1. Indexing in CVXPY follows exactly the same semantics as NumPy ndarrays.įor example, if expr has shape (5,) then expr gives the second entry. * should be matrix-scalar and vector-scalar multiplicationĮlementwise multiplication can be applied with the multiply function. Starting with Python 3.5, users can writeĮxpr1 expr2 for matrix multiplication and dot products.Īs of CVXPY version 1.1, we are adopting a new should be used for matrix-matrix and matrix-vector multiplication, Historically, CVXPY used expr1 * expr2 to denote matrix multiplication. The vast majority of users will need only. CVXPY has seven types of constraints: non-positive, equality or zero, positive semidefinite, second-order cone, exponential cone, 3-dimensional power cones, and N-dimensional power cones. The expression expr1*expr2 is affine inĬVXPY when one of the expressions is constant, and expr1/expr2 is affine A constraint is an equality or inequality that restricts the domain of an optimization problem. The infix operators +, -, *, /, are treated as functions.
The DCP rules to mark expressions with a sign and curvature. you convert wyjscie to a list, but this list will be a nested list because original dim is 2d. CVXPY uses the function information in this section and H is a numpy-array with dtypefloat as its default. ValueError: setting an array element with a sequence.This section of the tutorial describes the atomic functions that can be applied > 83 return array(a, dtype, copy=False, order=order) ~\AppData\Roaming\Python\Python37\site-packages\numpy\core\_asarray.py in asarray(a, dtype, order) import numpy as np import matplotlib.pyplot as plt import cvxpy as cp from cvxpy import np.ed (6201) mean1 -1, -1 mean2 1, 1 cov 1, 0.25, 0.25, 1 x np.random.multivariatenormal (mean1, cov, 200) y np.random.multivariatenormal (mean2, cov, 200) plt.scatter (x :,0,x :,1,color'blue') plt.scatter (y :,0,y. > 98 trunc = np.asarray(trunc, dtype=dtype)ġ00 raise ValueError('Shape of sample %s of sequence at position %s '
~\AppData\Roaming\Python\Python37\site-packages\keras_preprocessing\sequence.py in pad_sequences(sequences, maxlen, dtype, padding, truncating, value) > 158 padding=padding, truncating=truncating, value=value)
~\AppData\Roaming\Python\Python37\site-packages\tensorflow\python\keras\preprocessing\sequence.py in pad_sequences(sequences, maxlen, dtype, padding, truncating, value)ġ57 sequences, maxlen=maxlen, dtype=dtype, > 4 input_padding = tf._sequences(inputList, maxlen = 100, dtype='float32', padding='post')ĥ stopper = tf.(monitor='loss', patience=3)Ħ history = rnnModel.fit(x=input_padding, y=labelList, batch_size = 1000, epochs = 100, verbose = 2, callbacks =, validation_split = 0.2) ValueError Traceback (most recent call last)Ģ inputList = np.asarray(train_())ģ labelList = np.asarray(train_()) The above exception was the direct cause of the following exception: TypeError: only size-1 arrays can be converted to Python scalars TypeError Traceback (most recent call last) Stopper = tf.(monitor='loss', patience=3) Input_padding = tf._sequences(, maxlen = 100, dtype='float32', padding='post') train_df2 = train_df2.sample(frac = 1).reset_index(drop = True) Train_df2 is formatted like this (shows only one row)
#SETTING AN ARRAY ELEMENT WITH A SEQUENCE CVXPY CODE#
I am just confused why the code below is giving me a value error and saying that setting a pad_sequences parameter to a sequence gives of an error when the documentation says that a sequence is indeed required. I am trying to run the following code, however, I got ValueError: setting an array element with a sequence. ValueError: setting an array element with a sequence.
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