multidimensional-array

问题 Having a 4-D numpy.ndarray, e.g. myarr = np.random.rand(10,4,3,2) dims={'time':1:10,'sub':1:4,'cond':['A','B','C'],'measure':['meas1','meas2']} But with possible higher dimensions. How can I create a pandas.dataframe with multiindex, just passing the dimensions as indexes, without further manual adjustments (reshaping the ndarray into 2D shape)? I can't wrap my head around the reshaping, not even really in 3 dimensions quite yet, so I'm searching for an 'automatic' method if possible. What

问题 This question already has answers here : How do you split a list into evenly sized chunks? (63 answers) Closed 7 years ago . I have a list [1,2,3,4,5,6,7,8] I want to convert this as [[1,2,3,4][5,6,7,8]] in python. Can somebody help me with this 回答1: To take an input: def chunks(l, n): return [l[i:i+n] for i in range(0, len(l), n)] mylist = [1,2,3,4,5,6,7,8] while 1: try: size = int(raw_input('What size? ')) # Or input() if python 3.x break except ValueError: print "Numbers only please" print

问题 This question already has answers here : How do you split a list into evenly sized chunks? (63 answers) Closed 7 years ago . I have a list [1,2,3,4,5,6,7,8] I want to convert this as [[1,2,3,4][5,6,7,8]] in python. Can somebody help me with this 回答1: To take an input: def chunks(l, n): return [l[i:i+n] for i in range(0, len(l), n)] mylist = [1,2,3,4,5,6,7,8] while 1: try: size = int(raw_input('What size? ')) # Or input() if python 3.x break except ValueError: print "Numbers only please" print

问题 I am working on my first full program with two weeks of programming under my belt, and have run into a road block I can't seem to figure out. I am making a connect 4 game, and have started by building the logic in JavaScript before pushing to the DOM. I have started to make it with cell objects made by a constructor, that are then pushed into a game object in the form of a 2D array. I have managed to create a function that makes the play each time, and changes the value of the cell at the

问题 I am working on my first full program with two weeks of programming under my belt, and have run into a road block I can't seem to figure out. I am making a connect 4 game, and have started by building the logic in JavaScript before pushing to the DOM. I have started to make it with cell objects made by a constructor, that are then pushed into a game object in the form of a 2D array. I have managed to create a function that makes the play each time, and changes the value of the cell at the

问题 Essentially I'm not sure how to store a 3D data structure for the fastest access possible as I'm not sure what is going on under the hood for multi-dimensional arrays. NOTE: The arrays will be a constant and known size each and every time, and each element will be exactly 16 bits. Option one is to have a multi-dimension array data[16, 16, 16] and simply access via data[x, y, z] option two is to have a single dimension array data[16 * 16 * 16] and access via data[x + (y * 16) + (z * 16 * 16)]

问题 Essentially I'm not sure how to store a 3D data structure for the fastest access possible as I'm not sure what is going on under the hood for multi-dimensional arrays. NOTE: The arrays will be a constant and known size each and every time, and each element will be exactly 16 bits. Option one is to have a multi-dimension array data[16, 16, 16] and simply access via data[x, y, z] option two is to have a single dimension array data[16 * 16 * 16] and access via data[x + (y * 16) + (z * 16 * 16)]

问题 Consider the following exercise in Numpy array broadcasting. import numpy as np v = np.array([[1.0, 2.0]]).T # column array A2 = np.random.randn(2,10) # 2D array A3 = np.random.randn(2,10,10) # 3D v * A2 # works great # causes error: v * A3 # error I know the Numpy rules for broadcasting, and I'm familiar with bsxfun functionality in Matlab. I understand why attempting to broadcast a (2,1) array into a (2,N,N) array fails, and that I have to reshape the (2,1) array into a (2,1,1) array before

问题 Consider the following exercise in Numpy array broadcasting. import numpy as np v = np.array([[1.0, 2.0]]).T # column array A2 = np.random.randn(2,10) # 2D array A3 = np.random.randn(2,10,10) # 3D v * A2 # works great # causes error: v * A3 # error I know the Numpy rules for broadcasting, and I'm familiar with bsxfun functionality in Matlab. I understand why attempting to broadcast a (2,1) array into a (2,N,N) array fails, and that I have to reshape the (2,1) array into a (2,1,1) array before

问题 I wonder, can binary search be applied on a 2D array ? What would the conditions on the array be? Sorted on 2D?? What would be the time complexity for it? How would the algorithm change the boundary of the search (minX,maxX,minY,maxY) ?? Edit: Binary Search on 1D maintains 2 pointers minX and maxX .. It selects the middle index (minX+maxX)/2 and compare it with the search value, if greater then change maxX , else change minX ... until minX>=maxX Pseudo code for normal binary seacrh: min := 1;