numpy

问题 I have a data frame as shown below B_ID Session no_show cumulative_no_show 1 s1 0.4 0.4 2 s1 0.6 1.0 3 s1 0.2 1.2 4 s1 0.1 1.3 5 s1 0.4 1.7 6 s1 0.2 1.9 7 s1 0.3 2.2 10 s2 0.3 0.3 11 s2 0.4 0.7 12 s2 0.3 1.0 13 s2 0.6 1.6 14 s2 0.2 1.8 15 s2 0.5 2.3 where cumulative_no_show is the cumulative sum of no_show. From the above I would like to create a new column called u_no_show based on below condition. Whenever cumulative_no_show >= 0.8, then subtract 1 from next cumulative_no_show. and so on.

问题 I have a data frame as shown below B_ID Session no_show cumulative_no_show 1 s1 0.4 0.4 2 s1 0.6 1.0 3 s1 0.2 1.2 4 s1 0.1 1.3 5 s1 0.4 1.7 6 s1 0.2 1.9 7 s1 0.3 2.2 10 s2 0.3 0.3 11 s2 0.4 0.7 12 s2 0.3 1.0 13 s2 0.6 1.6 14 s2 0.2 1.8 15 s2 0.5 2.3 where cumulative_no_show is the cumulative sum of no_show. From the above I would like to create a new column called u_no_show based on below condition. Whenever cumulative_no_show >= 0.8, then subtract 1 from next cumulative_no_show. and so on.

问题 I am trying to code a function where it gives me the indexes of where either list_2 or list_3 crosses list_ . So it would give me the points of intersection if there are any in numpy code. I want to get the crosses in order, so the list of indexes have to be formatted so that it would give me a cross in order of list_2 cross, list_3 cross , list_2 cross or list_3 cross, list_2 cross , list_3 cross etc. So if a cross has happened it has to wait for the other array values to cross the list

问题 I am trying to code a function where it gives me the indexes of where either list_2 or list_3 crosses list_ . So it would give me the points of intersection if there are any in numpy code. I want to get the crosses in order, so the list of indexes have to be formatted so that it would give me a cross in order of list_2 cross, list_3 cross , list_2 cross or list_3 cross, list_2 cross , list_3 cross etc. So if a cross has happened it has to wait for the other array values to cross the list

问题 I am trying to code a function where it gives me the indexes of where either list_2 or list_3 crosses list_ . So it would give me the points of intersection if there are any in numpy code. I want to get the crosses in order, so the list of indexes have to be formatted so that it would give me a cross in order of list_2 cross, list_3 cross , list_2 cross or list_3 cross, list_2 cross , list_3 cross etc. So if a cross has happened it has to wait for the other array values to cross the list

问题 I have a 3D np.array arr = np.array([ [ [0, 205, 25], [210, 150, 30], [0, 0, 0], [1, 2, 3], [4, 5, 6], [7, 8, 9] ], [ [0, 255, 0], [255, 40, 0], [0, 0, 200], [7, 8, 9], [10, 11, 12], [120, 51, 58] ], [ [0, 0, 30], [0, 40, 0], [200, 100, 20], [12, 13, 14], [15, 16, 17], [13, 78, 84], ], [ [0, 205, 25], [210, 150, 30], [0, 0, 0], [1, 2, 3], [4, 5, 6], [7, 8, 9] ], [ [0, 255, 0], [255, 40, 0], [0, 0, 200], [7, 8, 9], [10, 11, 12], [120, 51, 58] ], [ [0, 0, 30], [0, 40, 0], [200, 100, 20], [12,

问题 I have a 3D np.array arr = np.array([ [ [0, 205, 25], [210, 150, 30], [0, 0, 0], [1, 2, 3], [4, 5, 6], [7, 8, 9] ], [ [0, 255, 0], [255, 40, 0], [0, 0, 200], [7, 8, 9], [10, 11, 12], [120, 51, 58] ], [ [0, 0, 30], [0, 40, 0], [200, 100, 20], [12, 13, 14], [15, 16, 17], [13, 78, 84], ], [ [0, 205, 25], [210, 150, 30], [0, 0, 0], [1, 2, 3], [4, 5, 6], [7, 8, 9] ], [ [0, 255, 0], [255, 40, 0], [0, 0, 200], [7, 8, 9], [10, 11, 12], [120, 51, 58] ], [ [0, 0, 30], [0, 40, 0], [200, 100, 20], [12,

问题 I am doing a molecular dynamics simulation. It consists of numerical integration, many for loops, manipulating large NumPy arrays. I have tried to use NumPy function and arrays wherever possible. But the code is still too slow. I thought of using numba jit as a speedup. But it always throws an error message. Here is the code. # -*- coding: utf-8 -*- """ Created on Sat Mar 28 12:10:42 2020 @author: Sandipan """ import numpy as np import matplotlib.pyplot as plt from numba import jit import os

问题 I know that in c we can construct a compound dataset easily using struct type and assign data chunk by chunk. I am currently implementing a similar structure in Python with h5py . import h5py import numpy as np # we create a h5 file f = h5py.File("test.h5") # default is mode "a" # We define a compound datatype using np.dtype dt_type = np.dtype({"names":["image","feature"], "formats":[('<f4',(4,4)),('<f4',(10,))]}) # we define our dataset with 5 instances a = f.create_dataset("test", shape=(5,

问题 I know that in c we can construct a compound dataset easily using struct type and assign data chunk by chunk. I am currently implementing a similar structure in Python with h5py . import h5py import numpy as np # we create a h5 file f = h5py.File("test.h5") # default is mode "a" # We define a compound datatype using np.dtype dt_type = np.dtype({"names":["image","feature"], "formats":[('<f4',(4,4)),('<f4',(10,))]}) # we define our dataset with 5 instances a = f.create_dataset("test", shape=(5,