我有一个数字列表,需要转换为 45 x 45 数组中的浮点数。
gauss_matrix = [list of 2025 float numbers]
mat_template = np.zeros([45, 45])
for rows in np.arange(45):
for columns in np.arange(45):
mat_template[rows, columns] = float(gauss_matrix[np.arange(2025)])
是否从第 0 行开始,循环遍历第 0-44 列。然后从第 2 行开始,循环遍历第 0-44 列,依此类推?
已解决的代码:(感谢您的帮助!)
with open('gaussfilter.csv', 'r+') as gauss: # Let's me read and write gaussfilter.csv
GaussFilterData = gauss.readlines() # Reads the lines of the csv file
# print("GaussFilterData: \n", GaussFilterData)
GaussList = [] # Empty list which will be used to append values to from the csv file
# print("GaussList 1: \n", GaussMatrix)
for lines in GaussFilterData: # Loops through each row of data in gaussfilter.csv
# print("lines: \n", lines)
for row in np.arange(45): # Looping through each row and splitting up the list by commas, while converting each value to a float and not a string
GaussList.append(float(lines.split(',')[row])) # Appending each row to GaussList
# print("\nGaussList 2: \n", GaussList)
# Making the array of values from GaussList
gauss = np.zeros([45, 45]) # Matrix of zeros, the zeros are placeholders for the values in GaussList
# print("gauss: \n", gauss)
Counter = -1 # Counter has to start at -1 so that it begins at 0 when referring to row 0 and column 0
for rows in np.arange(45): # Loop through rows 0 - 44
for columns in np.arange(45): # As we are looping through row 0, loop through all 45 columns
Counter = Counter + 1 # Counter keeps track of the number of cells in the matrix (2025)
gauss[rows][columns] = GaussList[Counter]
print("gauss array: \n", gauss)
首先请不要使用'list'。因此,我将其更改为my_list。
您可以使用“np.array()”创建一个数组,并且可以使用可选的“dtype”标志指定数据类型。
>>> import numpy as np
>>> my_list = [1.5, 2.5, 3.5]
>>> my_array = np.array(my_list,dtype=" ")
您始终可以使用以下方法检查您的数据类型:
>>> my_array.dtype
dtype('float64')
将
dtype
的 GaussMatrix
设置为 np.float64
怎么样?
GaussMatrix = np.array(GaussMatrix, dtype=np.float64)