想在深度學習程式執行時動態存下來一些引數。

存成Excel檔案檢視方便，就查了幾種方法，做個測試。因為我平常也不怎麼用 Excel，簡單的存取資料就夠了。

xlwt/xlrd庫 存Excel檔案：（如果儲存資料中有字元，那麼寫法還有點小小的變化）

import xlwt

workbook = xlwt.Workbook(encoding='utf-8')
booksheet = workbook.add_sheet('Sheet 1', cell_overwrite_ok=True)
#存第一行cell(1,1)和cell(1,2)
booksheet.write(0,0,34)
booksheet.write(0,1,38)
#存第二行cell(2,1)和cell(2,2)
booksheet.write(1,0,36)
booksheet.write(1,1,39)
#存一行資料
rowdata = [43,56]
for i in range(len(rowdata)):
    booksheet.write(2,i,rowdata[i])
workbook.save('test_xlwt.xls')
 

讀Excel檔案：（同樣是對於數值型別資料）

import xlrd

workbook = xlrd.open_workbook('D:\\Py_exercise\\test_xlwt.xls')
print(workbook.sheet_names())                  #檢視所有sheet
booksheet = workbook.sheet_by_index(0)         #用索引取第一個sheet
booksheet = workbook.sheet_by_name('Sheet 1')  #或用名稱取sheet
#讀單元格資料
cell_11 = booksheet.cell_value(0,0)
cell_21 = booksheet.cell_value(1,0)
#讀一行資料
row_3 = booksheet.row_values(2)
print(cell_11, cell_21, row_3)

>>>34.0 36.0 [43.0, 56.0]
 

from openpyxl import Workbook
 
workbook = Workbook()
booksheet = workbook.active     #獲取當前活躍的sheet,預設是第一個sheet
#存第一行單元格cell(1,1)
booksheet.cell(1,1).value = 6   #這個方法索引從1開始
booksheet.cell("B1").value = 7
#存一行資料
booksheet.append([11,87])
workbook.save("test_openpyxl.xlsx")

from openpyxl import load_workbook
 
workbook = load_workbook('D:\\Py_exercise\\test_openpyxl.xlsx')
#booksheet = workbook.active                #獲取當前活躍的sheet,預設是第一個sheet
sheets = workbook.get_sheet_names()         #從名稱獲取sheet
booksheet = workbook.get_sheet_by_name(sheets[0])

rows = booksheet.rows
columns = booksheet.columns
#迭代所有的行
for row in rows:
    line = [col.value for col in row]

#通過座標讀取值
cell_11 = booksheet.cell('A1').value
cell_11 = booksheet.cell(row=1, column=1).value
 

其實如果對儲存格式沒有要求的話，我覺得存成 csv檔案 也挺好的：

import pandas as pd

csv_mat = np.empty((0,2),float)
csv_mat = np.append(csv_mat, [[43,55]], axis=0)
csv_mat = np.append(csv_mat, [[65,67]], axis=0)
csv_pd = pd.DataFrame(csv_mat)
csv_pd.to_csv("test_pd.csv", sep=',', header=False, index=False)

import pandas as pd

filename = "D:\\Py_exercise\\test_pd.csv"
csv_data = pd.read_csv(filename, header=None)
csv_data = np.array(csv_data, dtype=float)