:return: 解密后的数组 """# 读取加密后的文件数据withopen(file_path,'rb')asf:iv=f.read(16)# 读取初始化向量encrypted_data=f.read()# 创建 AES 解密器cipher=AES.new(key,AES.MODE_CBC,iv=iv)# 进行数据解密decrypted_data=unpad(cipher.decrypt(encrypted_data),AES.block_size)# 恢复数组original...
parts=[]withopen(file_path,'rb')asf:part_number=1offset=0whileoffset<file_size:# 读取分块数据data=f.read(self.part_size)md5=self._calc_md5(data)# 上传分块result=self.bucket.upload_part(object_name,upload_id,part_number,data)parts.append(oss2.models.PartInfo(part_number,result.etag,md5...
The diagonal and diag functions return readonly views. Special scalar float values don’t cause upcast to double anymore Percentile output changes ndarray.tofile exception type Invalid fill value exceptions Polynomial Classes no longer derived from PolyBase Using numpy.random.binomial may change...
load(file,mmap_mode=None,allow_pickle=True,fix_imports=True,encoding='ASCII') file:类文件对象或字符串格式,要读取的文件或字符串,必填,类文件对象需要支持seek()和read()方法。 mmap_mode:内存映射模式,值域为:None、'r+'、'r'、'w+'、'c',选填。 allow_pickle:布尔型,选填,是否允许加载存储在npy...
例如, 以下代码演示: from numpy import * TEST_FILE = f"{os.path.dirname(__file__)}\\TEST.bin" FILE = open(TEST_FILE, 'wb') FILE.write(bytes([1, 2, 3, 4, 5, 6, 7, 8, 9])) FILE.close() FILE = open(TEST_FILE, 'rb') print(FILE.read()) FILE.close() 输出结果为:...
["encoding"]) as handle: doc = handle.read() # 定义不同类型的分词器 tokenizer_dict = { "words": tokenize_words, "characters": tokenize_chars, "whitespace": tokenize_whitespace, "bytes": tokenize_bytes_raw, } # 根据超参数选择相应的分词器 tokenizer = tokenizer_dict[H["tokenizer"]] # ...
>>> data = pd.read_csv('pd.csv') 你还可以使用 NumPy 的savetxt方法保存你的数组。 >>> np.savetxt('np.csv', a, fmt='%.2f', delimiter=',', header='1, 2, 3, 4') 如果在命令行中使用,可以使用类似以下的命令随时读取已保存的 CSV 文件: ...
The default value is ‘bytes’. New in version 1.14.0. max_rows : int, optional Read max_rows lines of content after skiprows lines. The default is to read all the lines. New in version 1.16.0. Returns: out : ndarray Data read from the text file. 例子: >>> from io import ...
Scipy.cluster%matplotlib inlineimport matplotlib.pyplot as plt## Import ndimage to read the imagefrom scipy import ndimage## Import cluster for clustering algorithmsfrom scipy import cluster## Read the imageimage = ndimage.imread("cluster_test_image.jpg")## Image is 1000x1000 pixels and it has ...
如果想操作更加复杂的.txt文件,可以去学习一下genfromtxt()函数。 导入导出 CSV 文件 CSV 文件非常简便易读。操作 CSV 文件就不得不提到另一个第三方科学计算库 Pandas 。 >>> import pandas as pd # 假设文件中每一列数据都具有相同的类型 >>> x = pd.read_csv('music.csv', header=0).values ...