我想知道如何打开或读取以八度音程保存的二进制文件，扩展名为.SAVE？我试过用MATLAB打开它，使用octave中的'load'函数，但似乎没有任何工作。我正在尝试了解其他人的代码，他们已经在此文件中保存了模拟的输出。
答案 0 :(得分：0)
在load-save.cc中的函数read_binary_data（）之前的注释中简要描述了Octave二进制格式。
您确定该文件是否为＆＃34; Octave二进制格式＆＃34;。文件结束＆＃34; .SAVE＆＃34;可以任意选择，所以这也可以是CSV，gzip压缩......
您可以运行＆＃34; file yourfile.SAFE＆＃34;并粘贴输出或检查文件的第一个字节，如果它们是＆＃34; Octave-1-L＆＃34;或＆＃34; Octave-1-B＆＃34;。
如果你想使用来自GNU Octave之外的其他程序的这些文件，我建议你在Octave中加载它并以其他格式保护它。请参阅＆＃34;帮助保存＆＃34;获取支持的格式列表。
修改 因为最初的海报问：当然你可以从终端使用GNU Octave（不需要GUI，我现在不会在你使用短语＆＃34; octave GUI＆＃34时引用哪个软件部分;，见这里Octave FAQ）。只需为您使用过的平台install instructions on wiki.octave.org安装并运行它。
答案 1 :(得分：0)
用于在python 2/3中读取八度二进制保存文件的代码。
经过测试：
不受支持：
Python代码：
# This code is public domain
from __future__ import print_function
import sys
from collections import OrderedDict
import numpy as np
if sys.version_info[0] > 2:
def tostr(s):
return s.decode('utf8')
def decode(s, encoding='utf8'):
return s.decode(encoding)
STR_ENCODING = 'utf8'
else:
def tostr(s):
return s
def decode(s, encoding='utf8'):
return unicode(s, encoding)
STR_ENCODING = None
DATA_TYPES = {
1: "scalar",
2: "matrix",
3: "complex scalar",
4: "complex matrix",
5: "old_string",
6: "range",
7: "string",
}
TYPE_CODES = {
0: "u1",
1: "u2",
2: "u4",
3: "i1",
4: "i2",
5: "i4",
6: "f4",
7: "f8",
8: "u8",
9: "i8",
}
DTYPES = {k: np.dtype(v) for k, v in TYPE_CODES.items()}
def loadoct(fd, encoding=STR_ENCODING):
"""
Read an octave binary file from the file handle fd, returning
an array of structures. If encoding is not None then convert
strings from bytes to unicode. Default is STR_ENCODING, which
is utf8 for python 3 and None for python 2, yielding arrays
of type str in each dialect.
"""
magic = fd.read(10)
assert(magic == b"Octave-1-L" or magic == b"Octave-1-B")
endian = "<" if magic[-1:] == b"L" else ">"
# Float type is 0: IEEE-LE, 1: IEEE-BE, 2: VAX-D, 3: VAX-G, 4: Cray
# Not used since Octave assumes IEEE format floats.
_float_format = fd.read(1)
len_dtype = np.dtype(endian + "i4")
def read_len():
len_bytes = fd.read(4)
if not len_bytes:
return None
return np.frombuffer(len_bytes, len_dtype)[0]
table = OrderedDict()
while True:
name_length = read_len()
if name_length is None: # EOF
break
name = tostr(fd.read(name_length))
doc_length = read_len()
doc = tostr(fd.read(doc_length)) if doc_length else ''
is_global = bool(ord(fd.read(1)))
data_type = ord(fd.read(1))
if data_type == 255:
type_str = tostr(fd.read(read_len()))
else:
type_str = DATA_TYPES[data_type]
#print("reading", name, type_str)
if type_str.endswith("scalar"):
if type_str == "scalar":
dtype = DTYPES[ord(fd.read(1))]
elif type_str == "complex scalar":
_ = fd.read(1)
dtype = np.dtype('complex128')
elif type_str == "float complex scalar":
_ = fd.read(1)
dtype = np.dtype('complex64')
else:
dtype = np.dtype(type_str[:-7])
dtype = dtype.newbyteorder(endian)
data = np.frombuffer(fd.read(dtype.itemsize), dtype)
table[name] = data[0]
elif type_str.endswith("matrix"):
ndims = read_len()
if ndims < 0:
ndims = -ndims
dims = np.frombuffer(fd.read(4*ndims), len_dtype)
else:
dims = (ndims, read_len())
count = np.prod(dims)
if type_str == "matrix":
dtype = DTYPES[ord(fd.read(1))]
elif type_str == "complex matrix":
_ = fd.read(1)
dtype = np.dtype('complex128')
elif type_str == "float complex matrix":
_ = fd.read(1)
dtype = np.dtype('complex64')
else:
dtype = np.dtype(type_str[:-7])
dtype = dtype.newbyteorder(endian)
data = np.frombuffer(fd.read(count*dtype.itemsize), dtype)
# Note: Use data.copy() to make a modifiable array.
table[name] = data.reshape(dims, order='F')
elif type_str == "old_string":
data = fd.read(read_len())
if encoding is not None:
data = decode(data, encoding)
table[name] = data
elif type_str in ("string", "sq_string"):
nrows = read_len()
if nrows < 0:
ndims = -nrows
dims = np.frombuffer(fd.read(4*ndims), len_dtype)
count = np.prod(dims)
fortran_order = np.frombuffer(fd.read(count), dtype='uint8')
c_order = np.ascontiguousarray(fortran_order.reshape(dims, order='F'))
data = c_order.view(dtype='|S'+str(dims[-1]))
if encoding is not None:
data = np.array([decode(s, encoding) for s in data.flat])
table[name] = data.reshape(dims[:-1])
else:
data = [fd.read(read_len()) for _ in range(nrows)]
if encoding is not None:
data = [decode(s, encoding) for s in data]
table[name] = np.array(data)
else:
raise NotImplementedError("unknown octave type "+type_str)
#print("read %s:%s"%(name, type_str), table[name])
return table
def _dump(filename, encoding=STR_ENCODING):
import gzip
if filename.endswith('.gz'):
with gzip.open(filename, 'rb') as fd:
table = loadoct(fd, encoding)
else:
with open(filename, 'rb') as fd:
table = loadoct(fd, encoding)
for k, v in table.items():
print(k, v)
if __name__ == "__main__":
#_dump(sys.argv[1], encoding='utf8') # unicode
#_dump(sys.argv[1], encoding=None) # bytes
_dump(sys.argv[1]) # str, encoding=STR_ENCODING