Convert string to ndarray in python - python

I am reading a stream of data from an A-D converter via a socket from Python; the data come in as raw bytes. I want to format these bytes as int32 and place them into an ndarray. The read process looks something like this:
def datarecv():
global msgbuf
binlen = BURSTLEN + 4
while len(msgbuf) < binlen:
msgbuf = msgbuf + socket.recv(4096)
reply = msgbuf[0:binlen]
msgbuf = msgbuf[binlen:]
# each recv comes with a 4 byte header that I throw away...
return reply[4:]
The following is used successfully to write the received data to a file:
with open(filename, "wb') as f:
bytesremaining = framesize
for i in range(lines):
f.write(datarecv()[0:min(linesize, bytesremaining)])
bytesremaining -= linesize
I can then read back the file with something like this:
>>> data = numpy.fromfile(filename, dtype='int32')
>>> type(data)
<type 'numpy.ndarray'>
So my data variable is the format I'm looking for, I.E.
>>> data[1:10]
array([4214234234, 2342342342, 2342342342, 34534535, 345345353, 5675757,
2142423424, 35334535, 35353535, 4754745754], dtype=int32)
** BUT ** I want to omit the intermediate step of writing to a file. After I read in the raw stream of data I want to make it an ndarray so that I can manipulate the data. I can change the line from
f.write(datarecv()[0:min(linesize, bytesremaining)])
to
bigbuf = bigbuf + datarecv()[0:min(linesize, bytesremaining)]
and then I end up with a big string. It's a string of raw bytes (not ASCII) which I have to convert to 32 bit integers. I'm hung up on this last step. I hope this makes sense what I'm asking. Thanks.


You can convert bigbuf to an array with numpy.fromstring
For example:
In [21]: bigbuf = "\1\0\0\0\2\0\0\0"
In [22]: fromstring(bigbuf, dtype=np.int32)
Out[22]: array([1, 2], dtype=int32)

Related

Create Numpy array from list of arbitrary sized bites

How can I create a numpy array from a python list of bytes objects of an arbitrary (but known) size?
Example:
size = 10
byte_list = [np.random.default_rng().bytes(size) for i in range(100)]
numpy_array = # make array from byte_list
# do something with the array
test_vals = np.random.default_rng().choice(numpy_array, size=10)
I tried to do something like this, but got an error that it didn't understand 'B10' as a data type.
numpy_array = np.fromiter(byte_list, dtype=np.dtype(f'B{size}'), count=100)

I think you should use S dtype and not B
numpy_array = np.fromiter(byte_list, dtype=np.dtype(f'S{size}'), count=100)
# HERE --^
# Unsigned byte (only one)
>>> np.dtype('B')
dtype('uint8')
# Byte string
>>> np.dtype('S10')
dtype('S10')

Problems when I write np array to binary file, new file is only half of the original one

I am trying to remove top 24 lines of a raw file, so I opened the original raw file(let's call it raw1.raw) and converted it to nparray, then I initialized a new array and remove the top24 lines, but after writing new array to the new binary file(raw2.raw), I found raw2 is 15.2mb only while the original file raw1.raw is like 30.6mb, my code:
import numpy as np
import imageio
import rawpy
import cv2
def ave():
fd = open('raw1.raw', 'rb')
rows = 3000 #around 3000, not the real rows
cols = 5100 #around 5100, not the real cols
f = np.fromfile(fd, dtype=np.uint8,count=rows*cols)
I_array = f.reshape((rows, cols)) #notice row, column format
#print(I_array)
fd.close()
im = np.zeros((rows - 24 , cols))
for i in range (len(I_array) - 24):
for j in range(len(I_array[i])):
im[i][j] = I_array[i + 24][j]
#print(im)
newFile = open("raw2.raw", "wb")
im.astype('uint8').tofile(newFile)
newFile.close()
if __name__ == "__main__":
ave()
I tried to use im.astype('uint16') when write in the binary file, but the value would be wrong if I use uint16.

There must clearly be more data in your 'raw1.raw' file that you are not using. Are you sure that file wasn't created using 'uint16' data and you are just pulling out the first half as 'uint8' data? I just checked the writing of random data.
import os, numpy as np
x = np.random.randint(0,256,size=(3000,5100),dtype='uint8')
x.tofile(open('testfile.raw','w'))
print(os.stat('testfile.raw').st_size) #I get 15.3MB.
So, 'uint8' for a 3000 by 5100 clearly takes up 15.3MB. I don't know how you got 30+.
############################ EDIT #########
Just to add more clarification. Do you realize that dtype does nothing more than change the "view" of your data? It doesn't effect the actual data that is saved in memory. This also goes for data that you read from a file. Take for example:
import numpy as np
#The way to understand x, is that x is taking 12 bytes in memory and using
#that information to hold 3 values. The first 4 bytes are the first value,
#the second 4 bytes are the second, etc.
x = np.array([1,2,3],dtype='uint32')
#Change x to display those 12 bytes at 6 different values. Doing this does
#NOT change the data that the array is holding. You are only changing the
#'view' of the data.
x.dtype = 'uint16'
print(x)
In general (there are few special cases), changing the dtype doesn't change the underlying data. However, the conversion function .astype() does change the underlying data. If you have any array of 12 bytes viewed as 'int32' then running .astype('uint8') will take each entry (4 bytes) and covert it (known as casting) to a uint8 entry (1 byte). The new array will only have 3 bytes for the 3 entries. You can see this litterally:
x = np.array([1,2,3],dtype='uint32')
print(x.tobytes())
y = x.astype('uint8')
print(y.tobytes())
So, when we say that a file is 30mb, we mean that the file has (minus some header information) is 30,000,000 bytes which are exactly uint8s. 1 uint8 is 1 byte. If any array has 6000by5100 uint8s (bytes), then the array has 30,600,000 bytes of information in memory.
Likewise, if you read a file (DOES NOT MATTER THE FILE) and write np.fromfile(,dtype=np.uint8,count=15_300_000) then you told python to read EXACTLY 15_300_000 bytes (again 1 byte is 1 uint8) of information (15mb). If your file is 100mb, 40mb, or even 30mb, it would be completely irrelevant because you told python to only read the first 15mb of data.

Why python has different types of bytes

I have two variables, one is b_d, the other is b_test_d.
When I type b_d in the console, it shows:
b'\\\x8f\xc2\xf5(\\\xf3?Nb\x10X9\xb4\x07#\x00\x00\x00\x00\x00\x00\xf0?'
when I type b_test_d in the console, it shows:
b'[-2.1997713216,-1.4249271187,-1.1076795391,1.5224958034,-0.1709796203,0.3663875698,0.14846441,-0.7415930061,-1.7602231949,0.126605689,0.6010934792,-0.466415358,1.5675525816,1.00836295,1.4332792992,0.6113384254,-1.8008540571,-0.9443408896,1.0943670356,-1.0114642686,1.443892627,-0.2709427287,0.2990462512,0.4650133591,0.2560791327,0.2257600462,-2.4077429827,-0.0509983213,1.0062187148,0.4315075795,-0.6116110033,0.3495131413,-0.3249903375,0.3962305931,-0.1985757285,1.165792433,-1.1171953063,-0.1732557874,-0.3791600654,-0.2860519953,0.7872658859,0.217728374,-0.4715179983,-0.4539613811,-0.396353657,1.2326862425,-1.3548659354,1.6476230786,0.6312713442,-0.735444661,-0.6853447369,-0.8480631975,0.9538606574,0.6653542368,-0.2833696021,0.7281604648,-0.2843872095,0.1461980484,-2.3511731773,-0.3118047948,-1.6938613893,-0.0359659687,-0.5162134311,-2.2026641552,-0.7294895084,0.7493073213,0.1034096968,0.6439803068,-0.2596155272,0.5851323455,1.0173285542,-0.7370464113,1.0442954406,-0.5363832595,0.0117795359,0.2225617514,0.067571974,-0.9154681906,-0.293808596,1.3717113798,0.4919516922,-0.3254944005,1.6203744532,-0.1810222279,-0.6111596457,1.344064259,-0.4596893179,-0.2356197144,0.4529942046,1.6244603294,0.1849995925,0.6223061217,-0.0340662398,0.8365900535,-0.6804201929,0.0149665385,0.4132453788,0.7971962667,-1.9391525531,0.1440486871,-0.7103617816,0.9026539637,0.6665798363,-1.5885073458,1.4084493329,-1.397040825,1.6215697667,1.7057148522,0.3802647045,-0.4239271483,1.4773614536,1.6841461329,0.1166845529,-0.3268795898,-0.9612751672,0.4062399443,0.357209662,-0.2977362702,-0.3988147401,-0.1174652196,0.3350589818,-1.8800423584,0.0124169787,1.0015110265,0.789541751,-0.2710408983,1.4987300181,-1.1726824468,-0.355322591,0.6567978423,0.8319110558,0.8258835069,-1.1567887763,1.9568551122,1.5148655075,1.0589021915,-0.4388232953,-0.7451680183,-2.1897621693,0.4502135234,-1.9583089063,0.1358789518,-1.7585860897,0.452259777,0.7406800349,-1.3578980418,1.108740204,-1.1986272667,-1.0273598206,-1.8165822264,1.0853600894,-0.273943514,0.8589890805,1.3639094329,-0.6121993589,-0.0587067992,0.0798457584,1.0992814648,-1.0455733611,1.4780003064,0.5047157705,0.1565451605,0.9656886956,-0.5998330255,0.4846727299,0.8790524818,1.0288893846,-2.0842447397,0.4074607421,2.1523241756,-1.1268047125,-0.6016001524,-1.3302141561,1.1869516954,1.0988060125,0.7405900405,1.1813110811,0.8685330644,2.0927140519,-1.7171952009,0.9231993147,0.320874115,0.7465845079,-0.1034484959,-0.4776822499,0.436218328,-0.4083564542,0.4835567895,1.0733230373,-0.858658902,-0.4493571034,0.4506418221,1.6696649735,-0.9189799982,-1.1690356499,-1.0689397924,0.3174297583,1.0403701444,0.5440082812,-0.1128248996]'
Both of them are bytes type, but I can use numpy.frombuffer to read the b_d, but not the b_test_d. And they look very different. Why do I have these two types of bytes?
Thank you.

[A]nyone can point out how to use Json marshall to convert the byte to the same type of bytes as the first one?
This isn't the right question, but I think I know what you're asking. You say you're getting the 2nd array via JSON marshalling, but that it's also not under your control:
it was obtained by json marshal (convert a received float array to byte array, and then convert the result to base64 string, which is done by someone else)
That's fine though, you just have to do a few steps of processing to get to a state equivalent to the first set of bytes.
First, some context to what's going on. You've already seen that numpy can understand your first set of bytes.
>>> numpy.frombuffer(data)
[1.21 2.963 1. ]
Based on its output, it looks like numpy is interpreting your data as 3 doubles, with 8 bytes each (24 bytes total)...
>>> data = b'\\\x8f\xc2\xf5(\\\xf3?Nb\x10X9\xb4\x07#\x00\x00\x00\x00\x00\x00\xf0?'
>>> len(data)
24
...which the struct module can also interpret.
# Separate into 3 doubles
x, y, z = data[:8], data[8:16], data[16:]
print([struct.unpack('d', i) for i in (x, y, z)])
[(1.21,), (2.963,), (1.0,)
There's actually (at least) 2 ways you can get a numpy array out of this.
Short way
1. Convert to string
# Original JSON data (snipped)
junk = b'[-2.1997713216,-1.4249271187,-1.1076795391,...]'
# Decode from bytes to a string (defaults to utf-8), then
# trim off the brackets (first and last characters in the string)
as_str = junk.decode()[1:-1]
2. Use numpy.fromstring
numpy.fromstring(as_str, dtype=float, sep=',')
# Produces:
array([-2.19977132, -1.42492712, -1.10767954, 1.5224958 , -0.17097962,
0.36638757, 0.14846441, -0.74159301, -1.76022319, 0.12660569,
0.60109348, -0.46641536, 1.56755258, 1.00836295, 1.4332793 ,
0.61133843, -1.80085406, -0.94434089, 1.09436704, -1.01146427,
1.44389263, -0.27094273, 0.29904625, 0.46501336, 0.25607913,
0.22576005, -2.40774298, -0.05099832, 1.00621871, 0.43150758,
... ])
Long way
Note: I found the fromstring method after writing this part up, figured I'd leave it here to at least help explain the byte differences.
1. Convert the JSON data into an array of numeric values.
# Original JSON data (snipped)
junk = b'[-2.1997713216,-1.4249271187,-1.1076795391,...]'
# Decode from bytes to a string - defaults to utf-8
junk = junk.decode()
# Trim off the brackets - First and last characters in the string
junk = junk[1:-1]
# Separate into values
junk = junk.split(',')
# Convert to numerical values
doubles = [float(val) for val in junk]
# Or, as a one-liner
doubles = [float(val) for val in junk.decode()[1:-1].split(',')]
# "doubles" currently holds:
[-2.1997713216,
-1.4249271187,
-1.1076795391,
1.5224958034,
...]
2. Use struct to get byte-representations for the doubles
import struct
as_bytes = [struct.pack('d', val) for val in doubles]
# "as_bytes" currently holds:
[b'\x08\x9b\xe7\xb4!\x99\x01\xc0',
b'\x0b\x00\xe0`\x80\xcc\xf6\xbf',
b'+ ..\x0e\xb9\xf1\xbf',
b'hg>\x8f$\\\xf8?',
...]
3. Join all the double values (as bytes) into a single byte-string, then submit to numpy
new_data = b''.join(as_bytes)
numpy.frombuffer(new_data)
# Produces:
array([-2.19977132, -1.42492712, -1.10767954, 1.5224958 , -0.17097962,
0.36638757, 0.14846441, -0.74159301, -1.76022319, 0.12660569,
0.60109348, -0.46641536, 1.56755258, 1.00836295, 1.4332793 ,
0.61133843, -1.80085406, -0.94434089, 1.09436704, -1.01146427,
1.44389263, -0.27094273, 0.29904625, 0.46501336, 0.25607913,
0.22576005, -2.40774298, -0.05099832, 1.00621871, 0.43150758,
... ])

A bytes object can be in any format. It is "just a bunch of bytes" without context. For display Python will represent byte values <128 as their ASCII value, and use hex escape codes (\x##) for others.
The first looks like IEEE 754 double precision floating point. numpy or struct can read it. The second one is in JSON format. Use the json module to read it:
import numpy as np
import json
import struct
b1 = b'\\\x8f\xc2\xf5(\\\xf3?Nb\x10X9\xb4\x07#\x00\x00\x00\x00\x00\x00\xf0?'
b2 = b'[-2.1997713216,-1.4249271187,-1.1076795391,1.5224958034]'
j = json.loads(b2)
n = np.frombuffer(b1)
s = struct.unpack('3d',b1)
print(j,n,s,sep='\n')
# To convert b2 into a b1 format
b = struct.pack('4d',*j)
print(b)
Output:
[-2.1997713216, -1.4249271187, -1.1076795391, 1.5224958034]
[1.21 2.963 1. ]
(1.21, 2.963, 1.0)
b'\x08\x9b\xe7\xb4!\x99\x01\xc0\x0b\x00\xe0`\x80\xcc\xf6\xbf+ ..\x0e\xb9\xf1\xbfhg>\x8f$\\\xf8?'

problem with rewriting a wav file in python

I have a problem with rewriting a .wav file (wave audio file). my project involves converting a wave file data into bytes of data and then reassembling a new audio file which sounds the same.
For some reason, when I try to do this with struct.pack, the result is similar, but not the same - it seems like the original data but not exactly.
note: for normal string it works, but for the type of data in which wave files are written, it doesn't.
My function for converting the original data to bytes:
def original_data_to_bytes_data(original_data):
"""
params: original data.
returns: all the data in bytes form, list of strings.
"""
original_data = str(''.join(format(ord(i), '08b') for i in original_data))
bytes_data = list()
for i in range(0, len(original_data), 8):
bytes_data.append(original_data[i:i+8])
return bytes_data
My function for converting the bytes to the original data:
def bytes_data_to_original_data(bytes_data):
"""
params: bytes_data - data, list of strings.
returns: original data.
"""
original_data =""
for i in bytes_data:
original_data += struct.pack('i', int(i, 2))
return original_data
Thanks for the help!

On Python 3 I get error message. On Python 2 it works without error so I assume that you also use Python 2.
I checked this
data = 'A'
result = bytes_data_to_original_data(original_data_to_bytes_data(data))
print(result)
print(type(data), type(result))
and it display the same text and the same typu
But when I check
print(data == result)
print(len(data), len(result))
print(repr(data), repr(result))
then it show that data and result are different
False
(1, 4)
("'A'", "'A\\x00\\x00\\x00'")
If I use "B" (byte) instead of "i" (integer) in code
struct.pack('B', int(i, 2))
then I get the same values - so wave should sound the same too.
it works also if I use bytes b"A" instead of string "A" because Python2 tread bytes as string.
def bytes_data_to_original_data(bytes_data):
"""
params: bytes_data - data, list of strings.
returns: original data.
"""
original_data = ""
for i in bytes_data:
original_data += struct.pack('B', int(i, 2))
return original_data
EDIT: In struct.pack() I changed 'b' (which need values -128..127) to 'B' (which works with values 0..255).

How to skip bytes after reading data using numpy fromfile

I'm trying to read noncontiguous fields from a binary file in Python using numpy fromfile function. It's based on this Matlab code using fread:
fseek(file, 0, 'bof');
q = fread(file, inf, 'float32', 8);
8 indicates the number of bytes I want to skip after reading each value. I was wondering if there was a similar option in fromfile, or if there is another way of reading specific values from a binary file in Python. Thanks for your help.
Henrik

Something like this should work, untested:
import struct
floats = []
with open(filename, 'rb') as f:
while True:
buff = f.read(4) # 'f' is 4-bytes wide
if len(buff) < 4: break
x = struct.unpack('f', buff)[0] # Convert buffer to float (get from returned tuple)
floats.append(x) # Add float to list (for example)
f.seek(8, 1) # The second arg 1 specifies relative offset
Using struct.unpack()

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