In the Python code using numpy 1.18.1
` def printBoard(self): current = self.player other = self.player % 2 + 1
currBin = '{:049b}'.format(self.current_position)
currRev = currBin[::-1]
cArr = (np.fromstring(currRev,'u1') - ord('0'))*current
other_position = self.current_position^self.mask
othBin = '{:049b}'.format(other_position)
othRev = othBin[::-1]
oArr = (np.fromstring(othRev,'u1') - ord('0'))*other
tArr = oArr+cArr
brd = np.reshape(tArr,(7,7),order = 'F')
for y in range(bitBoard.HEIGHT,-1,-1):
for x in range(bitBoard.WIDTH):
print(brd[y,x],end = ' ')
print()
print()
`
the line :
cArr = (np.fromstring(currRev,'u1') - ord('0'))*current
gives the following warning:
DeprecationWarning: The binary mode of fromstring is deprecated, as it behaves surprisingly on unicode inputs. Use frombuffer instead
cArr = (np.fromstring(currRev,'u1') - ord('0'))*current
Replacing 'fromstring' with 'frombuffer' gives the following error :
cArr = (np.frombuffer(currRev,'u1') - ord('0'))*current
TypeError: a bytes-like object is required, not 'str'
Despite some Googling I cannot find what I should use instead. Can anybody help?
Thank you.
Alan
The relevant part of your code is that which produces currRev. From that I can construct this example:
In [751]: astr = '{:049b}'.format(123)[::-1]
In [752]: astr
Out[752]: '1101111000000000000000000000000000000000000000000'
your warning:
In [753]: np.fromstring(astr, 'u1')
/usr/local/bin/ipython3:1: DeprecationWarning: The binary mode of fromstring is deprecated, as it behaves surprisingly on unicode inputs. Use frombuffer instead
#!/usr/bin/python3
Out[753]:
array([49, 49, 48, 49, 49, 49, 49, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48,
48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48,
48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48],
dtype=uint8)
frombuffer wants a bytestring, so let's create one:
In [754]: astr.encode()
Out[754]: b'1101111000000000000000000000000000000000000000000'
In [755]: np.frombuffer(astr.encode(),'u1')
Out[755]:
array([49, 49, 48, 49, 49, 49, 49, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48,
48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48,
48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48],
dtype=uint8)
And the rest of the line:
In [756]: _-ord('0')
Out[756]:
array([1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0], dtype=uint8)
Another way to get the same array:
In [758]: np.array(list(astr),'uint8')
Out[758]:
array([1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0], dtype=uint8)
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