def __init__(self, hash_name='md5', coerce_mmap=False):
"""
Parameters
----------
hash_name: string
The hash algorithm to be used
coerce_mmap: boolean
Make no difference between np.memmap and np.ndarray
objects.
"""
self.coerce_mmap = coerce_mmap
Hasher.__init__(self, hash_name=hash_name)
# delayed import of numpy, to avoid tight coupling
import numpy as np
self.np = np
if hasattr(np, 'getbuffer'):
self._getbuffer = np.getbuffer
else:
self._getbuffer = memoryview
python类getbuffer()的实例源码
def __init__(self, hash_name='md5', coerce_mmap=False):
"""
Parameters
----------
hash_name: string
The hash algorithm to be used
coerce_mmap: boolean
Make no difference between np.memmap and np.ndarray
objects.
"""
self.coerce_mmap = coerce_mmap
Hasher.__init__(self, hash_name=hash_name)
# delayed import of numpy, to avoid tight coupling
import numpy as np
self.np = np
if hasattr(np, 'getbuffer'):
self._getbuffer = np.getbuffer
else:
self._getbuffer = memoryview
def __init__(self, hash_name='md5', coerce_mmap=False):
"""
Parameters
----------
hash_name: string
The hash algorithm to be used
coerce_mmap: boolean
Make no difference between np.memmap and np.ndarray
objects.
"""
self.coerce_mmap = coerce_mmap
Hasher.__init__(self, hash_name=hash_name)
# delayed import of numpy, to avoid tight coupling
import numpy as np
self.np = np
if hasattr(np, 'getbuffer'):
self._getbuffer = np.getbuffer
else:
self._getbuffer = memoryview
def togglepattern():
global togsw,o,ovl,gui,alphaValue
# if overlay is inactive, ignore button:
if togsw == 0:
print "Pattern button pressed, but ignored --- Crosshair not visible."
# if overlay is active, drop it, change pattern, then show it again
else:
if guivisible == 0:
# reinitialize array:
ovl = np.zeros((height, width, 3), dtype=np.uint8)
patternswitch(ovl,0)
if o != None:
camera.remove_overlay(o)
o = camera.add_overlay(np.getbuffer(ovl), layer=3, alpha=alphaValue)
else:
# reinitialize array
gui = np.zeros((height, width, 3), dtype=np.uint8)
creategui(gui)
patternswitch(gui,1)
if o != None:
camera.remove_overlay(o)
o = camera.add_overlay(np.getbuffer(gui), layer=3, alpha=alphaValue)
return
def toggleonoff():
global togsw,o,alphaValue
if togsw == 1:
print "Toggle Crosshair OFF"
if o != None:
camera.remove_overlay(o)
togsw = 0
else:
print "Toggle Crosshair ON"
if guivisible == 0:
o = camera.add_overlay(np.getbuffer(ovl), layer=3, alpha=alphaValue)
else:
o = camera.add_overlay(np.getbuffer(gui), layer=3, alpha=alphaValue)
togsw = 1
return
# function
def togglepatternZoomOut():
global togsw,o,curpat,col,ovl,gui,alphaValue
# if overlay is inactive, ignore button:
if togsw == 0:
zoom_out()
else:
if guivisible == 0:
zoom_out()
# reinitialize array:
ovl = np.zeros((height, width, 3), dtype=np.uint8)
patternswitcherZoomOut(ovl,0)
o = camera.add_overlay(np.getbuffer(ovl), layer=3, alpha=alphaValue)
else:
zoom_out()
# reinitialize array
gui = np.zeros((height, width, 3), dtype=np.uint8)
creategui(gui)
patternswitcherZoomOut(gui,1)
o = camera.add_overlay(np.getbuffer(gui), layer=3, alpha=alphaValue)
return
def toggleonoff():
global togsw,o,alphaValue
if togsw == 1:
print "Toggle Crosshair OFF"
if o != None:
camera.remove_overlay(o)
togsw = 0
else:
print "Toggle Crosshair ON"
if guivisible == 0:
o = camera.add_overlay(np.getbuffer(ovl), layer=3, alpha=alphaValue)
else:
o = camera.add_overlay(np.getbuffer(gui), layer=3, alpha=alphaValue)
togsw = 1
return
# function
def togglepatternZoomOut():
global togsw,o,curpat,col,ovl,gui,alphaValue
# if overlay is inactive, ignore button:
if togsw == 0:
zoom_out()
else:
if guivisible == 0:
zoom_out()
# reinitialize array:
ovl = np.zeros((height, width, 3), dtype=np.uint8)
patternswitcherZoomOut(ovl,0)
o = camera.add_overlay(np.getbuffer(ovl), layer=3, alpha=alphaValue)
else:
zoom_out()
# reinitialize array
gui = np.zeros((height, width, 3), dtype=np.uint8)
creategui(gui)
patternswitcherZoomOut(gui,1)
o = camera.add_overlay(np.getbuffer(gui), layer=3, alpha=alphaValue)
return
def numpy_buffer(ndarray):
"""Creates a buffer from c_contiguous numpy ndarray."""
# Credits to: https://github.com/joblib/joblib/blob/04b001861e1dd03a857b7b419c336de64e05714c/joblib/hashing.py
if isinstance(ndarray, (pd.Series, pd.DataFrame)):
ndarray = ndarray.values
if ndarray.flags.c_contiguous:
obj_c_contiguous = ndarray
elif ndarray.flags.f_contiguous:
obj_c_contiguous = ndarray.T
else:
obj_c_contiguous = ndarray.flatten()
obj_c_contiguous = obj_c_contiguous.view(np.uint8)
if hasattr(np, 'getbuffer'):
return np.getbuffer(obj_c_contiguous)
else:
return memoryview(obj_c_contiguous)
def __init__(self, hash_name='md5', coerce_mmap=False):
"""
Parameters
----------
hash_name: string
The hash algorithm to be used
coerce_mmap: boolean
Make no difference between np.memmap and np.ndarray
objects.
"""
self.coerce_mmap = coerce_mmap
Hasher.__init__(self, hash_name=hash_name)
# delayed import of numpy, to avoid tight coupling
import numpy as np
self.np = np
if hasattr(np, 'getbuffer'):
self._getbuffer = np.getbuffer
else:
self._getbuffer = memoryview
def __call__(self):
plte = self.plte
a = self.idRaster
#a = array('B') #unsigned 1byte int
#a.fromlist(idRaster)
### Why is this here? byteswap has no effect on 'uint8'
#if SYSTEM_BYTEORDER == '\x00': #little
# a.byteswap() #to big (network)
# This is used directly in the final PNG, must be zlib.
cIdRaster = zlib.compress(numpy.getbuffer(a))
size = pack('!I',len(cIdRaster))
crc = pack('!I',crc32('IDAT'+cIdRaster) & 0xFFFFFFFF)
idat = size+'IDAT'+cIdRaster+crc
#b = array(UNSIGNED_ITEM_TYPES[4]) #unsigned 4byte int
#b.fromlist(plte)
#cPLTE = zlib.compress(plte.tostring())
cPLTE = zlib.compress(numpy.getbuffer(plte))
s = SYSTEM_BYTEORDER + pack('!LL',len(idat),len(cPLTE)) # 9bytes <--- ByteOrder(1byte), len of idat(4bytes), len of cPLTE(4bytes)
s = s+idat+cPLTE
return s
def __init__(self, hash_name='md5', coerce_mmap=False):
"""
Parameters
----------
hash_name: string
The hash algorithm to be used
coerce_mmap: boolean
Make no difference between np.memmap and np.ndarray
objects.
"""
self.coerce_mmap = coerce_mmap
Hasher.__init__(self, hash_name=hash_name)
# delayed import of numpy, to avoid tight coupling
import numpy as np
self.np = np
if hasattr(np, 'getbuffer'):
self._getbuffer = np.getbuffer
else:
self._getbuffer = memoryview
def patternswitch(target,guitoggle):
global o, alphaValue
toggleonoff()
if guitoggle == 1:
creategui(gui)
o = camera.add_overlay(np.getbuffer(target), layer=3, alpha=alphaValue)
return
def patternswitch(target,guitoggle):
global o, alphaValue
toggleonoff()
if guitoggle == 1:
creategui(gui)
o = camera.add_overlay(np.getbuffer(target), layer=3, alpha=alphaValue)
return
def hash_from_code(msg):
try:
return hashlib.md5(msg).hexdigest()
except TypeError:
assert isinstance(msg, numpy.ndarray)
return hashlib.md5(numpy.getbuffer(msg)).hexdigest()
def __call__(self):
if self.maxID < 2**16:
dtype = 'uint16' #UNSIGNED_ITEM_TYPES[2] #UNSIGNED_2_BYTE_INT
DTYPE = '\x00'
else:
dtype = 'uint32' #UNSIGNED_ITEM_TYPES[4] #UNSIGNED_4_BYTE_INT
DTYPE = '\x01'
a = self.intRaster.astype(dtype)
#return SYSTEM_BYTEORDER+DTYPE+zlib.compress(a.tostring())
return SYSTEM_BYTEORDER+DTYPE+zlib.compress(numpy.getbuffer(a))
