def process_crop_job(job, create_message=True):
""" This method does the actual cropping. It controls the data extraction
and the creation of the sub-stack. It can be executed as Celery task.
"""
try:
# Create the sub-stack
cropped_stack = extract_substack( job )
# Create tho output image
outputImage = ImageList()
for img in cropped_stack:
outputImage.append( img )
# Save the resulting micro_stack to a temporary location
no_error_occured = True
error_message = ""
# Only produce an image if parts of stacks are within the output
if len( cropped_stack ) > 0:
outputImage.writeImages( job.output_path )
# Add some meta data to the image
addMetaData( job.output_path, job, cropped_stack )
else:
no_error_occured = False
error_message = "A region outside the stack has been selected. " \
"Therefore, no image was produced."
except (IOError, OSError, ValueError), e:
no_error_occured = False
error_message = str(e)
# Delete the file if parts of it have been written already
if os.path.exists( job.output_path ):
os.remove( job.output_path )
def process_crop_job(job, create_message=True):
""" This method does the actual cropping. It controls the data extraction
and the creation of the sub-stack. It can be executed as Celery task.
"""
try:
# Create the sub-stack
cropped_stack = extract_substack(job)
# Create tho output image
outputImage = ImageList()
for img in cropped_stack:
outputImage.append(img)
# Save the resulting micro_stack to a temporary location
no_error_occured = True
error_message = ""
# Only produce an image if parts of stacks are within the output
if len(cropped_stack) > 0:
outputImage.writeImages(job.output_path)
# Add some meta data to the image
addMetaData(job.output_path, job, cropped_stack)
else:
no_error_occured = False
error_message = "A region outside the stack has been selected. " \
"Therefore, no image was produced."
except (IOError, OSError), e:
no_error_occured = False
error_message = str(e)
# Delete the file if parts of it have been written already
if os.path.exists(job.output_path):
os.remove(job.output_path)
def GenerateSHPpreview(mapObject):
# generates gif preview of shp files for every mapObject in list of objects
currentDirectory = os.getcwd()
for item in mapObject:
path = os.getcwd() + os.sep + 'openraData/data/maps/' + str(item.id) + os.sep
Dir = os.listdir(path + 'content/')
if os.path.isdir(path+'content/png/'):
shutil.rmtree(path+'content/png/')
for fn in Dir:
if fn.endswith('.shp'):
os.mkdir(path + 'content/png/')
os.chdir(path + 'content/png/')
command = 'mono --debug %sOpenRA.Utility.exe %s --png %s %s' % (settings.OPENRA_PATH, item.game_mod, path+'content/'+fn, '../../../../palettes/0/RA1/temperat.pal')
proc = Popen(command.split(), stdout=PIPE).communicate()
pngsdir = os.listdir(path + 'content/png/')
imglist = []
for pngfn in pngsdir:
if pngfn.endswith('.png'):
imglist.append(pngfn)
imglist.sort()
imgs = ImageList()
for img in imglist:
imgs.append(Image(path+'content/png/'+img))
imgs.animationDelayImages(50)
imgs.writeImages(path+'content/'+fn+'.gif')
os.chdir(currentDirectory)
shutil.rmtree(path+'content/png/')
return True
def resize5( srcFile="", destFile="", w=200,h=200 ):
imgs = ImageList()
outImgs = ImageList()
imgs.readImages( srcFile )
gifFrameLen = len( imgs )
#取得gif的第0帧
img = imgs.__getitem__( 0 )
#sw源图宽度
sw = img.columns()
sh = img.rows()
#要缩略的宽度
rw = w
#要缩略的高度
rh = h
#源图的宽高比
sratio = float(sw)/float(sh)
#目标图的宽高比
rratio = float(rw)/float(rh)
if ( sw>w ):
imgs.scaleImages( "%dx"%w)
#
#??长大高小的图片处理问题:1600x94 转换为160x298按照宽度等比缩放
#??长大高小的图片处理问题:1600x94 转换为522x294
#若源图的宽高比大于目标图的宽高比时，则按照高进行缩放后再裁剪宽度
else:
if ( sratio > rratio ):
hscale = float(rh)/float(sh)
w = int(sw*hscale)
h = int(sh*hscale)
#print (sw,sh,w,h,rw,rh,hscale)
#就高缩放
imgs.scaleImages( "%dx"%(w) )
#若源图的宽高比小于目标图的宽高比时，则按照宽进行缩放后再裁剪高度
else:
wscale = float(rw)/float(sw)
w = int(sw*wscale)
h = int(sh*wscale)
#print (sw,sh,w,h,rw,rh,wscale)
#就宽缩放
imgs.scaleImages("%dx%d"%(w,h))
#缩放完后遍历裁剪
for i in range( gifFrameLen ):
tmpImg = imgs.__getitem__( i )
tmpImg.crop(Geometry( rw,rh,0,0 ) )
tmpImg.profile("*", Blob())
outImgs.append( tmpImg )
#(102, 900, 160, 1411, 160, 298)
#print( sw,sh,w,h,rw,rh)
if ( len( outImgs ) > 0 ):
outImgs.writeImages(destFile)
else:
imgs.writeImages(destFile)
return "True"
def resize5(srcFile="", destFile="", w=200, h=200):
imgs = ImageList()
outImgs = ImageList()
imgs.readImages(srcFile)
gifFrameLen = len(imgs)
#取得gif的第0帧
img = imgs.__getitem__(0)
#sw源图宽度
sw = img.columns()
sh = img.rows()
#要缩略的宽度
rw = w
#要缩略的高度
rh = h
#源图的宽高比
sratio = float(sw) / float(sh)
#目标图的宽高比
rratio = float(rw) / float(rh)
if (sw > w):
imgs.scaleImages("%dx" % w)
#
#??长大高小的图片处理问题:1600x94 转换为160x298按照宽度等比缩放
#??长大高小的图片处理问题:1600x94 转换为522x294
#若源图的宽高比大于目标图的宽高比时，则按照高进行缩放后再裁剪宽度
else:
if (sratio > rratio):
hscale = float(rh) / float(sh)
w = int(sw * hscale)
h = int(sh * hscale)
#print (sw,sh,w,h,rw,rh,hscale)
#就高缩放
imgs.scaleImages("%dx" % (w))
#若源图的宽高比小于目标图的宽高比时，则按照宽进行缩放后再裁剪高度
else:
wscale = float(rw) / float(sw)
w = int(sw * wscale)
h = int(sh * wscale)
#print (sw,sh,w,h,rw,rh,wscale)
#就宽缩放
imgs.scaleImages("%dx%d" % (w, h))
#缩放完后遍历裁剪
for i in range(gifFrameLen):
tmpImg = imgs.__getitem__(i)
tmpImg.crop(Geometry(rw, rh, 0, 0))
tmpImg.profile("*", Blob())
outImgs.append(tmpImg)
#(102, 900, 160, 1411, 160, 298)
#print( sw,sh,w,h,rw,rh)
if (len(outImgs) > 0):
outImgs.writeImages(destFile)
else:
imgs.writeImages(destFile)
return "True"
def process_crop_job(job, create_message=True):
""" This method does the actual cropping. It controls the data extraction
and the creation of the sub-stack. It can be executed as Celery task.
"""
try:
# Create the sub-stack
cropped_stack = extract_substack(job)
# Create tho output image
outputImage = ImageList()
for img in cropped_stack:
outputImage.append(img)
# Save the resulting micro_stack to a temporary location
no_error_occured = True
error_message = ""
# Only produce an image if parts of stacks are within the output
if len(cropped_stack) > 0:
outputImage.writeImages(job.output_path.encode('ascii', 'ignore'))
# Add some meta data to the image
addMetaData(job.output_path, job, cropped_stack)
else:
no_error_occured = False
error_message = "A region outside the stack has been selected. " \
"Therefore, no image was produced."
except (IOError, OSError, ValueError) as e:
no_error_occured = False
error_message = str(e)
# Delete the file if parts of it have been written already
if os.path.exists(job.output_path):
os.remove(job.output_path)
if create_message:
# Create a notification message
bb_text = "( %s, %s, %s ) -> ( %s, %s, %s )" % (job.x_min, job.y_min, \
job.z_min, job.x_max, job.y_max, job.z_max)
msg = Message()
msg.user = User.objects.get(pk=int(job.user.id))
msg.read = False
if no_error_occured:
file_name = os.path.basename(job.output_path)
url = os.path.join(settings.CATMAID_URL,
"crop/download/" + file_name + "/")
msg.title = "Microstack finished"
msg.text = "The requested microstack %s is finished. You can " \
"download it from this location: <a href='%s'>%s</a>" % \
(bb_text, url, url)
msg.action = url
else:
msg.title = "Microstack could not be created"
msg.text = "The requested microstack %s could not be created due " \
"to an error while saving the result (%s)." % \
(bb_text, error_message)
msg.action = ""
msg.save()
return job.output_path if no_error_occured else error_message
def process_crop_job(job, create_message=True):
""" This method does the actual cropping. It controls the data extraction
and the creation of the sub-stack. It can be executed as Celery task.
"""
try:
# Create the sub-stack
cropped_stack = extract_substack(job)
# Create tho output image
outputImage = ImageList()
for img in cropped_stack:
outputImage.append( img )
# Save the resulting micro_stack to a temporary location
no_error_occured = True
error_message = ""
# Only produce an image if parts of stacks are within the output
if len( cropped_stack ) > 0:
outputImage.writeImages( job.output_path.encode('ascii', 'ignore') )
# Add some meta data to the image
addMetaData( job.output_path, job, cropped_stack )
else:
no_error_occured = False
error_message = "A region outside the stack has been selected. " \
"Therefore, no image was produced."
except (IOError, OSError, ValueError) as e:
no_error_occured = False
error_message = str(e)
# Delete the file if parts of it have been written already
if os.path.exists( job.output_path ):
os.remove( job.output_path )
if create_message:
# Create a notification message
bb_text = "( %s, %s, %s ) -> ( %s, %s, %s )" % (job.x_min, job.y_min, \
job.z_min, job.x_max, job.y_max, job.z_max)
msg = Message()
msg.user = User.objects.get(pk=int(job.user.id))
msg.read = False
if no_error_occured:
file_name = os.path.basename( job.output_path )
url = os.path.join( settings.CATMAID_URL, "crop/download/" + file_name + "/")
msg.title = "Microstack finished"
msg.text = "The requested microstack %s is finished. You can " \
"download it from this location: <a href='%s'>%s</a>" % \
(bb_text, url, url)
msg.action = url
else:
msg.title = "Microstack could not be created"
msg.text = "The requested microstack %s could not be created due " \
"to an error while saving the result (%s)." % \
(bb_text, error_message)
msg.action = ""
msg.save()
return job.output_path if no_error_occured else error_message
def save_files(png_list, save_name):
print("Saving files to gif:%s" % save_name)
imgs = ImageList()
for file_name in png_list:
im = PGImage(file_name)
imgs.animationDelayImages(5)
imgs.append(im)
imgs.writeImages(save_name)
def GenerateSHPpreview(self):
Dir = os.listdir(self.map_full_path_directory+'content/')
for fn in Dir:
if fn.endswith('.shp'):
os.mkdir(self.map_full_path_directory+'content/png/')
os.chdir(self.map_full_path_directory+'content/png/')
command = 'mono --debug %sOpenRA.Utility.exe %s --png %s %s' % (settings.OPENRA_PATH, self.MapMod, self.map_full_path_directory+'content/'+fn, '../../../../palettes/0/RA1/temperat.pal')
proc = Popen(command.split(), stdout=PIPE).communicate()
self.flushLog(proc)
pngsdir = os.listdir(self.map_full_path_directory+'content/png/')
imglist = []
for pngfn in pngsdir:
if pngfn.endswith('.png'):
imglist.append(pngfn)
imglist.sort()
imgs = ImageList()
for img in imglist:
imgs.append(Image(self.map_full_path_directory+'content/png/'+img))
imgs.animationDelayImages(50)
imgs.writeImages(self.map_full_path_directory+'content/'+fn+'.gif')
os.chdir(self.currentDirectory)
shutil.rmtree(self.map_full_path_directory+'content/png/')
def resize6( srcFile="", destFile="", w=200,h=200 ):
imgs = ImageList()
imgs.readImages(srcFile)
gifFrameLen = len(imgs)
#若只有一帧直接调用静态方法输出
if ( gifFrameLen == 1 ):
return staticPhoto.resize6(srcFile,destFile,w,h)
outImg = ImageList()
#取得第0帧
gifFrame0 = imgs.__getitem__(0)
#sw源图宽度
sw = gifFrame0.columns()
sh = gifFrame0.rows()
#如果宽高比大小于倍则转成静态图片
if ( int(sw/sh) > 5 ):
return staticPhoto.resize1(srcFile,destFile,w,h)
#要缩略的宽度
rw = w
#要缩略的高度
rh = h
#源图的宽高比
sratio = float(sw)/float(sh)
#目标图的宽高比
rratio = float(rw)/float(rh)
#若源图的宽高比大于目标图的宽高比时，则按照高进行缩放后再裁剪宽度
if ( sratio > rratio ):
hscale = float(rh)/float(sh)
w = int(sw*hscale)
h = int(sh*hscale)
#print (sw,sh,w,h,rw,rh,hscale)
#就高缩放
imgs.scaleImages("%dx%d"%(w,h))
#计算裁剪宽的部分的横坐标,超出的宽的部分进行裁剪
tmpRowsPos = int((sw*hscale - rw)/2)
#imgs.coalesceImags(Geometry( rw,rh,tmpRowsPos,0 ))
for i in range( gifFrameLen ):
tmpImg = imgs.__getitem__(i)
#print w,h,sw,sh,rw,rh,tmpRowsPos,i,gifFrameLen,tmpImg.columns(),tmpImg.rows()
#594 260 320 140 132 260 231 0 145 320 140
if ( sw == tmpImg.columns() and sh == tmpImg.rows() and tmpRowsPos > 0 ):
return staticPhoto.resize1(srcFile,destFile,rw,rh)
tmpImg.crop(Geometry( rw,rh,tmpRowsPos,0 ) )
tmpImg.profile("*", Blob())
outImg.append(tmpImg)
outImg.writeImages(destFile)
return "True"
#若源图的宽高比小于目标图的宽高比时，则按照宽进行缩放后再裁剪高度
else:
wscale = float(rw)/float(sw)
w = int(sw*wscale)
h = int(sh*wscale)
#print (sw,sh,w,h,rw,rh,wscale)
#就宽缩放
imgs.scaleImages("%dx%d"%(w,h))
tmpColsPos = int((sh*wscale-rh)/2 )
for i in range(gifFrameLen):
if ( i == 0 ):
tmpImg = gifFrame0
else:
tmpImg = imgs.__getitem__(i)
if ( sw == tmpImg.columns() and sh == tmpImg.rows() and tmpColsPos > 0 ):
return staticPhoto.resize1(srcFile,destFile,rw,rh)
tmpImg.crop( Geometry( rw,rh,0,tmpColsPos ) )
tmpImg.profile("*", Blob())
outImg.append(tmpImg)
outImg.writeImages(destFile)
return "True"
return "True"
def simulate(self, policy, iterations, output, figure_template, html, gif,
anim_delay):
raw_policy = deepcopy(policy)
# Policy dictionary
policy = {
tuple([pol['state'][agent][1]
for agent in self.agents]): pol['action']
for pol in policy
}
print ''
print 'Goal State Set:'
print self.name_goal
print ''
print 'Initial State:'
agent_locs = OrderedDict([(agent, None) for agent in self.agents])
for agent in self.agents:
agent_locs[agent] = np.random.choice(self.locs)
print agent_locs.values()
rwd = 0
print ''
print 'Steps'
history = {}
for i in range(iterations):
# Types of agent on each location
agent_classes_on_loc = OrderedDict([(loc, [])
for loc in self.locs])
for agent in self.agents:
agent_classes_on_loc[agent_locs[agent]].append(
self.agents_types[agent])
# State idx
state_idx = self.s.index(
tuple([self.locs[s] for s in agent_locs.values()]))
# Computing rewards
rwd = 0
for loc, types in self.name_goal.items():
if not (set(types) - set(agent_classes_on_loc[loc])):
rwd += 1
# Printing history
history[i] = {
'state_idx': state_idx,
'agent_locs': copy.deepcopy(agent_locs),
'rwd': rwd
}
# Updating agent location, given policy
for agent in self.agents:
# Locations adjacent to the agent location
adj_locs = self.name_loc_roads[agent_locs[agent]]
# Baseline probability of going to any adjacent location (error)
pdf = np.zeros(len(self.locs), dtype=np.float32)
for adj_loc in adj_locs:
pdf[self.locs[adj_loc]] = self.error / (len(adj_locs) - 1)
# Agent intended next state
sn = self.locs[policy[tuple(agent_locs.values())][agent][-1]]
# Success probability
pdf[sn] = 1.0 - self.error
# Transition
agent_locs[agent] = np.random.choice(self.locs, p=pdf)
# Printing history
self.plot(raw_policy,
output + figure_template,
states=[hist['state_idx'] for hist in history.values()])
# Printing history
for h, hist in history.items():
print h, hist
# Creating animated GIF
imgs = ImageList()
for h, hist in history.items():
imgs.append(Image(output + figure_template % hist['state_idx']))
imgs.animationDelayImages(anim_delay)
imgs.writeImages(output + gif)
# Generating HTML report
doc, tag, text, line = Doc().ttl()
with tag('html'):
with tag('body'):
with tag('p', id='main'):
with tag('h1'):
text('Simulation Results')
line('h2', 'Animation')
with tag('div', id='frame'):
doc.stag('img', src=gif)
for h, hist in history.items():
with tag('p', id='%d' % h):
line('h2', 'Iteration %d' % h)
doc.stag('br')
text('State ID: %d' % hist['state_idx'])
doc.stag('br')
text('Reward: %d' % hist['rwd'])
doc.stag('br')
for agent, loc in hist['agent_locs'].items():
text('Agent %s at location %s.' % (agent, loc))
doc.stag('br')
with tag('div', id='frame'):
doc.stag('img',
src=figure_template %
hist['state_idx'])
# Storing HTML file
result = indent(doc.getvalue())
with open(output + html, 'w') as f:
f.write(result)
from pgmagick import Image, ImageList, Geometry, Color
imgs = ImageList()
for color in ('red', 'blue', 'green', 'black', 'yellow'):
imgs.append(Image(Geometry(200, 200), Color(color)))
imgs.animationDelayImages(100)
imgs.scaleImages(Geometry(100, 100))
print len(imgs)
imgs.writeImages('output.gif')
imgs = ImageList()
imgs.readImages('output.gif')
for img in imgs:
print img
from pgmagick import Image, ImageList, Geometry, Color
imgs = ImageList()
for color in ("red", "blue", "green", "black", "yellow"):
imgs.append(Image(Geometry(200, 200), Color(color)))
imgs.animationDelayImages(100)
imgs.scaleImages(Geometry(100, 100))
print len(imgs)
imgs.writeImages("output.gif")
imgs = ImageList()
imgs.readImages("output.gif")
for img in imgs:
print img
def resize6(srcFile="", destFile="", w=200, h=200):
imgs = ImageList()
imgs.readImages(srcFile)
gifFrameLen = len(imgs)
#若只有一帧直接调用静态方法输出
if (gifFrameLen == 1):
return staticPhoto.resize6(srcFile, destFile, w, h)
outImg = ImageList()
#取得第0帧
gifFrame0 = imgs.__getitem__(0)
#sw源图宽度
sw = gifFrame0.columns()
sh = gifFrame0.rows()
#如果宽高比大小于倍则转成静态图片
if (int(sw / sh) > 5):
return staticPhoto.resize1(srcFile, destFile, w, h)
#要缩略的宽度
rw = w
#要缩略的高度
rh = h
#源图的宽高比
sratio = float(sw) / float(sh)
#目标图的宽高比
rratio = float(rw) / float(rh)
#若源图的宽高比大于目标图的宽高比时，则按照高进行缩放后再裁剪宽度
if (sratio > rratio):
hscale = float(rh) / float(sh)
w = int(sw * hscale)
h = int(sh * hscale)
#print (sw,sh,w,h,rw,rh,hscale)
#就高缩放
imgs.scaleImages("%dx%d" % (w, h))
#计算裁剪宽的部分的横坐标,超出的宽的部分进行裁剪
tmpRowsPos = int((sw * hscale - rw) / 2)
#imgs.coalesceImags(Geometry( rw,rh,tmpRowsPos,0 ))
for i in range(gifFrameLen):
tmpImg = imgs.__getitem__(i)
#print w,h,sw,sh,rw,rh,tmpRowsPos,i,gifFrameLen,tmpImg.columns(),tmpImg.rows()
#594 260 320 140 132 260 231 0 145 320 140
if (sw == tmpImg.columns() and sh == tmpImg.rows()
and tmpRowsPos > 0):
return staticPhoto.resize1(srcFile, destFile, rw, rh)
tmpImg.crop(Geometry(rw, rh, tmpRowsPos, 0))
tmpImg.profile("*", Blob())
outImg.append(tmpImg)
outImg.writeImages(destFile)
return "True"
#若源图的宽高比小于目标图的宽高比时，则按照宽进行缩放后再裁剪高度
else:
wscale = float(rw) / float(sw)
w = int(sw * wscale)
h = int(sh * wscale)
#print (sw,sh,w,h,rw,rh,wscale)
#就宽缩放
imgs.scaleImages("%dx%d" % (w, h))
tmpColsPos = int((sh * wscale - rh) / 2)
for i in range(gifFrameLen):
if (i == 0):
tmpImg = gifFrame0
else:
tmpImg = imgs.__getitem__(i)
if (sw == tmpImg.columns() and sh == tmpImg.rows()
and tmpColsPos > 0):
return staticPhoto.resize1(srcFile, destFile, rw, rh)
tmpImg.crop(Geometry(rw, rh, 0, tmpColsPos))
tmpImg.profile("*", Blob())
outImg.append(tmpImg)
outImg.writeImages(destFile)
return "True"
return "True"
