def run_async_operation(request_handler, operation_name):
gc.logger.debug('>>> running an async operation')
request_id = util.generate_request_id()
params, raw_post_body, plugin_client = get_request_params(request_handler)
gc.logger.debug(request_id)
gc.logger.debug(params)
gc.logger.debug(raw_post_body)
worker_thread = BackgroundWorker(operation_name, params, True, request_id, raw_post_body, plugin_client)
gc.logger.debug('worker created')
worker_thread.start()
gc.logger.debug('worker thread started')
async_request_queue[request_id] = worker_thread
gc.logger.debug('placed into queue')
#q = Queue() #on larger object puts, process would hang
#using manager based on this recommendation:
#http://stackoverflow.com/questions/11442892/python-multiprocessing-queue-failure
# manager = Manager()
# q = manager.Queue() #TODO: request is failing here many times
# gc.logger.debug('finished with queue')
#worker = BackgroundWorker(operation_name, params, True, request_id, raw_post_body, q)
#gc.logger.debug('worker created')
#p = multiprocessing.Process(target=process_request_in_background,args=(worker,))
#p.start()
#gc.logger.debug('started process!')
#add_to_request_queue(request_id, p, q)
#gc.logger.debug('preparing to response with the async id!')
return respond_with_async_request_id(request_handler, request_id)
def run_async_operation(request_handler, operation_name):
gc.logger.debug('>>> running an async operation')
request_id = util.generate_request_id()
params, raw_post_body, plugin_client = get_request_params(request_handler)
gc.logger.debug(request_id)
gc.logger.debug(params)
gc.logger.debug(raw_post_body)
worker_thread = BackgroundWorker(operation_name, params, True, request_id,
raw_post_body, plugin_client)
gc.logger.debug('worker created')
worker_thread.start()
gc.logger.debug('worker thread started')
async_request_queue[request_id] = worker_thread
gc.logger.debug('placed into queue')
#q = Queue() #on larger object puts, process would hang
#using manager based on this recommendation:
#http://stackoverflow.com/questions/11442892/python-multiprocessing-queue-failure
# manager = Manager()
# q = manager.Queue() #TODO: request is failing here many times
# gc.logger.debug('finished with queue')
#worker = BackgroundWorker(operation_name, params, True, request_id, raw_post_body, q)
#gc.logger.debug('worker created')
#p = multiprocessing.Process(target=process_request_in_background,args=(worker,))
#p.start()
#gc.logger.debug('started process!')
#add_to_request_queue(request_id, p, q)
#gc.logger.debug('preparing to response with the async id!')
return respond_with_async_request_id(request_handler, request_id)
def connections_delete_request(request_handler):
request_id = util.generate_request_id()
params, raw_post_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('delete_connection', params, False, request_id, raw_post_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def get_active_session_request(request_handler):
'''
GET /[email protected]&password=force&org_type=developer
'''
request_id = util.generate_request_id()
params, json_body = get_request_params(request_handler)
worker = BackgroundWorker('get_active_session', params, False, request_id, json_body)
response = worker.run()
respond(request_handler, response)
def get_active_session_request(request_handler):
'''
GET /[email protected]&password=force&org_type=developer
'''
request_id = util.generate_request_id()
params, json_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('get_active_session', params, False, request_id, json_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def metadata_list_request(request_handler):
'''
GET /metadata/list
{
"sid" : "",
"metadata_type" : "",
"murl" : ""
}
call to get a list of metadata of a certain type
'''
request_id = util.generate_request_id()
params, json_body = get_request_params(request_handler)
worker = BackgroundWorker('list_metadata', params, False, request_id, json_body)
response = worker.run()
respond(request_handler, response)
def metadata_list_request(request_handler):
'''
GET /metadata/list
{
"sid" : "",
"metadata_type" : "",
"murl" : ""
}
call to get a list of metadata of a certain type
'''
request_id = util.generate_request_id()
params, json_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('list_metadata', params, False, request_id, json_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def update_credentials_request(request_handler):
'''
POST /project/creds
{
"project_name" : "my project name"
"username" : "*****@*****.**",
"password" : "force",
"org_type" : "developer",
}
NOTE: project name should not be updated, as it is used to find the project in question
TODO: maybe we assign a unique ID to each project which will give users the flexibility
to change the project name??
TODO: we may need to implement a "clean" flag which will clean the project after creds
have been updated
'''
request_id = util.generate_request_id()
params, raw_post_body = get_request_params(request_handler)
worker = BackgroundWorker('update_credentials', params, False, request_id, raw_post_body)
response = worker.run()
respond(request_handler, response)
def connections_delete_request(request_handler):
request_id = util.generate_request_id()
params, raw_post_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('delete_connection', params, False, request_id, raw_post_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def get_active_session_request(request_handler):
'''
GET /[email protected]&password=force&org_type=developer
'''
request_id = util.generate_request_id()
params, json_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('get_active_session', params, False, request_id, json_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def project_edit_subscription(request_handler):
'''
POST /project/subscription
{
"project_name" : "my project name"
"subscription" : ["ApexClass", "ApexPage"]
}
'''
request_id = util.generate_request_id()
params, raw_post_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('update_subscription', params, False, request_id, raw_post_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def refresh_metadata_index(request_handler):
'''
GET /project/get_index/refresh
{
"project_name" : "my project name",
"metadata_types" : ["ApexClass"]
}
call to refresh a certain type of metadata
'''
request_id = util.generate_request_id()
params, json_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('refresh_metadata_index', params, False, request_id, json_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def get_metadata_index(request_handler):
'''
GET /project/get_index
{
"project_name" : "my project name",
"keyword" : "mykeyword" //optional
}
call to get the metadata index for a project
'''
request_id = util.generate_request_id()
params, json_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('get_indexed_metadata', params, False, request_id, json_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def metadata_list_request(request_handler):
'''
GET /metadata/list
{
"sid" : "",
"metadata_type" : "",
"murl" : ""
}
call to get a list of metadata of a certain type
'''
request_id = util.generate_request_id()
params, json_body, plugin_client = get_request_params(request_handler)
worker_thread = BackgroundWorker('list_metadata', params, False, request_id, json_body, plugin_client)
worker_thread.start()
worker_thread.join()
response = worker_thread.response
respond(request_handler, response)
def connections_delete_request(request_handler):
request_id = util.generate_request_id()
params, raw_post_body = get_request_params(request_handler)
worker = BackgroundWorker('delete_connection', params, False, request_id, raw_post_body)
response = worker.run()
respond(request_handler, response)
def end(self):
BackgroundWorker.end(self)
def begin(self):
BackgroundWorker.begin(self)
def __init__(self, expbase, cmdparams=None):
"""cryodata is a CryoData instance.
expbase is a path to the base of folder where this experiment's files
will be stored. The folder above expbase will also be searched
for .params files. These will be loaded first."""
BackgroundWorker.__init__(self)
# Create a background thread which handles IO
self.io_queue = Queue()
self.io_thread = Thread(target=self.ioworker)
self.io_thread.daemon = True
self.io_thread.start()
# General setup ----------------------------------------------------
self.expbase = expbase
self.outbase = None
# Paramter setup ---------------------------------------------------
# search above expbase for params files
_,_,filenames = os.walk(opj(expbase,'../')).next()
self.paramfiles = [opj(opj(expbase,'../'), fname) \
for fname in filenames if fname.endswith('.params')]
# search expbase for params files
_,_,filenames = os.walk(opj(expbase)).next()
self.paramfiles += [opj(expbase,fname) \
for fname in filenames if fname.endswith('.params')]
if 'local.params' in filenames:
self.paramfiles += [opj(expbase,'local.params')]
# load parameter files
self.params = Params(self.paramfiles)
self.cparams = None
if cmdparams is not None:
# Set parameter specified on the command line
for k,v in cmdparams.iteritems():
self.params[k] = v
# Dataset setup -------------------------------------------------------
self.imgpath = self.params['inpath']
psize = self.params['resolution']
if not isinstance(self.imgpath,list):
imgstk = MRCImageStack(self.imgpath,psize)
else:
imgstk = CombinedImageStack([MRCImageStack(cimgpath,psize) for cimgpath in self.imgpath])
if self.params.get('float_images',True):
imgstk.float_images()
self.ctfpath = self.params['ctfpath']
mscope_params = self.params['microscope_params']
if not isinstance(self.ctfpath,list):
ctfstk = CTFStack(self.ctfpath,mscope_params)
else:
ctfstk = CombinedCTFStack([CTFStack(cctfpath,mscope_params) for cctfpath in self.ctfpath])
self.cryodata = CryoDataset(imgstk,ctfstk)
self.cryodata.compute_noise_statistics()
if self.params.get('window_images',True):
imgstk.window_images()
minibatch_size = self.params['minisize']
testset_size = self.params['test_imgs']
partition = self.params.get('partition',0)
num_partitions = self.params.get('num_partitions',1)
seed = self.params['random_seed']
if isinstance(partition,str):
partition = eval(partition)
if isinstance(num_partitions,str):
num_partitions = eval(num_partitions)
if isinstance(seed,str):
seed = eval(seed)
self.cryodata.divide_dataset(minibatch_size,testset_size,partition,num_partitions,seed)
self.cryodata.set_datasign(self.params.get('datasign','auto'))
if self.params.get('normalize_data',True):
self.cryodata.normalize_dataset()
self.voxel_size = self.cryodata.pixel_size
# Iterations setup -------------------------------------------------
self.iteration = 0
self.tic_epoch = None
self.num_data_evals = 0
self.eval_params()
outdir = self.cparams.get('outdir',None)
if outdir is None:
if self.cparams.get('num_partitions',1) > 1:
outdir = 'partition{0}'.format(self.cparams['partition'])
else:
outdir = ''
self.outbase = opj(self.expbase,outdir)
if not os.path.isdir(self.outbase):
os.makedirs(self.outbase)
# Output setup -----------------------------------------------------
self.ostream = OutputStream(opj(self.outbase,'stdout'))
self.ostream(80*"=")
self.ostream("Experiment: " + expbase + \
" Kernel: " + self.params['kernel'])
self.ostream("Started on " + socket.gethostname() + \
" At: " + time.strftime('%B %d %Y: %I:%M:%S %p'))
self.ostream("Git SHA1: " + gitutil.git_get_SHA1())
self.ostream(80*"=")
gitutil.git_info_dump(opj(self.outbase, 'gitinfo'))
self.startdatetime = datetime.now()
# for diagnostics and parameters
self.diagout = Output(opj(self.outbase, 'diag'),runningout=False)
# for stats (per image etc)
self.statout = Output(opj(self.outbase, 'stat'),runningout=True)
# for likelihoods of individual images
self.likeout = Output(opj(self.outbase, 'like'),runningout=False)
self.img_likes = n.empty(self.cryodata.N_D)
self.img_likes[:] = n.inf
# optimization state vars ------------------------------------------
init_model = self.cparams.get('init_model',None)
if init_model is not None:
filename = init_model
if filename.upper().endswith('.MRC'):
M = readMRC(filename)
else:
with open(filename) as fp:
M = cPickle.load(fp)
if type(M)==list:
M = M[-1]['M']
if M.shape != 3*(self.cryodata.N,):
M = cryoem.resize_ndarray(M,3*(self.cryodata.N,),axes=(0,1,2))
else:
init_seed = self.cparams.get('init_random_seed',0) + self.cparams.get('partition',0)
print "Randomly generating initial density (init_random_seed = {0})...".format(init_seed), ; sys.stdout.flush()
tic = time.time()
M = cryoem.generate_phantom_density(self.cryodata.N, 0.95*self.cryodata.N/2.0, \
5*self.cryodata.N/128.0, 30, seed=init_seed)
print "done in {0}s".format(time.time() - tic)
tic = time.time()
print "Windowing and aligning initial density...", ; sys.stdout.flush()
# window the initial density
wfunc = self.cparams.get('init_window','circle')
cryoem.window(M,wfunc)
# Center and orient the initial density
cryoem.align_density(M)
print "done in {0:.2f}s".format(time.time() - tic)
# apply the symmetry operator
init_sym = get_symmetryop(self.cparams.get('init_symmetry',self.cparams.get('symmetry',None)))
if init_sym is not None:
tic = time.time()
print "Applying symmetry operator...", ; sys.stdout.flush()
M = init_sym.apply(M)
print "done in {0:.2f}s".format(time.time() - tic)
tic = time.time()
print "Scaling initial model...", ; sys.stdout.flush()
modelscale = self.cparams.get('modelscale','auto')
mleDC, _, mleDC_est_std = self.cryodata.get_dc_estimate()
if modelscale == 'auto':
# Err on the side of a weaker prior by using a larger value for modelscale
modelscale = (n.abs(mleDC) + 2*mleDC_est_std)/self.cryodata.N
print "estimated modelscale = {0:.3g}...".format(modelscale), ; sys.stdout.flush()
self.params['modelscale'] = modelscale
self.cparams['modelscale'] = modelscale
M *= modelscale/M.sum()
print "done in {0:.2f}s".format(time.time() - tic)
if mleDC_est_std/n.abs(mleDC) > 0.05:
print " WARNING: the DC component estimate has a high relative variance, it may be inaccurate!"
if ((modelscale*self.cryodata.N - n.abs(mleDC)) / mleDC_est_std) > 3:
print " WARNING: the selected modelscale value is more than 3 std devs different than the estimated one. Be sure this is correct."
self.M = n.require(M,dtype=density.real_t)
self.fM = density.real_to_fspace(M)
self.dM = density.zeros_like(self.M)
self.step = eval(self.cparams['optim_algo'])
self.step.setup(self.cparams, self.diagout, self.statout, self.ostream)
# Objective function setup --------------------------------------------
param_type = self.cparams.get('parameterization','real')
cplx_param = param_type in ['complex','complex_coeff','complex_herm_coeff']
self.like_func = eval_objective(self.cparams['likelihood'])
self.prior_func = eval_objective(self.cparams['prior'])
if self.cparams.get('penalty',None) is not None:
self.penalty_func = eval_objective(self.cparams['penalty'])
prior_func = SumObjectives(self.prior_func.fspace, \
[self.penalty_func,self.prior_func], None)
else:
prior_func = self.prior_func
self.obj = SumObjectives(cplx_param,
[self.like_func,prior_func], [None,None])
self.obj.setup(self.cparams, self.diagout, self.statout, self.ostream)
self.obj.set_dataset(self.cryodata)
self.obj_wrapper = ObjectiveWrapper(param_type)
self.last_save = time.time()
self.logpost_history = FiniteRunningSum()
self.like_history = FiniteRunningSum()
# Importance Samplers -------------------------------------------------
self.is_sym = get_symmetryop(self.cparams.get('is_symmetry',self.cparams.get('symmetry',None)))
self.sampler_R = FixedFisherImportanceSampler('_R',self.is_sym)
self.sampler_I = FixedFisherImportanceSampler('_I')
self.sampler_S = FixedGaussianImportanceSampler('_S')
self.like_func.set_samplers(sampler_R=self.sampler_R,sampler_I=self.sampler_I,sampler_S=self.sampler_S)
