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 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 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)