def _session_hook(self):
from matlab.engine import start_matlab
startup_ops = '-nodesktop -nodisplay' if self._num_threads != 1 else \
'-nodesktop -nodisplay -singleCompThread'
try:
return start_matlab(startup_ops)
except:
return start_matlab()
def _session_hook(self):
from matlab.engine import start_matlab
startup_ops = '-nodesktop -nodisplay' if self._num_threads != 1 else \
'-nodesktop -nodisplay -singleCompThread'
try:
return start_matlab(startup_ops)
except:
return start_matlab()
def _start_matlab(self,
event: mp.Event,
alive_check_period=60,
startup_options=None,
shared_name=None):
pid = mp.current_process().pid
logger.info('Starting Matlab engine "{}" helper process {}...',
shared_name, pid)
self._terminate_event.clear()
event.clear()
try:
if startup_options is None:
eng = me.start_matlab()
else:
eng = me.start_matlab(startup_options)
if shared_name:
eng.matlab.engine.shareEngine(shared_name, nargout=0)
else:
eng.matlab.engine.shareEngine(nargout=0)
shared_name = eng.matlab.engine.engineName(nargout=1)
logger.info('Matlab engine "{}" is started', shared_name)
except (me.EngineError, me.MatlabExecutionError):
logger.exception('Cannot start Matlab engine "{}"', shared_name)
raise
finally:
event.set()
while not self._terminate_event.is_set():
# Is matlab alive?
try:
eng.version(nargout=0)
except (me.EngineError, me.CancelledError):
break
try:
time.sleep(alive_check_period)
except KeyboardInterrupt:
break
try:
eng.exit()
except SystemError:
logger.exception('Cannot terminate Matlab process correctly')
else:
logger.info('Terminate Matlab engine "{}" helper process {}',
shared_name, pid)
def get_matlab_engine():
if sys.platform == 'win32':
matlab = get_preferred_matlab()
if not matlab:
warnings.warn(
"MATLAB not found in registry. Using Python implementation.",
RuntimeWarning)
return None
if matlab[0] == platform.architecture()[0]:
MATLABROOT = matlab[2]
engine = import_matlab_python_engine(MATLABROOT)
return MatlabInProcessProxyReplacement(engine.start_matlab())
else:
python_exe = os.path.join(
os.path.dirname(os.path.abspath(__file__)),
'dist_{}\\python.exe'.format(matlab[0]))
if not os.path.isfile(python_exe):
raise Exception(
"'{}' does not exist. Run `setup.py py2exe` with Python {} in the matlab_proxy dir"
.format(python_exe, matlab[0]))
return get_engine_proxy(matlab[2], python_exe, matlab[0])
try:
import matlab.engine
return MatlabInProcessProxyReplacement(matlab.engine.start_matlab())
except ImportError as e:
warnings.warn("Failed to import matlab.engine: %s" % e, RuntimeWarning)
return None
def getFinalScore(A, B, H, Pa, Pb, node_A=None, node_B=None):
eng = mateng.start_matlab()
if node_A is None and node_B is None:
node_A = np.ones((A.get_shape()[0], 1))
node_B = np.ones((B.get_shape()[0], 1))
else:
node_A = node_A.reshape((node_A.shape[0], 1))
if np.array_equal(node_A, Pa.dot(node_A)):
print "node_A == Pa.dot(node_A)"
node_A = Pa.dot(node_A)
node_B = node_B.reshape((node_B.shape[0], 1))
if np.array_equal(node_B, Pb.dot(node_B)):
print "node_B == Pb.dot(node_B)"
node_B = Pb.dot(node_B)
io.savemat('temp_final.mat',
dict(A=A, B=B, H=H, Pa=Pa, Pb=Pb, node_A=node_A, node_B=node_B))
accuracy, ma, mb = eng.runFinal(nargout=3)
matching_matrix = getCSRMatrix(A.shape, ma, mb)
print "final: " + str(accuracy)
eng.quit()
return accuracy, matching_matrix
def _runMatlabCode(matrix, matlab_session):
#matrix = scipy.sparse.coo_matrix(matrix)
dir = os.path.dirname(__file__)
visuAddress = os.path.join(dir, "GenLouvain-master")
#print("saving matrix for matlab ")
scipy.io.savemat(visuAddress + '/file.mat', {"B": matrix})
result_file = visuAddress + '/result.mat'
###matFormat = matlab.double(matrix.tolist())
#print("starting matlab engine")
eng = matlab_session
if eng == None:
eng = engine.start_matlab()
eng.addpath(visuAddress, nargout=0)
#print("matlab engine started successfully")
start_time = time.time()
out = io.StringIO()
err = io.StringIO()
#(S, Q) = eng.genlouvain('file.mat', nargout=2)
eng.genlouvain('file.mat', result_file, stdout=out, stderr=err)
duration = time.time() - start_time
#print("matlab code ran successfully")
#print(err.getvalue())
res = scipy.io.loadmat(result_file)
S = res["S"]
return (S, duration)
def parse_annotations(args): eng = mateng.start_matlab() [s, X] = eng.read_binary_blob(args.PATH_TO_DATA + '176.conv5b', nargout = 2) color = 'b' i = 0 for label in all_segments: print "Parsing label " + label segments = all_segments[label] if label == '2': color = 'r' elif label == '3': color = 'g' else: color = 'b' for seg in segments: j = seg[0] while j <= seg[1]: if j == 176: color_map[i] = color index_map[i] = j j += 16 i += 1 continue [s, data] = eng.read_binary_blob(args.PATH_TO_DATA + str(j) + '.conv5b', nargout = 2) data = np.array(data) X = np.concatenate((X, data), axis = 0) color_map[i] = color index_map[i] = j j += 16 i += 1 return X
def main():
"""
Run the preprocess functionality on each of the participant directories. Some of the
values for the current study are hard coded into this file for ease of use.
"""
parser = ArgumentParser()
parser.add_argument("inputDir")
parser.add_argument("outputDir")
args = parser.parse_args()
directory = args.inputDir
outputDirectory = args.outputDir
intervalSize = 5
trialLength = 600
# Start a matlab instance to speed up repeated processes
eng = start_matlab()
participantIds = [ '001', '002', '003', '004', '005', '006', '007']
for participantId in participantIds:
participantDir = path.join( directory, participantId )
preprocess( participantDir, outputDirectory, intervalSize, trialLength, eng )
eng.quit()
def parse_annotations_pickle(annotations_file, PATH_TO_DATA):
index_map = {}
label_map = {}
eng = mateng.start_matlab()
map_index_data = pickle.load(open(annotations_file, "rb"))
X = None
i = 0
for index in map_index_data:
print "Parsing label " + str(index)
segments = map_index_data[index]
color = np.random.rand(3,1)
for seg in segments:
j = seg[0]
while j <= seg[1]:
if X is None:
[s, X] = eng.read_binary_blob(PATH_TO_DATA + str(j) + '.conv5b', nargout = 2)
else:
[s, data] = eng.read_binary_blob(PATH_TO_DATA + str(j) + '.conv5b', nargout = 2)
data = np.array(data)
X = np.concatenate((X, data), axis = 0)
index_map[i] = j
label_map[i] = index
j += 16
i += 1
return X, label_map, index_map
def standard_methods_to_test():
eng = engine.start_matlab()
def smoothed_louvain(x, elapsed_time=True):
return tn.DCD.iterative_match(x,
CDalgo="smoothedLouvain",
elapsed_time=elapsed_time)
# methods_to_test = {"iterative":DCD.iterative_match,"dynamo":dynamo,"dynmoga":dynmoga,"smoothed_louvain":smoothed_louvain}
def mucha_opti(x, elapsed_time=True):
return transversal_network_mucha_original(x,
elapsed_time=elapsed_time,
matlab_session=eng)
def mucha_global(x, elapsed_time=True):
return transversal_network_mucha_original(x,
elapsed_time=elapsed_time,
matlab_session=eng,
form="global")
print("pas de mucha")
methods_to_test = {
"iterative": tn.DCD.iterative_match,
"dynamo": dynamo,
"smoothed_louvain": smoothed_louvain,
"mucha": mucha_opti, # "mucha_global":mucha_global,
"survival_graph": tn.DCD.label_smoothing
} # ,"dynmoga":dynmoga}#
# methods_to_test = {"smoothed_louvain":smoothed_louvain}#,"dynmoga":dynmoga}#
return methods_to_test
def main(scp):
data = load_data(scp)
params = []
bot = top = 0
for line in data:
line = line.strip().split()
fin = line[0]
gender = line[1]
fout = line[2]
des = fout.split("/")[:-1]
des = "/".join(des)
if gender == "M":
bot = 50.0
top = 300.0
#continue
else:
#continue
bot = 75.0
top = 500.0
#param = [[fin], [bot], [top], [fout]]
#param = [fin, des, fout, bot, top]
param = [fin, des, fout, bot, top]
params.append(param)
eng = me.start_matlab()
eng.f0_extraction_parallel(params, nargout=0)
eng.quit()
print("Done with f0 extraction...")
def main():
"""
Run the preprocess functionality on each of the participant directories. Some of the
values for the current study are hard coded into this file for ease of use.
"""
parser = ArgumentParser()
parser.add_argument("inputDir")
parser.add_argument("outputDir")
args = parser.parse_args()
directory = args.inputDir
outputDirectory = args.outputDir
intervalSize = 5
trialLength = 600
# Start a matlab instance to speed up repeated processes
eng = start_matlab()
participantIds = ['001', '002', '003', '004', '005', '006', '007']
for participantId in participantIds:
participantDir = path.join(directory, participantId)
preprocess(participantDir, outputDirectory, intervalSize, trialLength,
eng)
eng.quit()
def run1(GUI2):
initSignal(GUI2)
eng = engine.start_matlab()
eng.cd(r'.\2')
def send1():
GUI2.signal1.emit(eng)
def send2():
GUI2.signal2.emit(eng)
def send3():
GUI2.signal3.emit(eng)
def send4():
GUI2.signal4.emit(eng)
def send5():
GUI2.signal5.emit(eng)
GUI2.firstButton1.clicked.connect(send1)
GUI2.secondButton1.clicked.connect(send2)
GUI2.secondButton2.clicked.connect(send3)
GUI2.thirdButton1.clicked.connect(send4)
GUI2.thirdButton2.clicked.connect(send5)
def warping(anno_dic, gaze_dic, ref_img_name, gaze_path=None, save=False):
'''
Warps the gaze coordinates of the required image to the plane of a reference image using Thin Plate Spline
transformation and saves the resultant coordinates in a new csv file.
:param anno_dic: dictionary with image names and list of annotated coordinates as key value pair.
:param gaze_dic: dictionary with image names and list of gaze coordinates as key value pair.
:param ref_img_name: Reference image name as string.
:param gaze_path: string that gives the path to the gaze files
:param save: boolean to save the output warped gaze data to a csv file.
:return: None
'''
warped_dict = {}
eng = me.start_matlab()
ref_annos = m.double(
np.transpose(np.array(anno_dic[ref_img_name])).tolist())
for img in anno_dic:
annotations = m.double(np.transpose(np.array(anno_dic[img])).tolist())
if np.shape(np.array(annotations))[1] == np.shape(
np.array(ref_annos))[1]:
gaze = m.double(np.transpose(np.array(gaze_dic[img])).tolist())
tps = eng.tpaps(annotations, ref_annos)
warp = eng.fnval(tps, gaze)
warp_ = np.transpose(np.array(warp)).tolist()
warp_ = [[int(point[0]), int(point[1])] for point in warp_]
if save is True:
with open(gaze_path + 'output_warped/' + img + '.csv',
'wb') as cs:
writer = csv.writer(cs, delimiter=',')
for point in warp_:
writer.writerow(point)
warped_dict[img] = warp_
# print('Done Warping!')
return warped_dict
def _connect_matlab_engine(self, use_existing=True, persistent=True):
"""
Connect to a matlab engine, starting a new one if it hasn't been started yet
:return:
"""
found_eng = False
if use_existing:
eng_names = engine.find_matlab()
for eng_name in eng_names:
try:
self.eng = engine.connect_matlab(eng_name)
self.eng_name = eng_name
found_eng = True
# unable to connect to an instance because it already has a connection
except matlab.engine.EngineError:
pass
if found_eng:
break
if not found_eng:
# if we're making a new persistent engine, create it
if persistent:
self.eng_name = self._start_persistent_shared_matlab()
self.eng = engine.connect_matlab(self.eng_name)
# otherwise, make a new engine just for the lifetime of self
else:
self.eng = engine.start_matlab()
self.eng_name = None # to be explicit
self.eng_deleted = False
def _runMatlabCode(dummy_coms_files, graphs_files, T, ouput_file):
dir = os.path.dirname(__file__)
visuAddress = os.path.join(dir, "DYNMOGA2015b-2")
print("starting matlab engine")
eng = engine.start_matlab()
eng.addpath(visuAddress, nargout=0)
print("matlab engine started successfully")
start_time = time.time()
out = io.StringIO()
err = io.StringIO()
#(S, Q) = eng.genlouvain('file.mat', nargout=2)
try:
eng.run_DYNMOGA(dummy_coms_files,
graphs_files,
T,
ouput_file,
stdout=out,
stderr=err,
nargout=0)
except:
print(err.getvalue())
print(out.getvalue())
print("matlab code ran successfully")
#print(err.getvalue())
duration = time.time() - start_time
return (duration)
def __init__(self, logger, beh):
import matlab.engine as eng
self.mat = eng.start_matlab()
self.mat.run('c:/pipeline/pipeline/setPath.m', nargout=0)
self.mat.run('c:/pipeline/pipeline/setDJ.m', nargout=0)
self.trial = []
super(DaqPiezoStim, self).__init__(logger, beh)
def parseAndRemoveBaseline(inputFilename, outputDirectory, eng=None):
"""
Parse the specified input EDF file, remove baseline, and write the
relevant channel data out to a tab-separated text file that can be more
easily read. A matlab engine can be passed in to cut down on processing time.
Returns the name of the file the data was written to.
"""
outputFilename = path.join(outputDirectory, "eeg_parsed.txt")
existing = True
# Create a matlab instance if one was not provided
if eng == None:
eng = start_matlab()
existing = False
# Add the current directory to the matlab path so that the function can be found
eng.addpath(dirname(realpath(__file__)))
eng.ParseEEG(inputFilename, outputFilename, nargout=0)
eng.clc(nargout=0)
eng.clear(nargout=0)
# Shutdown matlab if it was created here
if not existing:
eng.quit()
return outputFilename
def __init__(self, logger, beh):
import matlab.engine as eng
self.mat = eng.start_matlab()
self.mat.run('/home/atlab/pipeline/setPath.m', nargout=0)
self.mat.run('/home/atlab/pipeline/setDJ.m', nargout=0)
self.trial = []
super(Psychtoolbox, self).__init__(logger, beh)
def parse_annotations(args):
eng = mateng.start_matlab()
[s, X] = eng.read_binary_blob(args.PATH_TO_DATA + '176.conv5b', nargout=2)
color = 'b'
i = 0
for label in all_segments:
print "Parsing label " + label
segments = all_segments[label]
if label == '2':
color = 'r'
elif label == '3':
color = 'g'
else:
color = 'b'
for seg in segments:
j = seg[0]
while j <= seg[1]:
if j == 176:
color_map[i] = color
index_map[i] = j
j += 16
i += 1
continue
[s, data] = eng.read_binary_blob(args.PATH_TO_DATA + str(j) +
'.conv5b',
nargout=2)
data = np.array(data)
X = np.concatenate((X, data), axis=0)
color_map[i] = color
index_map[i] = j
j += 16
i += 1
return X
def parse_annotations_pickle(annotations_file, PATH_TO_DATA):
index_map = {}
label_map = {}
eng = mateng.start_matlab()
map_index_data = pickle.load(open(annotations_file, "rb"))
X = None
i = 0
for index in map_index_data:
print "Parsing label " + str(index)
segments = map_index_data[index]
color = np.random.rand(3, 1)
for seg in segments:
j = seg[0]
while j <= seg[1]:
if X is None:
[s, X] = eng.read_binary_blob(PATH_TO_DATA + str(j) +
'.conv5b',
nargout=2)
else:
[s, data] = eng.read_binary_blob(PATH_TO_DATA + str(j) +
'.conv5b',
nargout=2)
data = np.array(data)
X = np.concatenate((X, data), axis=0)
index_map[i] = j
label_map[i] = index
j += 16
i += 1
return X, label_map, index_map
def parseAndRemoveBaseline( inputFilename, outputDirectory, eng = None ): """ Parse the specified input EDF file, remove baseline, and write the relevant channel data out to a tab-separated text file that can be more easily read. A matlab engine can be passed in to cut down on processing time. Returns the name of the file the data was written to. """ outputFilename = path.join( outputDirectory, "eeg_parsed.txt" ) existing = True # Create a matlab instance if one was not provided if eng == None: eng = start_matlab() existing = False # Add the current directory to the matlab path so that the function can be found eng.addpath( dirname(realpath(__file__)) ) eng.ParseEEG( inputFilename, outputFilename, nargout=0) eng.clc(nargout = 0) eng.clear(nargout = 0) # Shutdown matlab if it was created here if not existing: eng.quit() return outputFilename
def _start_matlab(self,
event: mp.Event,
alive_check_period=60,
startup_options=None,
shared_name=None):
pid = mp.current_process().pid
self._pid.value = pid
logger.info('Starting matlab engine "{}" helper process {}',
shared_name, pid)
event.clear()
if startup_options is None:
eng = me.start_matlab()
else:
eng = me.start_matlab(startup_options)
try:
if shared_name:
eng.matlab.engine.shareEngine(shared_name, nargout=0)
else:
eng.matlab.engine.shareEngine(nargout=0)
shared_name = eng.matlab.engine.engineName(nargout=1)
logger.info('Matlab shared engine "{}" is started', shared_name)
except me.MatlabExecutionError:
logger.exception('Cannot start Matlab shared engine "{}"',
shared_name)
raise
finally:
event.set()
while self._pid.value != -1:
# Is matlab alive?
try:
eng.version(nargout=0)
except me.EngineError:
break
time.sleep(alive_check_period)
if eng._check_matlab():
eng.exit()
logger.info('Terminate matlab engine "{}" helper process {}',
shared_name, pid)
def get_matlab_engine():
"""
Returns matlab engine with path to functions for WSI appended
"""
matlab_dir = os.path.dirname(__file__)
eng = engine.start_matlab()
eng.cd(r'{}'.format(matlab_dir), nargout=0)
return eng
def __init__(self, *args, **kwargs) -> None:
# Init base class
QuadrigaInterface.__init__(self, *args, **kwargs)
# Start the matlab engine
self.__engine = start_matlab()
def _start_matlab(self,
event: mp.Event,
alive_check_period=60,
startup_options=None,
shared_name=None):
pid = mp.current_process().pid
self._pid.value = pid
print('Start matlab process %s with process ID {}'.format(pid) %
shared_name)
event.clear()
if startup_options is None:
eng = me.start_matlab()
else:
eng = me.start_matlab(startup_options)
try:
if shared_name:
eng.matlab.engine.shareEngine(shared_name, nargout=0)
else:
eng.matlab.engine.shareEngine(nargout=0)
shared_name = eng.matlab.engine.engineName(nargout=1)
print('Matlab shared engine {} is started'.format(shared_name))
except me.MatlabExecutionError:
raise
finally:
event.set()
while self._pid.value != -1:
# Is matlab alive?
try:
eng.version(nargout=0)
except me.EngineError:
break
time.sleep(alive_check_period)
if eng._check_matlab(): eng.exit()
print(
'Terminate matlab helper process %s with process ID {}'.format(pid)
% shared_name)
def __init__(
self,
m_file_path,
benchmark_os_path,
parallel,
shared_engine=None #TAG:MSH
):
self.parallel = parallel
import matlab.engine as matlab_engine
import matlab as matlab
# Don't seem to nee matlab.engine other than to start the matlab
# session.
# self.matlab_engine = matlab_engine
self.matlab = matlab
#TAG:MSH
if shared_engine is None:
print 'starting matlab...'
self.eng = matlab_engine.start_matlab()
print 'done'
else:
print 'attempting to connect to an existing matlab session'
self.eng = matlab_engine.connect_matlab(shared_engine)
self.m_file = m_file_path
m_file_name_split = self.m_file.split('.')
if m_file_name_split[1].strip() != 'm':
raise err.Fatal('internal error!')
self.m_fun_str = m_file_name_split[0].strip()
# self.sim_fun = self.eng.simulate_m_file(1)
# add paths
# comm.call_function([], 'addpath', [SQ + benchmark_os_path + SQ])
self.eng.addpath(benchmark_os_path)
#TAG:CLSS
# TODO: Remove this hack. Added for backwards compatibility
# detect if the simulator file is a function or a class
# source: http://blogs.mathworks.com/loren/2013/08/26/what-kind-of-matlab-file-is-this/
# classy = 8 if class else is 0 (function or a script)
classy = self.eng.exist(self.m_fun_str, 'class')
if classy == 0.0:
print 'maltab file is a function'
self.sim_is_class = False
elif classy == 8.0:
print 'maltab file is a class'
self.sim_is_class = True
self.sim_obj = self.eng.init_plant(self.m_fun_str)
else:
raise err.Fatal(
'''Supplied matlab simulator is neither a class or a function:
possible floating point error?. exist() returned: {}'''.format(
classy))
def start_engine() -> Any:
""" """
return
global MATLAB_ENGINE
if not MATLAB_ENGINE:
from matlab import engine
print("Starting Matlab")
if True:
MATLAB_ENGINE = engine.start_matlab()
else:
future = engine.start_matlab(background=True)
MATLAB_ENGINE = future.result()
print("Matlab started")
else:
print("Matlab already running")
return MATLAB_ENGINE
def __init__(self, filepath):
super().__init__()
self.filepath = filepath
start_time = time()
print("Initializing IMU...")
self.eng = m_engine.start_matlab()
print("Initialization Complete. Time elapsed: {0}s".format(time() -
start_time))
self.eng.addpath(os.path.join(config.ROOT_DIR, '3rd_party_scripts'))
def getNetalignScore(A, B, L, Pa, Pb):
eng = mateng.start_matlab()
# eng.saveMat(matlab.double(A.tolist()), matlab.double(B.tolist()), matlab.double(L.tolist()), s, nargout=0)
io.savemat('temp.mat', dict(A=A, B=B, L=L, Pa=Pa, Pb=Pb))
accuracy = eng.runNetalign(nargout=1)
print "netalign: " + str(accuracy)
eng.quit()
return accuracy
def __init__(self):
self.mod_name = 'model_path.mat'
self.max_pos = [850, 700]
self.min_pos = [0, 0]
self.engine = me.start_matlab()
self.model = self.engine.ModelLoader(self.mod_name)
self.mc = MC.Motorcontrol()
self.mc.setup()
self.grabPos = [0]
self.currPos = [0, 0]
def __init__(
self,
m_file_path,
benchmark_os_path,
parallel,
shared_engine=None #TAG:MSH
):
self.parallel = parallel
import matlab.engine as matlab_engine
import matlab as matlab
# Don't seem to nee matlab.engine other than to start the matlab
# session.
# self.matlab_engine = matlab_engine
self.matlab = matlab
#TAG:MSH
if shared_engine is None:
print 'starting matlab...'
self.eng = matlab_engine.start_matlab()
print 'done'
else:
print 'attempting to connect to an existing matlab session'
self.eng = matlab_engine.connect_matlab(shared_engine)
self.m_file = m_file_path
m_file_name_split = self.m_file.split('.')
if m_file_name_split[1].strip() != 'm':
raise err.Fatal('internal error!')
self.m_fun_str = m_file_name_split[0].strip()
# self.sim_fun = self.eng.simulate_m_file(1)
# add paths
# comm.call_function([], 'addpath', [SQ + benchmark_os_path + SQ])
self.eng.addpath(benchmark_os_path)
#TAG:CLSS
# TODO: Remove this hack. Added for backwards compatibility
# detect if the simulator file is a function or a class
# source: http://blogs.mathworks.com/loren/2013/08/26/what-kind-of-matlab-file-is-this/
# classy = 8 if class else is 0 (function or a script)
classy = self.eng.exist(self.m_fun_str, 'class')
if classy == 0.0:
print 'maltab file is a function'
self.sim_is_class = False
elif classy == 8.0:
print 'maltab file is a class'
self.sim_is_class = True
self.sim_obj = self.eng.init_plant(self.m_fun_str)
else:
raise err.Fatal('''Supplied matlab simulator is neither a class or a function:
possible floating point error?. exist() returned: {}'''.format(classy))
def parse(): eng = mateng.start_matlab() [s, X] = eng.read_binary_blob(PATH_TO_DATA + '1.conv5b', nargout = 2) i = 17; while i <= 1489: [s, data] = eng.read_binary_blob(PATH_TO_DATA + str(i) + '.conv5b', nargout = 2) data = np.array(data) X = np.concatenate((X, data), axis = 0) i += 16 return X
def __init__(self, input_image):
print("Matlab engine initialization started")
self._matlab_eng = start_matlab()
# changing directory to the one with matlab functions
self._matlab_eng.cd("..\\PSO\\MatlabFiles")
matlab_img = matlab.double(input_image.tolist())
super().__init__(matlab_img)
self._matlab_eng.initialize_mat(matlab_img, nargout=0)
#super().__init__(matlab.double(input_image))
print("Matlab engine initialization finished")
def parse(): eng = mateng.start_matlab() [s, X] = eng.read_binary_blob(PATH_TO_DATA + '1.conv5b', nargout = 2) i = 17; while i <= 1489: [s, data] = eng.read_binary_blob(PATH_TO_DATA + str(i) + '.conv5b', nargout = 2) data = np.array(data) X = np.concatenate((X, data), axis = 0) i += 16 return X
def getIsoRankScore(A, B, L, Pa, Pb):
eng = mateng.start_matlab()
# eng.saveMat(matlab.double(A.tolist()), matlab.double(B.tolist()), matlab.double(L.tolist()), s, nargout=0)
io.savemat('temp_iso.mat', dict(A=A, B=B, L=L, Pa=Pa, Pb=Pb))
accuracy = eng.runIsoRank(nargout=1)
print "isorank: " + str(accuracy)
eng.quit()
return accuracy
def __init__(self, logger, beh):
import matlab.engine as eng
self.mat = eng.start_matlab()
self.mat.run('c:/pipeline/pipeline/setPath.m', nargout=0)
# get datajoint info from environment variables set in startup script
self.mat.setenv('DJ_HOST',os.getenv('DJ_HOST'),nargout=0)
self.mat.setenv('DJ_USER',os.getenv('DJ_USER'),nargout=0)
self.mat.setenv('DJ_PASS',os.getenv('DJ_PASS'),nargout=0)
self.trial = []
super(DaqStim, self).__init__(logger, beh)
def processChannelFile( filename, eng = None ):
"""
Process a single channel file, creating band information
for each segment of data. A matlab engine can be passed
in to reduce overhead.
Returns a 2D list of band information in the order: [ delta, theta,
alpha, beta, gamma ] for each time interval
"""
existing = True
# Create a new matlab instance if one was not provided
if eng == None:
eng = start_matlab()
existing = False
# Add the current directory to the matlab path so that the function can be found
eng.addpath( dirname(realpath(__file__)) )
channelData = []
with open( filename ) as fin:
for line in fin:
contents = line.strip().split('\t')
# Remove the time stamp
contents.pop(0)
# Cast the elements to floats
values = [ float(ele) for ele in contents ]
# Make a matlab array from the data
mArray = matlab.double(values)
bands = eng.Bandify( mArray, nargout = 5 )
eng.clc(nargout = 0)
eng.clear(nargout = 0)
channelData.append( bands )
# Shutdown matlab if it was created here
if not existing:
eng.quit()
return channelData
def cca(W, Z): """ Canonical Correlation Analysis (CCA): Returns rows of Z which are maximally correlated to W. """ print "CCA....." import matlab import matlab.engine as mateng eng = mateng.start_matlab() W_mat = matlab.double(W.tolist()) Z_mat = matlab.double(Z.tolist()) [A, B, r, U, V, stats] = eng.canoncorr(W_mat, Z_mat, nargout = 6) Z = np.array(V) eng.quit() return Z
def main():
print strftime("start time: %H:%M:%S")
setGatewayIP()
time.sleep(1)
recordSound()
# start matlab object
eng = mat.start_matlab()
ret = eng.soundtest(WAVE_OUTPUT_FILENAME)
if int(ret) > 3:
print "found %d" % ret
getSnapShot()
person = findPerson("detected", "image.jpg")
person = person.split("\\")[1]
print person, People[person]
if person != None:
sendSMS(ret, person)
getVideo()
sendEmail()
print strftime("end time: %H:%M:%S")
def get_matlab_engine():
if sys.platform == 'win32':
matlab = get_preferred_matlab()
if not matlab:
warnings.warn("MATLAB not found in registry. Using Python implementation.", RuntimeWarning)
return None
if matlab[0] == platform.architecture()[0]:
MATLABROOT = matlab[2]
engine = import_matlab_python_engine(MATLABROOT)
return MatlabInProcessProxyReplacement(engine.start_matlab())
else:
python_exe = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'dist_{}\\python.exe'.format(matlab[0]))
if not os.path.isfile(python_exe):
raise Exception("'{}' does not exist. Run `setup.py py2exe` with Python {} in the matlab_proxy dir".format(python_exe, matlab[0]))
return get_engine_proxy(matlab[2], python_exe)
try:
import matlab.engine
return MatlabInProcessProxyReplacement(matlab.engine.start_matlab())
except ImportError as e:
warnings.warn("Failed to import matlab.engine: %s" % e, RuntimeWarning)
return None
def before__first_request_():
global eng
global mappedX
global cl_idx
global Wtopk
global voca
global distanceMatrix
global distanceMatrix_main
tic = time.time()
print "Starting matlab - ",
eng = engine.start_matlab()
eng.cd(os.path.dirname(os.getcwd()))
print "%.4f" % (time.time() - tic)
tic = time.time()
# dataset
# vis=0
# cnn=1
# nyt=2
# dataset=2
# if dataset ==0:
# eng.main_topic(nargout=0)
# distanceMatrix = io.loadmat('./../Visdata.mat')['DD']
# elif dataset ==1:
# eng.main_cnn(nargout=0)
# distanceMatrix = io.loadmat('./../result2.mat')['DD']
# else:
eng.main_nyt(nargout=0)
distanceMatrix = io.loadmat("./../nyt.mat")["DD"]
mappedX = eng.workspace["mappedX"]
cl_idx = eng.workspace["cl_idx"]
Wtopk_idx = eng.workspace["Wtopk_idx"]
voca = eng.workspace["dict"]
print "%.4f" % (time.time() - tic)
tic = time.time()
print "Calculate data - ",
Wtopk = []
for idxArray in Wtopk_idx:
tempArray = []
for idx in idxArray:
tempArray.append(voca[int(idx) - 1])
Wtopk.append(tempArray)
cl_idx = cl_idx[0]
# cl_idx = cl_idx
# distanceMatrix = distanceMatrix
# cl_idx = cl_idx
# distanceMatrix = distanceMatrix
sameTopicWeight = 0.8
differentTopicWeight = 1.2
distanceMatrix_main = supervisedTSNE(
distanceMatrix, cl_idx, sameTopicWeight=sameTopicWeight, differentTopicWeight=differentTopicWeight
)
print "%.4f" % (time.time() - tic)
distanceMatrix_main = distanceMatrix_main.tolist()
def build_sample_graph(self):
####### Things that happen at system boot ########
#Users
self.add_user_node('HR1')
self.add_user_node('HR2')
self.add_user_node('HR3')
self.add_user_node('HR4')
self.add_user_node('HR5')
self.add_user_node('CEO')
self.add_user_node('Dev1')
self.add_user_node('Dev2')
self.add_user_node('Dev3')
self.add_user_node('Intern')
self.add_user_node('External')
#Machines
self.add_machine_node('HR-laptop1.company.com')
self.add_machine_node('HR-laptop2.company.com')
self.add_machine_node('HR-laptop3.company.com')
self.add_machine_node('HR-laptop4.company.com')
self.add_machine_node('HR-laptop5.company.com')
self.add_machine_node('HR-front-desk.company.com')
self.add_machine_node('CEO-laptop.company.com')
self.add_machine_node('CEO-desktop.company.com')
self.add_machine_node('Dev-laptop1.company.com')
self.add_machine_node('Dev-laptop2.company.com')
self.add_machine_node('Dev-laptop3.company.com')
self.add_machine_node('Dev-desktop1.company.com')
self.add_machine_node('Dev-desktop2.company.com')
self.add_machine_node('Dev-desktop3.company.com')
self.add_machine_node('extra-computer1.company.com')
self.add_machine_node('extra-computer2.company.com')
self.add_machine_node('server.company.com')
self.add_machine_node('database.company.com')
self.add_machine_node('use-cluster.company.com')
self.add_machine_node('sandbox-cluster.company.com')
self.add_machine_node('R1')
self.add_machine_node('R2')
self.add_machine_node('R3')
#Applications
self.add_application_node('ETR')
self.add_application_node('payroll-app')
self.add_application_node('website-host')
self.add_application_node('email-host')
self.add_application_node('website-backup')
self.add_application_node('employee-database')
#Physical Topology
self.add_physical_edge('R1', 'R2',0,20)
self.add_physical_edge('R1', 'R3',0)
self.add_physical_edge('HR-laptop1.company.com', 'R3',0)
self.add_physical_edge('HR-laptop2.company.com', 'R3',0)
self.add_physical_edge('HR-laptop3.company.com', 'R3',0)
self.add_physical_edge('HR-laptop4.company.com', 'R3',0)
self.add_physical_edge('HR-laptop5.company.com', 'R3',0)
self.add_physical_edge('HR-front-desk.company.com', 'R3',0)
self.add_physical_edge('CEO-laptop.company.com', 'R3',0)
self.add_physical_edge('CEO-desktop.company.com', 'R3',0)
self.add_physical_edge('Dev-laptop1.company.com', 'R3',0)
self.add_physical_edge('Dev-laptop2.company.com', 'R3',0)
self.add_physical_edge('Dev-laptop3.company.com', 'R3',0)
self.add_physical_edge('Dev-desktop1.company.com', 'R3',0)
self.add_physical_edge('Dev-desktop2.company.com', 'R3',0)
self.add_physical_edge('Dev-desktop3.company.com', 'R3',0)
self.add_physical_edge('extra-computer1.company.com', 'R3',0)
self.add_physical_edge('extra-computer2.company.com', 'R3',0)
self.add_physical_edge('server.company.com', 'R2',0)
self.add_physical_edge('database.company.com', 'R2',0)
self.add_physical_edge('use-cluster.company.com', 'R2',0)
self.add_physical_edge('sandbox-cluster.company.com', 'R2',0)
#Access Control
self.add_access_edge('HR1', 'HR-laptop1.company.com', 'standard',0)
self.add_access_edge('Dev1', 'HR-laptop1.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'HR-laptop1.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'HR-laptop1.company.com', 'sudo',0)
self.add_access_edge('HR2', 'HR-laptop2.company.com', 'standard',0)
self.add_access_edge('Dev1', 'HR-laptop2.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'HR-laptop2.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'HR-laptop2.company.com', 'sudo',0)
self.add_access_edge('HR3', 'HR-laptop3.company.com', 'standard',0)
self.add_access_edge('Dev1', 'HR-laptop3.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'HR-laptop3.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'HR-laptop3.company.com', 'sudo',0)
self.add_access_edge('HR4', 'HR-laptop4.company.com', 'standard',0)
self.add_access_edge('Dev1', 'HR-laptop4.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'HR-laptop4.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'HR-laptop4.company.com', 'sudo',0)
self.add_access_edge('HR5', 'HR-laptop5.company.com', 'standard',0)
self.add_access_edge('Dev1', 'HR-laptop5.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'HR-laptop5.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'HR-laptop5.company.com', 'sudo',0)
self.add_access_edge('HR1', 'HR-front-desk.company.com', 'standard',0)
self.add_access_edge('HR2', 'HR-front-desk.company.com', 'standard',0)
self.add_access_edge('HR3', 'HR-front-desk.company.com', 'standard',0)
self.add_access_edge('HR4', 'HR-front-desk.company.com', 'standard',0)
self.add_access_edge('HR5', 'HR-front-desk.company.com', 'standard',0)
self.add_access_edge('Dev1', 'HR-front-desk.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'HR-front-desk.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'HR-front-desk.company.com', 'sudo',0)
self.add_access_edge('CEO', 'CEO-laptop.company.com', 'sudo',0)
self.add_access_edge('Dev1', 'CEO-laptop.company.com', 'sudo',0)
self.add_access_edge('CEO', 'CEO-desktop.company.com', 'sudo',0)
self.add_access_edge('Dev1', 'CEO-desktop.company.com', 'sudo',0)
self.add_access_edge('Dev1', 'Dev-laptop1.company.com', 'sudo',0)
self.add_access_edge('Dev1', 'Dev-desktop1.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'Dev-laptop2.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'Dev-desktop2.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'Dev-laptop3.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'Dev-desktop3.company.com', 'sudo',0)
self.add_access_edge('HR1', 'extra-computer1.company.com', 'standard',0)
self.add_access_edge('HR2', 'extra-computer1.company.com', 'standard',0)
self.add_access_edge('HR3', 'extra-computer1.company.com', 'standard',0)
self.add_access_edge('HR4', 'extra-computer1.company.com', 'standard',0)
self.add_access_edge('HR5', 'extra-computer1.company.com', 'standard',0)
self.add_access_edge('CEO', 'extra-computer1.company.com', 'standard',0)
self.add_access_edge('Intern', 'extra-computer1.company.com', 'standard',0)
self.add_access_edge('Dev1', 'extra-computer1.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'extra-computer1.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'extra-computer1.company.com', 'sudo',0)
self.add_access_edge('HR1', 'extra-computer2.company.com', 'standard',0)
self.add_access_edge('HR2', 'extra-computer2.company.com', 'standard',0)
self.add_access_edge('HR3', 'extra-computer2.company.com', 'standard',0)
self.add_access_edge('HR4', 'extra-computer2.company.com', 'standard',0)
self.add_access_edge('HR5', 'extra-computer2.company.com', 'standard',0)
self.add_access_edge('CEO', 'extra-computer2.company.com', 'standard',0)
self.add_access_edge('Intern', 'extra-computer2.company.com', 'standard',0)
self.add_access_edge('Dev1', 'extra-computer2.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'extra-computer2.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'extra-computer2.company.com', 'sudo',0)
self.add_access_edge('Dev1', 'server.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'server.company.com', 'standard',0)
self.add_access_edge('Dev1', 'database.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'database.company.com', 'standard',0)
self.add_access_edge('CEO', 'use-cluster.company.com', 'standard',0)
self.add_access_edge('Intern', 'use-cluster.company.com', 'standard',0)
self.add_access_edge('Dev1', 'use-cluster.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'use-cluster.company.com', 'sudo',0)
self.add_access_edge('Dev3', 'use-cluster.company.com', 'sudo',0)
self.add_access_edge('Dev1', 'sandbox-cluster.company.com', 'sudo',0)
self.add_access_edge('Dev2', 'sandbox-cluster.company.com', 'standard',0)
self.add_access_edge('Dev3', 'sandbox-cluster.company.com', 'standard',0)
#Systems
self.add_hosting_edge('ETR', 'use-cluster.company.com', 880,0)
self.add_hosting_edge('payroll-app', 'use-cluster.company.com', 50,0)
self.add_hosting_edge('website-host', 'server.company.com', 10,0)
self.add_hosting_edge('email-host', 'server.company.com', 80,0)
self.add_hosting_edge('website-backup', 'database.company.com', 880,0)
self.add_hosting_edge('employee-database', 'database.company.com', 62,0)
####### Set times ############
random.seed(seed)
flows = []
for i in range(200):
flows.append((random.uniform(0,200),'HR1', 'payroll-app', 'HR1'))
flows.append((random.uniform(0,200),'HR2', 'payroll-app', 'HR2'))
flows.append((random.uniform(0,200),'HR3', 'payroll-app', 'HR3'))
flows.append((random.uniform(0,200),'HR4', 'payroll-app', 'HR4'))
flows.append((random.uniform(0,200),'HR5', 'payroll-app', 'HR5'))
flows.append((random.uniform(0,200),'HR1', 'ETR', 'HR1'))
flows.append((random.uniform(0,200),'HR2', 'ETR', 'HR2'))
flows.append((random.uniform(0,200),'HR3', 'ETR', 'HR3'))
flows.append((random.uniform(0,200),'HR5', 'ETR', 'HR5'))
flows.append((random.uniform(0,200),'CEO', 'ETR', 'CEO'))
flows.append((random.uniform(0,200),'Dev1', 'ETR', 'Dev1'))
flows.append((random.uniform(0,200),'Dev2', 'ETR', 'Dev2'))
flows.append((random.uniform(0,200),'Dev3', 'ETR', 'Dev3'))
flows.append((random.uniform(0,200),'Intern', 'ETR', 'Intern'))
flows.append((random.uniform(0,200),'HR1', 'email-host', 'HR1'))
flows.append((random.uniform(0,200),'HR2', 'email-host', 'HR2'))
flows.append((random.uniform(0,200),'HR3', 'email-host', 'HR3'))
flows.append((random.uniform(0,200),'HR4', 'email-host', 'HR4'))
flows.append((random.uniform(0,200),'HR5', 'email-host', 'HR5'))
flows.append((random.uniform(0,200),'CEO', 'email-host', 'CEO'))
flows.append((random.uniform(0,200),'Dev1', 'email-host', 'Dev1'))
flows.append((random.uniform(0,200),'Dev2', 'email-host', 'Dev2'))
flows.append((random.uniform(0,200),'Dev3', 'email-host', 'Dev3'))
flows.append((random.uniform(0,200),'Intern', 'email-host', 'Intern'))
flows.append((random.uniform(0,200),'Dev2', 'website-host', 'Dev2'))
flows.append((random.uniform(0,200),'Dev3', 'employee-database', 'Dev3'))
flows.append((random.uniform(0,200),'payroll-app', 'ETR', 'Dev1'))
flows.append((random.uniform(0,200),'website-backup', 'website-host', 'Dev1'))
##External user is the weird one##
for i in range(800):
flows.append((random.uniform(0,200),'External', 'website-host', 'External'))
for i in range(5000):
flows.append((50+i/1000, 'External', 'website-host', 'External'))
####### Loop through the time windows and add flows/perform actions ############
i = 1
if take_action: engine = m.start_matlab()
for flow in sorted(flows):
if flow[0] >= i: #We have hit the next time window
#print(i)
if i > 10:
self.print_steady_state_with_snapshot(i-1,i)
####Print out the throughput for this snapshot (Netflow case)
times = []
with open('output/test/' + str(i-1) + '-' + str(i) + '_application_graph.csv') as f:
reader = csv.reader(f)
printzero = True
for row in reader:
if row[1] == 'website-host':
num_bytes = float(row[2])
duration = float(row[3])
times.append(num_bytes/duration)
printzero = False
if printzero: times.append(0)
print(statistics.mean(times))
#Decide to take action or not
if take_action: engine.Main_demo(nargout=0,stdout=out,stderr=err)
with open('output.csv') as f:
reader = csv.reader(f)
j = 0
for row in reader:
if not j==0:
if take_action and float(row[1]) > 0:
print('Taking action against', row[0])
self.blocked_users['website-host'].append(row[0])
self.remove_pending_requests(i,row[0],'website-host')
self.remove_pending_requests(i,row[0],'email-host')
j += 1
#if i == 52:
# self.blocked_users['website-host'].append('External')
# self.remove_pending_requests(54,'External','website-host')
# self.remove_pending_requests(54,'External','email-host')
i += 1
self.create_modeled_dataflow_edge(flow[1], flow[2], flow[0], random.gauss(50,5), flow[3])
def featurize_cnn_features(list_of_demonstrations, kinematics, layer, folder, feature_index, net, sr = 3, config = [True, False, False], C = 100):
# For config params [x,y,z] refers to perform PCA, CCA and GRP respectively
data_X_PCA = {}
data_X_CCA = {}
data_X_GRP = {}
big_Z = None
# Initialization
demonstration_size = {}
init_demonstration = list_of_demonstrations[0]
big_Z = utils.sample_matrix(load_cnn_features(init_demonstration, layer, folder, net), sampling_rate = sr)
demonstration_size[init_demonstration] = big_Z.shape[0]
kinematics_sampled = {}
kinematics_sampled[init_demonstration] = utils.sample_matrix(kinematics[init_demonstration], sampling_rate = sr)
dimensions_of_PCA = demonstration_size[init_demonstration]
for demonstration in list_of_demonstrations[1:]:
print "Loading Visual Features for ", demonstration
Z = load_cnn_features(demonstration, layer, folder, net)
Z_sampled = utils.sample_matrix(Z, sampling_rate = sr)
print "Sampled visual", Z.shape, Z_sampled.shape
dimensions_of_PCA += Z_sampled.shape[0]
big_Z = np.concatenate((big_Z, Z_sampled), axis = 0)
demonstration_size[demonstration] = Z_sampled.shape[0]
kinematics_sampled[demonstration] = utils.sample_matrix(kinematics[demonstration], sampling_rate = sr)
print "Sampled kinematics", kinematics_sampled[demonstration].shape
print "PCA # of rows: ", dimensions_of_PCA
PC = min(C, min(demonstration_size.values()))
print "XXXX - PC:", str(PC)
# Quick check to see if kinematics and visual features are aligned
for demonstration in list_of_demonstrations:
print demonstration_size[demonstration], kinematics_sampled[demonstration].shape[0]
assert demonstration_size[demonstration] == kinematics_sampled[demonstration].shape[0]
if config[0]:
big_Z_pca = utils.pca_incremental(big_Z, PC = PC)
if config[2]:
big_Z_grp = utils.grp(big_Z)
start = 0
end = 0
import matlab
import matlab.engine as mateng
eng = mateng.start_matlab()
for demonstration in list_of_demonstrations:
W = kinematics_sampled[demonstration]
size = demonstration_size[demonstration]
end = start + size
# ------------- PCA -------------
if config[0]:
Z = big_Z_pca[start:end]
X = np.concatenate((W, Z), axis = 1)
data_X_PCA[demonstration] = X
# ------------- CCA -------------
if config[1]:
Z = big_Z[start:end]
Z = utils.cca(W, Z)
X = np.concatenate((W, Z), axis = 1)
data_X_CCA[demonstration] = X
# ------------- GRP -------------
if config[2]:
Z = big_Z_grp[start:end]
X = np.concatenate((W, Z), axis = 1)
data_X_GRP[demonstration] = X
start += size
if config[0]:
pickle.dump(data_X_PCA, open(PATH_TO_FEATURES + str(feature_index) + "_PCA.p", "wb"))
if config[1]:
pickle.dump(data_X_CCA, open(PATH_TO_FEATURES + str(feature_index) + "_CCA.p", "wb"))
if config[2]:
pickle.dump(data_X_GRP, open(PATH_TO_FEATURES + str(feature_index) + "_GRP.p", "wb"))
import locale
import json
import tornado.ioloop
import tornado.web
from requestManager import RequestManager
from matlab import engine
ERROR_MESSAGE = "F**k. This wasn't supposed to happen."
eng = engine.start_matlab()
eng.cd('matlab')
class MainHandler(tornado.web.RequestHandler):
def get(self):
data = None
with open("hold.html", "r") as htmlfile:
data = htmlfile.read().replace("\n", "")
data = data if data is not None else ERROR_MESSAGE
self.set_cookie("digitATM", "")
self.write(data)
class DebugHandler(tornado.web.RequestHandler):
def get(self):
data = None
with open("debug.html", "r") as htmlfile:
data = htmlfile.read().replace("\n", "")
data = data if data is not None else ERROR_MESSAGE
self.write(data)
def featurize_cnn_features_no_kinematics(list_of_demonstrations, layer, folder, feature_index, net, sr = 3, config = [True, False, True]):
# For config params [x,y,z] refers to perform PCA, CCA and GRP respectively
data_X_PCA = {}
data_X_GRP = {}
big_Z = None
# Initialization
demonstration_size = {}
init_demonstration = list_of_demonstrations[0]
big_Z = utils.sample_matrix(load_cnn_features(init_demonstration, layer, folder, net), sampling_rate = sr)
demonstration_size[init_demonstration] = big_Z.shape[0]
for demonstration in list_of_demonstrations[1:]:
print "Loading Visual Features for ", demonstration
Z = load_cnn_features(demonstration, layer, folder, net)
Z_sampled = utils.sample_matrix(Z, sampling_rate = sr)
big_Z = np.concatenate((big_Z, Z_sampled), axis = 0)
demonstration_size[demonstration] = Z_sampled.shape[0]
PC = min(100, min(demonstration_size.values()))
if config[0]:
big_Z_pca = utils.pca_incremental(big_Z, PC = PC)
if config[2]:
big_Z_grp = utils.grp(big_Z)
start = 0
end = 0
import matlab
import matlab.engine as mateng
eng = mateng.start_matlab()
for demonstration in list_of_demonstrations:
size = demonstration_size[demonstration]
end = start + size
# ------------- PCA -------------
if config[0]:
Z = big_Z_pca[start:end]
data_X_PCA[demonstration] = Z
# ------------- GRP -------------
if config[2]:
Z = big_Z_grp[start:end]
data_X_GRP[demonstration] = Z
start += size
if config[0]:
pickle.dump(data_X_PCA, open(PATH_TO_FEATURES + str(feature_index) + "_PCA.p", "wb"))
if config[2]:
pickle.dump(data_X_GRP, open(PATH_TO_FEATURES + str(feature_index) + "_GRP.p", "wb"))
# decode
print ("coder: %s" % strCoder)
arrDecoded_bin_1 = decode(eng, arrEncoded_bin_1, n, k, strCoder)
arrDecoded_bin_2 = decode(eng, arrEncoded_bin_2, n, k, strCoder)
print "decoded1(%d): " % len(arrDecoded_bin_1), arrDecoded_bin_1
print "decoded2(%d): " % len(arrDecoded_bin_2), arrDecoded_bin_2
# BER
nCount = 0
for i in xrange(len(arrDecoded_bin_1)):
if arrDecoded_bin_1[i] != arrDecoded_bin_2[i]:
nCount += 1
dBER = nCount * 1.0 / len(arrDecoded_bin_1)
print "BER: ", dBER
if __name__ == "__main__":
eng = mtEngine.start_matlab()
#%%
print "** error correction test **"
n = 7
k = 4
strCoder = "hamming/binary"
arrEncoded = np.random.randint(0, 2, 140)
test_error_correction(eng, arrEncoded, 5, n, k, strCoder)
#%%
eng.quit()
