def show_goals(self):
t1 = time.clock()
personis_vis = cherrypy.session.get('vismgr')
res = personis_vis.show_goals()
t2 = time.clock()
write_log('notice','Show goals visualisation')
print 'show_goal took %0.3fms' % ((t2-t1)*1000.0)
return res
def show_size(self):
t1 = time.clock()
personis_vis = cherrypy.session.get('vismgr')
modeltree = cherrypy.session.get('modeltree')
res = personis_vis.show_size(modeltree)
t2 = time.clock()
print res
if type(res) is ListType:
res = json.dumps(res)
write_log('notice','Show size visualisation')
print 'show_health took %0.3fms' % ((t2-t1)*1000.0)
return res
def get_asx_dailys(self): #download and save all ASX files for the date required
self.get_last_save_date()
while self.last_date < self.date:
tic = time.clock()
self.last_date = self.last_date + timedelta(days=1) #next day from last save
if self.last_date.weekday() < 5: #if Monday to Friday
#print 'Getting data for %s' % str(self.last_date)
for dirs,tails in self.asx_dirs.iteritems():
self.get_asx(dirs,tails) #download the htm files to directory structure
if self.got_htm_file == True:
self.get_asx_table() #returns self.allasxdata, a dictionary of dataframes in the ASX web data
self.update_warehouse(tails)
toc = time.clock()
info_text = 'Data for %s processed in %s seconds' % (self.last_date,str(toc-tic))
logger.info(info_text)
def main():
start_time = datetime.now()
start_time1 = time.clock()
ic("Thread %s is Running..." % current_thread().name)
t = list()
for i in range(5):
t.append(Thread(target=thread_test, name="thread" + str(i + 1)))
t[i].start()
for i in range(5):
t[i].join()
ic("global num: ", num)
ic("Thread %s is Ended..." % current_thread().name)
end_time = datetime.now()
end_time1 = time.clock()
ic(end_time - start_time, end_time1 - start_time1)
def register_app(self, data):
t1 = time.clock()
res = ""
try:
print data
if 'nogoals' not in data:
self.__setgoal = True
else:
self.__setgoal = False
result = cherrypy.session.get('appmgr').register_app(data)
if "Error" not in result:
write_log('notice','Apps register operation successful')
res = result
else:
res = "Error in opration "
write_log('error','Apps register Operation Failed; '+result)
except Exception,e:
print e
write_log('error','Apps regsiter Operation Failed; Error:'+str(e))
res = "Error in opration "
def get_asx_dailys(
self): #download and save all ASX files for the date required
self.get_last_save_date()
while self.last_date < self.date:
tic = time.clock()
self.last_date = self.last_date + timedelta(
days=1) #next day from last save
if self.last_date.weekday() < 5: #if Monday to Friday
#print 'Getting data for %s' % str(self.last_date)
for dirs, tails in self.asx_dirs.iteritems():
self.get_asx(
dirs,
tails) #download the htm files to directory structure
if self.got_htm_file == True:
self.get_asx_table(
) #returns self.allasxdata, a dictionary of dataframes in the ASX web data
self.update_warehouse(tails)
toc = time.clock()
info_text = 'Data for %s processed in %s seconds' % (
self.last_date, str(toc - tic))
logger.info(info_text)
def show_sub_context(self,context=None):
um = cherrypy.session.get('um')
browser_activities = um.get_evidence_new(context = ['Admin'], componentid = 'browseractivity')
t1 = time.clock()
print context
cherrypy.session['cur_context'] = context
udata = context.decode("utf-8")
context = udata.encode("ascii","ignore")
context_list = context.split('/')
modeltree = cherrypy.session.get('modeltree')
genshi_tmpl = LoadGenshiTemplate(cherrypy.session.get('cur_session'), cherrypy.session.get('username'), browser_activities)
try:
#contexts, components = self.personis_um.all_access_model(context_list);
contexts,components = um.get_all_component(context_list);
if type(contexts) is ListType:
t2 = time.clock()
print 'show_subcontext took %0.3fms' % ((t2-t1)*1000.0)
write_log('notice','Subdirectories Clicked: operation successful')
for item in modeltree:
if item.name == context_list[0]:
item.visited = 1
else:
item.visited = 0
return genshi_tmpl.browse_sub_elements(context, "", sorted(contexts), sorted(components,key=operator.attrgetter('Identifier')), self.modeltree)
else:
e = contexts
write_log('error','Subdirectories Clicked: Operation Failed; Error:'+str(e))
return genshi_tmpl.greeting_template(e, "Browse", modeltree)
except Exception,e:
#print e
write_log('error','Sub browser Clicked: Operation Failed; Error:'+str(e))
return genshi_tmpl.greeting_template(e, "Browse", modeltree)
def update_warehouse(self,tails):
'''Ok, this works but is extremely inefficient in terms of the amount of drive space required for the panel object - basically its embarassing. Something is not quite here - probably a user error...'''
if self.last_date == date(2009,7,14): #Create ASX HDF5 data file for the first time
asx_futures = HDFStore(self.asx_path + self.asx_warehouse_file) #open the asx data warehouse!
ota = Panel({self.last_date:self.allasxdata['EA']})
ben = Panel({self.last_date:self.allasxdata['EE']})
asx_futures['OTA_' + tails] = ota
asx_futures['BEN_' + tails] = ben
asx_futures.close()
else:
tic=time.clock()
asx_futures = HDFStore(self.asx_path + self.asx_warehouse_file) #open the asx data warehouse!
ota = asx_futures['OTA_' + tails] #get ota
ben = asx_futures['BEN_' + tails]
asx_futures.close()
os.remove(self.asx_path + self.asx_warehouse_file)
toc=time.clock()
info_text = 'Opening ' + self.asx_warehouse_file + ' took %s seconds' % (str(toc-tic))
logger.info(info_text)
tic=time.clock()
ota = ota.join(Panel({self.last_date:self.allasxdata['EA']}),how='outer') #join the new data to the exisiting panel data - this took a bit of figuring out. Outer is the union of the indexes so when a new row appears for a new quater, Nulls or NaNs full the remainder of the dataframe
ben = ben.join(Panel({self.last_date:self.allasxdata['EE']}),how='outer')
toc=time.clock()
info_text = 'Data join took %s seconds' % (str(toc-tic))
logger.info(info_text)
tic=time.clock()
asx_futures = HDFStore(self.asx_path + self.asx_warehouse_file) #open the asx data warehouse!
asx_futures['OTA_' + tails] = ota #overwrite ota_xxx
asx_futures['BEN_' + tails] = ben
asx_futures.close() #closing ASX warehouse
toc=time.clock()
info_text = 'Resaving ' + self.asx_warehouse_file + ' took %s seconds' % (str(toc-tic))
logger.info(info_text)
to_excel = True
if to_excel == True:
#Spit to XLS ****THIS IS SLOW**** comment out if updating h5 file
try: #to local linux box
ota.to_excel(self.asx_path + 'OTA_' + tails + '.xls') #spit to excel
ben.to_excel(self.asx_path + 'BEN_' + tails + '.xls')
except error_text:
logger.error(error_text)
try: #to P:/ASX_dailys/
ota.to_excel(self.asx_path_P + 'OTA_' + tails + '.xls') #spit to excel
ben.to_excel(self.asx_path_P + 'BEN_' + tails + '.xls')
except error_text:
logger.error(error_text)
def add_new_evidence(self,data=None):
#show_id = request.GET.get('name')
res = ""
t1 = time.clock()
um = cherrypy.session.get('um')
try:
#print data
udata = data.decode("utf-8")
data = udata.encode("ascii","ignore")
cur_context = cherrypy.session.get('cur_context')
if um.add_new_evidence(cur_context, data):
res = """ Successfully added"""
write_log('notice','Add new evidence operation successful')
else:
res = """Failed to add"""
write_log('error','Show evidence list Operation Failed; Error:'+str(res))
except Exception, e:
#print e
res = """Failed to add""" + str(e)
write_log('error','Add new evidence Operation Failed; Error:'+str(e))
def search_image(img):
desc = extract_image(img, conf.ENABLE_ROTATED_SEARCH)
if desc is not False and desc is not None:
con = sqlite_connect(db.SQLITE_DB + '_' + conf.ALGORITHM + '.db')
cur = con.cursor()
cur.execute("SELECT mysql_id, arr FROM descriptor")
data = cur.fetchall()
idx = np.array([])
dataset = None
for i in data:
if dataset is None:
dataset = i[1]
idx = np.linspace(i[0], i[0], len(i[1]))
else:
dataset = np.concatenate((dataset, i[1]))
idx = np.concatenate((idx, np.linspace(i[0], i[0], len(i[1]))))
flann = FLANN()
params = flann.build_index(dataset, algorithm="kdtree", trees=1, target_precision=conf.SEARCH_PRECISION,
log_level="info", cores=4)
if conf.ENABLE_ROTATED_SEARCH is False:
desc = [desc]
arr = []
for d in desc:
timer_start = time.clock()
result, dists = flann.nn_index(d, 5, checks=params["checks"])
print 'time for every search:', time.clock() - timer_start
uniq, idx_count = np.unique(idx[result], return_counts=True)
top_results = np.argwhere(idx_count > len(d) * conf.SEARCH_PRECISION)
top_counts = idx_count[top_results]
top_ids = uniq[top_results]
# print uniq
# print idx_count
# print len(d)
t = np.hstack((top_ids, top_counts)) # getting [id,count] array
if len(t) > 0:
arr.append(t)
flann.delete_index()
if len(arr) > 0:
sub_case = ''
list_ids = []
list_sub = []
for i in arr:
list_sub.append((str(int(i[0][0])), str(int(i[0][1]))))
list_ids.append((str(int(i[0][0]))))
ids = ",".join(list_ids)
# print 'ids', ids
# print 'sub', list_sub
# print 'listIDs', list_ids
for i in list_sub:
sub_case += " WHEN i2.id = " + i[0] + " THEN " + i[1] # adding rank
q = "SELECT i.id, i.src_name, i.target_type, i.target, i.user_id, i.title, u.username, i.pos, i.pinned " \
"FROM image i " \
"LEFT JOIN user u ON u.id = i.user_id " \
"LEFT JOIN (" \
"SELECT i2.id, (CASE " + sub_case + " ELSE 0 END) AS rank " \
"FROM image i2 " \
"WHERE i2.id IN (" + ids + ")) AS sub ON sub.id = i.id " \
"WHERE i.id IN (" + ids + ") " \
"ORDER BY i.pinned DESC, sub.rank DESC LIMIT 1"
result = mysql_fetch(q, {})
return result
return False
def main(argv):
allParams = {}
#"""
res = readObject(allParams,argv)
if(res!="Alright!"):
return {"greetings":"some issue with reading the file. ErrorMsg --> "+str(res)}
constVars['numParts'] = allParams['numParts']
# should remove when we uncomment the above part
"""
allParams['path'] = "../componentExamples/load_files/nr1_fvcorr.domn.193K" #"part_1.log" #"/home/amoghli13/PACE/serverless/serverless-training-set/rodinia_cfd/componentExamples/nr_4_fvcorr.domn.193K"
constVars['numParts'] = 1
allParams['numParts'] = 1 # should come in as a parameter
allParams['bucketName'] = "cfd_data"
allParams['keySuffix'] = "misc" #"cfd_np2_part"
allParams['curPartNum'] = 0
allParams['exchangeNum'] = 0
constVars['numParts'] = allParams['numParts']
allParams["fluxKey"] = str(allParams['keySuffix'])+"_"+str(allParams["curPartNum"])
allParams["fluxFilename"] = str(allParams['keySuffix'])+"_"+str(allParams["curPartNum"])+".log"
#"""
# end of removal.
path = allParams['path']
print ("\t path: %s "%(path))
initParams(allParams)
#print ("\t allParams['ff_flux_contribution_momentum_x']: %s "%(allParams['ff_flux_contribution_momentum_x']))
readFile(allParams['path'],allParams)
# Solving part..
# Create arrays and set initial conditions
varSizes = (allParams['nelr'])*constVars['NVAR']*constVars['numParts'] # defensively increasing by 1 element.
variables = [0.0 for x in range(varSizes)]
#print ("\t allParams['nelr']*constVars['NVAR']: %d "%(allParams['nelr']*constVars['NVAR']))
initialize_variables(allParams['nelr'], variables, allParams['ff_variable']);
old_variables = [0.0 for x in range(varSizes)]
fluxes = [0.0 for x in range(allParams['nelr']*constVars['NVAR'])]
sync_fluxes = [0.0 for x in range(varSizes)]
step_factors = [0.0 for x in range(allParams['nelr'])]
allParams['variables'] = variables
allParams['old_variables'] = old_variables
allParams['fluxes'] = fluxes
allParams['sync_fluxes'] = sync_fluxes
allParams['step_factors'] = step_factors
#print ("\t allParams['variables'][0:20]: %s "%(str(allParams['variables'][0:20])))
begin = time.clock()
# Begin iterations
for i in range(constVars['iterations']):
allParams['old_variables'] = [x for x in (allParams['variables'])]
#copy<float>(old_variables, variables, nelr*NVAR);
# print ("\t Before --> allParams['step_factors'][0:20]: %s "%(str(allParams['step_factors'][0:20])))
# for the first iteration we compute the time step
compute_step_factor(allParams['nelr'], allParams['variables'], allParams['areas'], allParams['step_factors']);
# print ("\t After --> allParams['step_factors'][0:20]: %s "%(str(allParams['step_factors'][0:20])))
#print ("\t Before --> allParams['fluxes'][0:20]: %s "%(str(allParams['fluxes'][0:20])))
for j in range(constVars['RK']):
compute_flux(allParams['nelr'],allParams['elements_surrounding_elements'],allParams['normals'],allParams['variables']
,allParams['fluxes'],allParams['ff_variable'],allParams['ff_flux_contribution_momentum_x'],allParams['ff_flux_contribution_momentum_y']
,allParams['ff_flux_contribution_momentum_z'],allParams['ff_flux_contribution_density_energy'])
#(nelr, elements_surrounding_elements, normals, variables, fluxes, ff_variable, ff_flux_contribution_momentum_x, ff_flux_contribution_momentum_y,ff_flux_contribution_momentum_z, ff_flux_contribution_density_energy);
# should synchronize
synchronizeFluxes(allParams) # push local flux, wait for remote fluxes
#print ("\t Hows it going?")
#time_step(j, allParams['nelr'], allParams['old_variables'], allParams['variables'], allParams['step_factors'], allParams['fluxes']);
time_step(j, allParams['nelr'], allParams['old_variables'], allParams['variables'], allParams['step_factors'], allParams['sync_fluxes']);
#print ("\t After --> allParams['fluxes'][0:20]: %s "%(str(allParams['fluxes'][0:20])))
end = time.clock();
diff = end-begin
#if(i%10==0): print ("\t i: %d diff: %.6lf "%(i,diff))
break;
print ("\t End: %s Begin: %s Time: %s "%(end,begin,diff))
resultStr = "Took %.4lf time "%(diff)
if(allParams["curPartNum"]==0):
deleteVarFiles(allParams)
return {"greetings" : resultStr}
cur_context = cherrypy.session.get('cur_context')
if um.add_new_evidence(cur_context, data):
res = """ Successfully added"""
write_log('notice','Add new evidence operation successful')
else:
res = """Failed to add"""
write_log('error','Show evidence list Operation Failed; Error:'+str(res))
except Exception, e:
#print e
res = """Failed to add""" + str(e)
write_log('error','Add new evidence Operation Failed; Error:'+str(e))
t2 = time.clock()
print 'add_new_evidence took %0.3fms' % ((t2-t1)*1000.0)
return res
add_new_evidence.exposed = True
def add_new_element(self,data):
data = data.split('_')
cur_context = cherrypy.session.get('cur_context')
context = cur_context.split('/')
if cur_context == "None" or data[3] == "Home":
context = []
print context
um = cherrypy.session.get('um')
if data[0] == 'component':
try:
um.make_new_component(data[1],'attribute', 'string',None,data[2],context)
def wrapper(*arg):
t1 = time.clock()
res = func(*arg)
t2 = time.clock()
print '%s took %0.3fms' % (func.func_name, (t2-t1)*1000.0)
return res
def users_json(self, rows=None, sidx=None, _search=None, searchField=None,
searchOper=None, searchString=None, page=None, sord=None, nd=None): # 1 line
"""Returns all users from test_data in a json format that's compatible with jqGrid.""" # 2 lines
t1 = time.clock()
header = ["value", "flags", "source", "evidence_type", "creation_time", "time", "useby", "owner", "comment"] # 3 lines
reslist = []
genshi_tmpl = LoadGenshiTemplate(cherrypy.session.get('cur_session'), cherrypy.session.get('username'))
cur_component = cherrypy.session.get('cur_component')
cur_context = cherrypy.session.get('cur_context')
if cur_component != 'None':
#print "getting new"
context = cur_context.split()
um = cherrypy.session.get('um')
reslist = um.get_evidence_new(context, cur_component)
cherrypy.session['cur_component'] = 'None'
else:
#print "getting default"
cherrypy.session['cur_component'] = 'firstname'
reslist = um.get_evidence_new()
#users_list = test_data_to_list(test_data) # 4 lines
evdlist = []
i = 0
#{'comment': None, 'evidence_type': 'explicit', 'creation_time': 1322914468.889158, 'value': 'Bob',
#'source': 'Jane', 'flags': [], 'time': None, 'owner': 'Jane', 'objectType': 'Evidence', 'useby': None}
myEvd = []
if type(reslist) is ListType:
for res in reslist:
print "Inside user_json "
myEvd = [0]*10
myEvd[0] = i
for key, value in res.__dict__.items():
#print "%s:%s"%(key, value)
for item in header:
if item == key:
#print "key: %s %s--"%(item,key)
if key == 'creation_time' or key == 'time' or key == 'useby':
if value:
import datetime
value = datetime.datetime.fromtimestamp(int(value)).strftime('%d/%m/%Y %H:%M:%S')
elif key == 'flags':
if value:
value = ''.join(value)
else:
value="None"
__index = header.index(item)
#print "%s in %d" %(value,__index+1)
myEvd[__index+1]=value
evdlist.append(myEvd)
i = i+1
#print "Evidence: %d" %i
#for val in myEvd:
# print val
import my_jqGrid
result_page = my_jqGrid.jqgrid_json(self, evdlist, header, rows=rows, sidx=sidx, _search=_search,
searchField=searchField, searchOper=searchOper, searchString=searchString, page=page, sord=sord)
t2 = time.clock()
print 'user-json took %0.3fms' % ((t2-t1)*1000.0)
write_log('notice','Show evidence list operation successful')
return result_page
else:
#print reslist
e = reslist
write_log('error','Show evidence list Operation Failed; Error:'+str(e))
modeltree = cherrypy.session.get('modeltree')
return genshi_tmpl.greeting_template(e, "Evidencelist upload", modeltree)
def update_warehouse(self, tails):
'''Ok, this works but is extremely inefficient in terms of the amount of drive space required for the panel object - basically its embarassing. Something is not quite here - probably a user error...'''
if self.last_date == date(
2009, 7, 14): #Create ASX HDF5 data file for the first time
asx_futures = HDFStore(
self.asx_path +
self.asx_warehouse_file) #open the asx data warehouse!
ota = Panel({self.last_date: self.allasxdata['EA']})
ben = Panel({self.last_date: self.allasxdata['EE']})
asx_futures['OTA_' + tails] = ota
asx_futures['BEN_' + tails] = ben
asx_futures.close()
else:
tic = time.clock()
asx_futures = HDFStore(
self.asx_path +
self.asx_warehouse_file) #open the asx data warehouse!
ota = asx_futures['OTA_' + tails] #get ota
ben = asx_futures['BEN_' + tails]
asx_futures.close()
os.remove(self.asx_path + self.asx_warehouse_file)
toc = time.clock()
info_text = 'Opening ' + self.asx_warehouse_file + ' took %s seconds' % (
str(toc - tic))
logger.info(info_text)
tic = time.clock()
ota = ota.join(
Panel({self.last_date: self.allasxdata['EA']}), how='outer'
) #join the new data to the exisiting panel data - this took a bit of figuring out. Outer is the union of the indexes so when a new row appears for a new quater, Nulls or NaNs full the remainder of the dataframe
ben = ben.join(Panel({self.last_date: self.allasxdata['EE']}),
how='outer')
toc = time.clock()
info_text = 'Data join took %s seconds' % (str(toc - tic))
logger.info(info_text)
tic = time.clock()
asx_futures = HDFStore(
self.asx_path +
self.asx_warehouse_file) #open the asx data warehouse!
asx_futures['OTA_' + tails] = ota #overwrite ota_xxx
asx_futures['BEN_' + tails] = ben
asx_futures.close() #closing ASX warehouse
toc = time.clock()
info_text = 'Resaving ' + self.asx_warehouse_file + ' took %s seconds' % (
str(toc - tic))
logger.info(info_text)
to_excel = True
if to_excel == True:
#Spit to XLS ****THIS IS SLOW**** comment out if updating h5 file
try: #to local linux box
ota.to_excel(self.asx_path + 'OTA_' + tails +
'.xls') #spit to excel
ben.to_excel(self.asx_path + 'BEN_' + tails + '.xls')
except error_text:
logger.error(error_text)
try: #to P:/ASX_dailys/
ota.to_excel(self.asx_path_P + 'OTA_' + tails +
'.xls') #spit to excel
ben.to_excel(self.asx_path_P + 'BEN_' + tails + '.xls')
except error_text:
logger.error(error_text)
def __init__(self, name):
self.time_admitted = time.clock()
self.name = name
def get_lmp(self, latest=False,
start_at=False, end_at=False, market='hourly', grp_type='ALL',node='ALL',csv=False, **kwargs):
# Construct_oasis_payload expects market option to be one of 'hourly', 'fivemin', 'tenmin', 'na', 'dam'
# if csv = False, pulls xml files, parses SLOWLY, and returned data is
# a list of dicts, each of which has a main index of the timestamp
# if csv=True, pulls csv files, parses more quickly, and returns Pandas
# Panel data structure
# Expected parameters:
# node: CAISO node ID. Can be set to individual node or "ALL". "ALL" will override grp_type
# grp_type: either "ALL_APNodes" or "ALL" - This will trigger day-by-day iteration
# NOTE: This needs to be turned off for processing individual nodes. This will override node types
# market= "DAM", "HASP", "RTM"
# start_at and end_at can be a variety of parsable input types, with or without time codes
# i.e. '2013-10-12T11:45:30' or '2011-10-12'
# Relevant XML Calls:
# PRC_LMP - for market_run_id='DAM'
# PRC_HASP_LMP for market_run_id='HASP'
# PRC_INTVL_LMP for market_run_id='RTM'
# PRC_RTPD_LMP No longer valid?
# Max call interval:
# In the HASP and RTM markets, requesting more than the max interval length may result in the wrong data being returned.
# Individual nodes: <31 days
# Calling "ALL" or "ALL_APNODES":
# DAM: 1 day, returns 4 files from expanded zip. Each has 20-line header
# HASP: 1 hour, returns one file with all components (LMP, MCC, MCE, MCL)
# RTM: 1 hour, returns one file with all components (LMP, MCC, MCE, MCL)
#PRC_LMP
# if grp_type=="ALL" or "ALL_APNODES", we are processing full node sets:
# remove 'node' from the payload
# can only process one time step at a time,
# Time step for DAM = 1 day; time step otherwise = 1 hr
#
# if node is not "ALL", we are dealing with a specific node:
# remove grp_type from payload
# Check to make sure that the date is less than 31 days or cut into pieces
# set args
self.handle_options(data='load', latest=latest,
start_at=start_at, end_at=end_at, market=market, grp_type=grp_type,node=node, **kwargs)
requestSpan = self.options['end_at'] - self.options['start_at'] # This is the duration spanned by our request
requestStart = self.options['start_at'] #This should be a datetime object
requestEnd = self.options['end_at'] # This should be a datetime object
print 'Request span is:',requestSpan
# ensure market and freq are set # What is this for?
if 'market' not in self.options:
if self.options['forecast']:
self.options['market'] = self.MARKET_CHOICES.dam
else:
self.options['market'] = self.MARKET_CHOICES.fivemin
"""if 'freq' not in self.options: # What is the frequency used for?
if self.options['forecast']:
self.options['freq'] = self.FREQUENCY_CHOICES.hourly
else:
self.options['freq'] = self.FREQUENCY_CHOICES.fivemin
"""
# Clean up conflicting commands
# Check this: this may currently be buggy when requesting grp_type=ALL_APNODES but excluding 'node' in the call
if self.options['node']=='ALL' and self.options['grp_type']!='ALL':
del self.options['grp_type'] # Node typically overrides the grp_type call
# Decision fork: either we are handing "all" nodes or we are handling an individual node
if self.options['grp_type']=='ALL' or self.options['grp_type']=='ALL_APNodes':
# If we are processing full node sets, need to iterate across the appropriate time blocks
del self.options['node'] # Get rid of node commands to ensure we aren't sending mixed signals. This will override the node option.
if market=='DAHR':
print ('The DAM LMP call is not yet implemented... you should go do that.')
else: # We are not in DAM, but in HASP or RTM
# If we are requesting all nodes in the Hour-ahead market or real-time markets, we can request at most one hour at a time
if market=='RTHR':
# This is a request for the Hour-Ahead Scheduling Process (HASP)
oasis_API_call= 'PRC_HASP_LMP'
else: #if ':market=='RTM
# Assume that this is a request for the real-time market
oasis_API_call= 'PRC_INTVL_LMP'
parsed_data = [] # Placeholder
currentStartAt = requestStart # Initialize loop conditions
currentEndAt = currentStartAt
# The contents of the following if statement can probably be refactored
if requestSpan.total_seconds()>3600:
timeStep = timedelta(hours=1) # Increment by one hour each iteration
currentEndAt = currentEndAt + timeStep # Priming the pump
# The following loop can probably be refactored significantly
while currentEndAt < requestEnd:
# Set up payload, fetch data, and parse data
self.options['start_at']=currentStartAt
self.options['end_at']=currentEndAt
payload = self.construct_oasis_payload(oasis_API_call,csv=csv)
print 'Requesting data for time starting at ', (currentStartAt).strftime(self.oasis_request_time_format)
startRequest = time.clock()
oasis_data = self.fetch_oasis(payload=payload)
endRequest = time.clock()
print 'Imported data in ',endRequest-startRequest,' s'
parsed_data.append(self.parse_lmp(oasis_data,csv=csv))
print 'Parsed Data in ', time.clock()-endRequest,' s'
currentStartAt = currentEndAt
currentEndAt = currentEndAt + timeStep
# Previous 'if' block was to get us within one time step of the finish. This will get us the rest of the way.
#Clean up final iteration to get to the end time
print 'Exited the loop'
self.options['start_at']=currentStartAt
self.options['end_at']=requestEnd
payload = self.construct_oasis_payload(oasis_API_call,csv=csv)
print 'Requesting data for time starting at ', (currentStartAt).strftime(self.oasis_request_time_format)
oasis_data = self.fetch_oasis(payload=payload)
parsed_data.append(self.parse_lmp(oasis_data,csv))
result = parsed_data
#merge dataframes if you have been pulling csv's
if csv:
for i in range(len(parsed_data)):
if i == 0: result = parsed_data[0]
else:
result = result.append(parsed_data[i])
result = result.unstack()
result.columns = result.columns.droplevel()
else:
# If we aren't handling full node sets, we are handling individual nodes and can request up to 31 days of data at a time
print('The single-node calls are not yet implemented... you should go do that.')
# Return either just the most recent datapoint, or return all the parsed data
# It seems like this could be moved to a separate function
# Commenting out for now because it looks like it needs a specific data structure, i.e. a dict with a 'timestamp' key
"""
if self.options['latest']:
# select latest
latest_dp = None
latest_ts = self.utcify('1900-01-01 12:00')
now = self.utcify(datetime.utcnow(), tz_name='utc')
for dp in parsed_data:
if dp['timestamp'] < now and dp['timestamp'] > latest_ts:
latest_dp = dp
latest_ts = dp['timestamp']
# return latest
if latest_dp:
return [latest_dp]
else:
return []
else:
# return all data
return parsed_data
"""
return result
cv2.namedWindow("output", cv2.WINDOW_NORMAL)
imS = cv2.resize(predicted_frame, (960, 540))
cv2.imshow("output", imS)
key = cv2.waitKey(3) & 0xFF
if label_pair[1] < 45 and label_pair[0] > 0 and locked is True:
f = open('Log.txt', 'a')
f.write("\n At ")
f.write(str(datetime.now()))
f.write(", ")
f.write(subjects[label_pair[0]])
f.write(" is entering the room with a variance of " + str(label_pair[1]))
f.close()
GPIO.output(Motor1E,GPIO.HIGH)
waitTime = time.clock()+10
while time.clock() < waitTime:
pass
GPIO.output(Motor1E, GPIO.LOW)
locked = False
input_state = GPIO.input(18)
if input_state == False:
f = open('Log.txt', 'a')
if locked is True:
GPIO.output(Motor1E,GPIO.HIGH)
waitTime = time.clock()+10
while time.clock() < waitTime:
pass
GPIO.output(Motor1E, GPIO.LOW)
locked = False
def TickCount() -> float:
return time.clock()
>>> import sys
>>> print(sys.version)
3.8.5 (tags/v3.8.5:580fbb0, Jul 20 2020, 15:43:08) [MSC v.1926 32 bit (Intel)]
>>>
>>> print(time.perf_counter(), time.localtime(time.perf_counter()))
89.4915672 time.struct_time(tm_year=1970, tm_mon=1, tm_mday=1, tm_hour=1, tm_min=1, tm_sec=29, tm_wday=3, tm_yday=1, tm_isdst=0)
>>>
>>> import time
>>> time.time()
1614326427.3598132
>>> time.localtime(time.time())
time.struct_time(tm_year=2021, tm_mon=2, tm_mday=26, tm_hour=9, tm_min=0, tm_sec=57, tm_wday=4, tm_yday=57, tm_isdst=0)
>>> time.asctime(time.localtime(time.time()))
'Fri Feb 26 09:01:38 2021'
>>> time.localtime(time.clock())
Traceback (most recent call last):
File "<pyshell#4>", line 1, in <module>
time.localtime(time.clock())
AttributeError: module 'time' has no attribute 'clock'
>>> time.localtime(time.clock()))
SyntaxError: unmatched ')'
>>> import calendar
>>> calendar.month(2021, 7)
' July 2021\nMo Tu We Th Fr Sa Su\n 1 2 3 4\n 5 6 7 8 9 10 11\n12 13 14 15 16 17 18\n19 20 21 22 23 24 25\n26 27 28 29 30 31\n'
>>> calendar.month(2021, 7, w=1, l=2)
' July 2021\n\nMo Tu We Th Fr Sa Su\n\n 1 2 3 4\n\n 5 6 7 8 9 10 11\n\n12 13 14 15 16 17 18\n\n19 20 21 22 23 24 25\n\n26 27 28 29 30 31\n\n'
>>> calendar.setfirstweekday(6)
>>> calendar.month(2021, 7)
' July 2021\nSu Mo Tu We Th Fr Sa\n 1 2 3\n 4 5 6 7 8 9 10\n11 12 13 14 15 16 17\n18 19 20 21 22 23 24\n25 26 27 28 29 30 31\n'
