def main(self):
self.idf = {}
self.paras = re.split('\s{4,}', self.text)
N = len(self.paras)
ni = {}
tf = []
self.qv = processData(self).queryVector(self.question)
for para in self.paras:
pd = processData(self)
temp = pd.findTfVector(para)
tf.append(temp)
for word in temp.keys():
if not word in ni:
ni[word] = 0
ni[word] += 1
for word in ni:
self.idf[word] = math.log((N + 1) / ni[word])
sim = []
for tfForDoc in tf:
sim.append(processData(self).findSim(self.qv, tfForDoc, self.idf))
self.sim = sorted(enumerate(sim),
key=operator.itemgetter(1),
reverse=True)
self.question_type = Question().classifyQues(self.question)
self.answer = Answer().getAnswer(self)
return self.answer
def main(args):
'Tests accuracy of logistic regression in predicting if candies are chocolate'
alpha, regParam, iterations = _getParams(args)
#Regression on full data set
fullDesign, fullLabels = processData('data/candy-data.csv')
fullTheta, fullAccuracy = _runLogRegression(fullDesign, fullLabels, alpha,
regParam, iterations)
#Regression on first half of data set
halfDesign, halfLabels = processData('data/firstHalf-candy-data.csv')
halfTheta, halfAccuracy = _runLogRegression(halfDesign, halfLabels, alpha,
regParam, iterations)
#Test accuracy of params trained on first half on second half
secondHalfDesign, secondHalfLabels = processData(
'data/secondHalf-candy-data.csv')
secondHalfAccuracy = accuracy(logHypo(halfTheta, secondHalfDesign),
secondHalfLabels)
_displayResults(fullAccuracy, halfAccuracy, secondHalfAccuracy)
def create(self, pvoutput):
'''Create a goodwe instance.'''
goodwe = None
process = None
if self.config.get_input_source() == 'USB':
import goodweUsb
import processNone
goodwe = goodweUsb.goodweUsb(self.config.get_gpio_usb_pin(),
self.config.get_usb_sample_interval(),
0x0084)
process = processNone.processNone(pvoutput)
elif self.config.get_input_source() == 'RS485':
import goodweRS485
import processNone
goodwe = goodweRS485.goodweRS485('',
self.config.get_serial_device(),
self.config.get_serial_baudrate())
process = processNone.processNone(pvoutput)
elif self.config.get_input_source() == 'WIFI':
import goodweWIFI
import processNone
goodwe = goodweWIFI.goodweWIFI(self.config.get_wifi_address(), '',
self.config.get_serial_baudrate())
process = processNone.processNone(pvoutput)
else: # self.config.get_input_source() == 'URL':
import readGoodwe
goodwe = readGoodwe.readGoodwe(self.config.get_goodwe_url(),
self.config.get_goodwe_loginUrl(),
self.config.get_goodwe_system_id())
# Request password for Goodwe-power.com
password = self.config.get_goodwe_passwd()
if password == '':
passwd_text = 'Supply password for ' + str(
self.config.get_goodwe_loginUrl()) + ': '
password = getpass.getpass(passwd_text)
goodwe.login(self.config.get_goodwe_user_id(), password)
if self.config.get_spline_fit():
import processData2
process = processData2.processData2(pvoutput)
else:
import processData
process = processData.processData(pvoutput)
return goodwe, process
def create( self, pvoutput):
'''Create a goodwe instance.'''
goodwe = None
process = None
if self.config.get_input_source() == 'USB':
import goodweUsb
import processNone
goodwe = goodweUsb.goodweUsb( self.config.get_gpio_usb_pin(),
self.config.get_usb_sample_interval(),
0x0084)
process = processNone.processNone( pvoutput)
elif self.config.get_input_source() == 'RS485':
import goodweRS485
import processNone
goodwe = goodweRS485.goodweRS485( '',
self.config.get_serial_device(),
self.config.get_serial_baudrate())
process = processNone.processNone( pvoutput)
elif self.config.get_input_source() == 'WIFI':
import goodweWIFI
import processNone
goodwe = goodweWIFI.goodweWIFI( self.config.get_wifi_address(),
'',
self.config.get_serial_baudrate())
process = processNone.processNone( pvoutput)
else: # self.config.get_input_source() == 'URL':
import readGoodwe
goodwe = readGoodwe.readGoodwe( self.config.get_goodwe_url(),
self.config.get_goodwe_loginUrl(),
self.config.get_goodwe_system_id())
# Request password for Goodwe-power.com
password = self.config.get_goodwe_passwd()
if password == '':
passwd_text = 'Supply password for ' + str(self.config.get_goodwe_loginUrl()) + ': '
password = getpass.getpass( passwd_text)
goodwe.login( self.config.get_goodwe_user_id(), password)
if self.config.get_spline_fit():
import processData2
process = processData2.processData2( pvoutput)
else:
import processData
process = processData.processData( pvoutput)
return goodwe, process
def execute_filter_calcs(progress_callback=[],
dataset=[],
mainDirectory=[],
directory=[],
continuing=False,
filterMethod=mF.wienerFilter):
defaultTemplate = np.loadtxt(
'template200_15us.txt') #change default template here
result = pD.processData(directory,
defaultTemplate,
GUI=True,
progress_callback=progress_callback,
dataset=dataset,
mainDirectory=mainDirectory,
continuing=continuing,
filterMethod=filterMethod)
return result
# Read Metadata.
from processData import processData
from writeData import getKey
if __name__ == "__main__":
# Input the audio file not with extension
file = input("Enter the audio file ---->" )
file = file + ".mp3" # Adding extenstion to audio file.
print("The file to be processed is ---> " + str(file)) # Printing the file name.
processData(file) # Processing the audio file.
import tensorflow as tf
from tensorflow.contrib import layers
from tensorflow.contrib.learn import ModeKeys
from processData import processData, output_max_len, vocab_size, index2word
import numpy as np
tf.logging.set_verbosity(tf.logging.INFO)
GO_TOKEN = 0
END_TOKEN = 1
UNK_TOKEN = 2
embed_dim = 50
num_units = 256
batch_size = 20
trainData, testData = processData('input.dat', 'output.dat')
in_data, la_data, out_data = trainData
in_data_t, la_data_t, out_data_t = testData
# `(features, labels, mode, params) -> (predictions, loss, train_op)`
def seq2seq(features, labels, mode, params):
in_data = features['input']
out_data = features['output']
# (batch_size, seq_length, embed_dim)
in_embed = layers.embed_sequence(in_data,
vocab_size=vocab_size,
embed_dim=embed_dim,
scope='embed')
out_embed = layers.embed_sequence(out_data,
def test_processData(self):
'Test dimensions of output from process data'
designM, labels = processData('../data/small-candy.csv')
self.assertEqual(designM.shape, (15, 12))
self.assertEqual(labels.shape, (15, 1))
prices = []
for i in range(len(th)):
prices.append(float((th[len(th) - i - 1]["5. adjusted close"])))
return prices
def getChange(self, priceList):
change = []
change.append(0)
for i in range(1, len(priceList)):
change.append((priceList[i] - priceList[i - 1]) / priceList[i - 1])
return change
stocks = stockapi()
tickerList = stocks.tickerList
process = processData(39, 1)
trainingData_X = []
trainingData_Y = []
testingData_X = []
testingData_Y = []
for tiker in tickerList:
time.sleep(1)
th = stocks.getTickerHistory(tiker)
if (th):
prices = stocks.getClosingPrice(th)
change = stocks.getChange(prices)
newData = process.cut(prices)
trD, teD = process.splitValidation(newData)
train_x, train_y = process.split(trD)
test_x, test_y = process.split(teD)
trainingData_X = (trainingData_X + train_x)
onlineUser[sid] = cInfo
print(str(onlineUser))
sid += 1
else: # 接收通讯数据
recvData = netstream.read(r)
# print 'Read data from ' + str(r.getpeername()) + '\tdata is: ' + str(recvData)
# 客户端socket关闭
if recvData == netstream.CLOSED or recvData == netstream.TIMEOUT:
if r.getpeername() not in disconnected_list:
print str(r.getpeername()) + 'disconnected'
disconnected_list.append(
r.getpeername()) #拓展断开连接的客户端列表
else: # 根据收到的request发送response
#公告
netstream.send(onlineUser[recvData['sid']]['connection'],
processData.processData(recvData))
break
'''
if 'notice' in recvData:
# 获取通讯中某个属性的值
number = recvData['sid']
print 'receive notice request from user id:', number
# 发送数据
sendData = {"notice_content": "This is a notice from server. Good luck!"}
netstream.send(onlineUser[number]['connection'], sendData)
'''
except Exception:
traceback.print_exc()
print 'Error: socket 链接异常'
def test_1( self):
gw1 = goodweData.goodweData('<tr class=\"DG_Item\"><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr>')
gw1.m_inverter_sn = 1
gw1.m_vpv1 = 1.0
gw1.m_vpv2 = 1.0
gw1.m_ipv1 = 1.0
gw1.m_ipv2 = 1.0
gw1.m_vac1 = 1.0
gw1.m_vac2 = 1.0
gw1.m_vac3 = 1.0
gw1.m_iac1 = 1.0
gw1.m_iac2 = 1.0
gw1.m_iac3 = 1.0
gw1.m_fac1 = 1.0
gw1.m_fac2 = 1.0
gw1.m_fac3 = 1.0
gw1.m_pgrid= 1.0
gw1.m_eday = 1.0
gw1.m_etotal= 1.0
gw1.m_htotal= 1.0
gw1.m_temperature= 1.0
gw2 = copy.deepcopy(gw1)
gw2.m_inverter_sn = 2
gw3 = copy.deepcopy(gw1)
gw3.m_inverter_sn = 3
gw4 = copy.deepcopy(gw1)
gw4.m_inverter_sn = 4
gw5 = copy.deepcopy(gw1)
gw5.m_inverter_sn = 5
gw6 = copy.deepcopy(gw1)
gw6.m_inverter_sn = 6
gw10 = copy.deepcopy(gw1)
gw10.m_inverter_sn = 10
gw10.m_vpv1 = 10.0
gw10.m_vpv2 = 10.0
gw10.m_ipv1 = 10.0
gw10.m_ipv2 = 10.0
gw10.m_vac1 = 10.0
gw10.m_vac2 = 10.0
gw10.m_vac3 = 10.0
gw10.m_iac1 = 10.0
gw10.m_iac2 = 10.0
gw10.m_iac3 = 10.0
gw10.m_fac1 = 10.0
gw10.m_fac2 = 10.0
gw10.m_fac3 = 10.0
gw10.m_pgrid= 10.0
gw10.m_eday = 10.0
gw10.m_etotal= 10.0
gw10.m_htotal= 10.0
gw10.m_temperature= 10.0
gw11 = copy.deepcopy(gw10)
gw11.m_inverter_sn = 11
gw12 = copy.deepcopy(gw10)
gw12.m_inverter_sn = 12
process = processData.processData(None, 4*60)
process.reset()
print "State:" + process.state_to_string()
process.processSample( gw1)
print "State:" + process.state_to_string()
process.processSample( gw2)
print "State:" + process.state_to_string()
process.processSample( gw3)
print "State:" + process.state_to_string()
process.processSample( gw4)
print "State:" + process.state_to_string()
process.processSample( gw10)
print "State:" + process.state_to_string()
process.processSample( gw11)
print "State:" + process.state_to_string()
process.processSample( gw5)
print "State:" + process.state_to_string()
process.processSample( gw6)
print "State:" + process.state_to_string()
process.processSample( gw12)
print "State:" + process.state_to_string()
process.reset()
print "State:" + process.state_to_string()
cost = calculate_loss(X, y, model)
costList.append(cost)
print("Loss after iteration %i: %f" % (i, cost))
return model
# Display plots inline and change default figure size
'''
np.random.seed(0)
X, y = sklearn.datasets.make_moons(200, noise=0.20)
print(X.shape)
print(y)
'''
X = pd.processData('adult.csv')
y = np.matrix(np.zeros((X.shape[0], 2), dtype='int'))
y = np.array(X[:, -1], dtype='int')
X = X[:, 0:X.shape[1] - 1]
X = norm.normalizeStd(X)
#Define training set and cross validation set
n = X.shape[0]
X_training = X[0:0.9 * n, :]
y_training = y[0:0.9 * n]
y_cross = y[0.9 * n:n]
X_cross = X[0.9 * n:n, :]
HAM = 'ham'
DATAFILE_PATH = './dataSet/SMSSpamCollection.txt' # Relative path to file
POS_SENTIMENT_PATH = './rt-polaritydata/rt-polarity.pos' # Relative path to file
NEG_SENTIMENT_PATH = './rt-polaritydata/rt-polarity.neg' # Relative path to file
SENTIMENT_PATH = './rt-polaritydata/rt-polarity' # Relative path to file
################
# Fetch the data
################
print("=======================")
print("Reading in SMS data...")
print("=======================")
start = time.time()
dataz = processData(DATAFILE_PATH)
end = time.time()
duration = end - start
# Some error checking
numTexts = len(dataz['text'].values)
numLabels = len(dataz['label'].values)
if numTexts != numLabels:
print("unknown error: text/label mismatch")
exit(1)
print("Read in %d SMS messages") % (numTexts)
print("Data read took %.2fsec\n") % (duration)
print "Hold on, we gotta make a sentiment analyzer first"
process.processSample(gw)
else:
# Wait for the inverter to come online
print "Inverter is not online: " + gw.to_string()
interval = 20.0 * 60
csv.reset()
process.reset()
# Wait for the next sample
print "sleep " + str(interval) + " seconds before next sample"
time.sleep(interval)
if __name__ == "__main__":
# Main entry point for the Goodwe to PVoutput logging script. Creates the
# objects needed and sets the URL and system IDs. These are defined at the
# start of this file
#
# These URLs should be okay for Goodwe-power and PVoutput.org (and yes, there
# is a spelling error in the goodwe URL).
goodwe_url = 'http://goodwe-power.com/PowerStationPlatform/PowerStationReport/InventerDetail'
pvoutput_url = 'http://pvoutput.org/service/r2/addstatus.jsp'
goodwe = readGoodwe.readGoodwe(goodwe_url, sid)
pvoutput = pvoutput.pvoutput(pvoutput_url, sys_id, api_key)
csv = csvoutput.csvoutput(csv_dir, 'Goodwe_PV_data')
process = processData.processData(pvoutput)
# Perform main loop
mainloop(goodwe, pvoutput, csv)
def processDataTF(cfg, monitor=False, reprocess=False):
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
if size < MIN_SIZE:
logging.error('need at least %d processes' % MIN_SIZE)
return
if monitor:
mname = '%s_memmon.%06d' % (cfg['grid']['output'], rank)
else:
mname = None
monitor = MonitorProcess(out=mname)
status = MPI.Status()
if rank == 0:
# MASTER
lname = "MASTER"
logging.info("%s:started" % lname)
busy = numpy.ones(size, dtype=int)
tiles = DHDTTiles(cfg, reprocess=reprocess)
tilesIterator = iter(tiles)
while numpy.any(busy > 0):
data = comm.recv(status=status)
source = status.Get_source()
if data == "get":
try:
t = next(tilesIterator)
logging.info("%s:shedule tile %d on %d" %
(lname, t, source))
except StopIteration:
t = None
busy[0] = 0
busy[source] = 0
logging.info("%s:shedule %d to shutdown" % (lname, source))
except:
logging.error(sys.exc_info()[0])
comm.Abort()
comm.send(t, dest=source)
else:
tiles.updateTile(data)
logging.info("%s:finished tile %d" % (lname, data))
else:
# SLAVE
lname = "SLAVE %d" % rank
logging.info("%s:started" % lname)
while True:
logging.info("%s:waiting for task" % lname)
comm.send("get", dest=0)
tile = comm.recv(source=0)
if tile is None:
# done processing
logging.info("%s:no more tiles" % lname)
break
# do stuff
logging.info("%s:computing tile %d" % (lname, tile))
try:
processData(cfg, tile, reprocess=reprocess)
# report done
comm.send(tile, dest=0)
except:
logging.error('processing tile %d %s' %
(tile, sys.exc_info()[0]))
comm.Barrier()
peak = monitor.peak()
logging.info('MPI: %d cpu: %.2f%%' % (rank, peak['cpu']))
logging.info('MPI: %d rss: %.2fGB' % (rank, peak['rss'] /
(1024. * 1024. * 1024.)))
logging.info('MPI: %d vms: %.2fGB' % (rank, peak['vms'] /
(1024. * 1024. * 1024.)))
logging.info(lname + ":finished")
# Local File
fileName = './streaming_data/tweetData.json'
logFile = './logfile.txt'
# MongoDB connection
client = MongoClient()
db = client.tweet_db
collection = db.tweets
# Auto-iterate through all files in the root folder.
query = {'q': "'0B7ziEhBHYh1bc3hEREo1eS1fMWs' in parents and trashed=false"}
# query = {'q': "'root' in parents and trashed=false"}
file_list = drive.ListFile(query).GetList()
total = len(file_list)
i = 0
with open(logFile, 'w') as op:
for f in file_list:
i += 1
print('File %d of %d' % (i, total))
print('Title: %s' % (f['title']))
op.write('\r\nTitle: ' + f['title'])
f.GetContentFile(fileName)
processedData = processData(fileName)
processedData.process()
result = collection.insert_many(processedData.getTweets())
print('Tweets %d' % (len(result.inserted_ids)))
op.write('\r\nTweets' + str(len(result.inserted_ids)))
print 'Completed All'
# Misc Parameters
tf.flags.DEFINE_boolean("allow_soft_placement", True,
"Allow device soft device placement")
tf.flags.DEFINE_boolean("log_device_placement", False,
"Log placement of ops on devices")
FLAGS = tf.flags.FLAGS
FLAGS._parse_flags()
print("\nParameters:")
for attr, value in sorted(FLAGS.__flags.items()):
print("{}={}".format(attr.upper(), value))
print("")
# x_evaluate = [u"这游戏玩的不爽",u"这皮肤太好看了",u"这英雄特别叼",u"这英雄伤害不高",u"嗯嗯",u"这样啊"]
datapreprocess = processData.processData(trainPath, sentence_length)
testData = pd.read_csv(testPath, sep="\t", encoding="utf-8")
x_evaluate = list(testData["text"])
x_test = datapreprocess.preprocess_dev_data(x_evaluate)
x_evaluate = [list(x) for x in x_test]
data = pd.DataFrame(x_test)
# Evaluation
# ==================================================
checkpoint_file_root = os.path.join(FLAGS.checkpoint_dir, "checkpoints")
checkpoint_file = tf.train.latest_checkpoint(checkpoint_file_root)
print checkpoint_file
def runModel(data, target):
processData.processData(data)
#select attributes...
if target not in data[0].keys():
print('Please enter a valid target attribute')
attributes = [k for k in data[0].keys()]
print('\n\n')
testAttributes = [[
'Precipitation', ' Consumption', 'c G Coverage',
'b Proportion of Tech Value', ' research spending per GDP',
' CO Emission', ' percentage of manufacturing employment',
' Manufacutring add value', ' Transportation Volume', ' number of ATM',
' not in education or employment', ' material footprint',
' Annual growth per employee', ' Annual Growth Rate', 'b Scholars',
' Organized Learning', ' Reading Proficiency', ' Malnutritiohn',
' Food insecurities', ' Undernourishment', 'Population', 'Area sq mi',
'Pop Density per sq mi', 'Net migration',
'Infant mortality per births', 'GDP per capita', 'Literacy ',
'Arable ', 'Crops ', 'Other ', 'Climate', 'Birthrate', 'Deathrate',
'Agriculture', 'Industry', 'Service', 'CoastlineLength'
],
[
'Precipitation', 'Climate', 'Arable ', 'Population',
'Area sq mi', 'Pop Density per sq mi',
'CoastlineLength'
], ['Climate'], ['Area sq mi'],
['Pop Density per sq mi'], ['Industry']]
attributes = testAttributes[1]
print('Performing experiment for target:', target, ', and attributes: \n',
attributes)
for ex in data:
keySet = list(ex.keys())
for k in keySet:
if k not in attributes and k != target: ex.pop(k)
print('remaining attributes are: ', data[0].keys())
#discretize our target, remove unneeded
targetData = [ex for ex in data if type(ex[target]) != str]
#temporary step: write out the data that can be found:
with open('noQmarks.csv', 'w', newline='') as csvfile:
fieldnames = [k for k in targetData[0].keys()]
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
for ex in targetData:
writer.writerow(ex)
targetMedian = st.median([val[target] for val in targetData])
for ex in targetData:
ex[target] = 'upperHalf' if ex[target] > targetMedian else 'lowerHalf'
with open('discretized.csv', 'w', newline='') as csvfile:
fieldnames = [k for k in targetData[0].keys()]
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
for ex in targetData:
writer.writerow(ex)
print("median value for target:", target, ': ', targetMedian)
#set which attribute are continuous, which ones are not...
continuous = [
'Precipitation', 'Arable ', 'Crops ', 'Other ', 'Population',
'Area sq mi', 'Pop Density per sq mi', 'CoastlineLength'
]
results = []
for i in range(1):
model = ID3.ID3Augmented(attributes, target, continuous, targetData)
results.append(model.runTrial(1))
print(sum(results) / len(results))
else:
# Wait for the inverter to come online
print "Inverter is not online: " + gw.to_string()
interval = 20.0*60
csv.reset()
process.reset()
# Wait for the next sample
print "sleep " + str(interval) + " seconds before next sample"
time.sleep(interval)
if __name__ == "__main__":
# Main entry point for the Goodwe to PVoutput logging script. Creates the
# objects needed and sets the URL and system IDs. These are defined at the
# start of this file
#
# These URLs should be okay for Goodwe-power and PVoutput.org (and yes, there
# is a spelling error in the goodwe URL).
goodwe_url = 'http://goodwe-power.com/PowerStationPlatform/PowerStationReport/InventerDetail'
pvoutput_url = 'http://pvoutput.org/service/r2/addstatus.jsp'
goodwe = readGoodwe.readGoodwe( goodwe_url, sid)
pvoutput = pvoutput.pvoutput( pvoutput_url, sys_id, api_key)
csv = csvoutput.csvoutput( csv_dir, 'Goodwe_PV_data')
process = processData.processData( pvoutput)
# Perform main loop
mainloop( goodwe, pvoutput, csv)
import requests as req
from env import env
from getData import getData
from processData import processData
from writeMessages import writeMessages
if __name__ == '__main__':
# get data from db for yesterday and process it
df = getData()
df = processData(df)
# craft messages from data
messages = writeMessages(df)
# assemble webhook-url
webhookUrl = f'https://hooks.slack.com/services/{env("S_WORKSPACE")}/{env("S_WEBHOOK_TOKEN")}'
# post to slack channel
for message in messages:
resp = req.post(webhookUrl, json=message)
print(f'response {resp.status_code} [{resp.text}]')
def test_1(self):
gw1 = goodweData.goodweData(
'<tr class=\"DG_Item\"><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td></tr>'
)
gw1.m_inverter_sn = 1
gw1.m_vpv1 = 1.0
gw1.m_vpv2 = 1.0
gw1.m_ipv1 = 1.0
gw1.m_ipv2 = 1.0
gw1.m_vac1 = 1.0
gw1.m_vac2 = 1.0
gw1.m_vac3 = 1.0
gw1.m_iac1 = 1.0
gw1.m_iac2 = 1.0
gw1.m_iac3 = 1.0
gw1.m_fac1 = 1.0
gw1.m_fac2 = 1.0
gw1.m_fac3 = 1.0
gw1.m_pgrid = 1.0
gw1.m_eday = 1.0
gw1.m_etotal = 1.0
gw1.m_htotal = 1.0
gw1.m_temperature = 1.0
gw2 = copy.deepcopy(gw1)
gw2.m_inverter_sn = 2
gw3 = copy.deepcopy(gw1)
gw3.m_inverter_sn = 3
gw4 = copy.deepcopy(gw1)
gw4.m_inverter_sn = 4
gw5 = copy.deepcopy(gw1)
gw5.m_inverter_sn = 5
gw6 = copy.deepcopy(gw1)
gw6.m_inverter_sn = 6
gw10 = copy.deepcopy(gw1)
gw10.m_inverter_sn = 10
gw10.m_vpv1 = 10.0
gw10.m_vpv2 = 10.0
gw10.m_ipv1 = 10.0
gw10.m_ipv2 = 10.0
gw10.m_vac1 = 10.0
gw10.m_vac2 = 10.0
gw10.m_vac3 = 10.0
gw10.m_iac1 = 10.0
gw10.m_iac2 = 10.0
gw10.m_iac3 = 10.0
gw10.m_fac1 = 10.0
gw10.m_fac2 = 10.0
gw10.m_fac3 = 10.0
gw10.m_pgrid = 10.0
gw10.m_eday = 10.0
gw10.m_etotal = 10.0
gw10.m_htotal = 10.0
gw10.m_temperature = 10.0
gw11 = copy.deepcopy(gw10)
gw11.m_inverter_sn = 11
gw12 = copy.deepcopy(gw10)
gw12.m_inverter_sn = 12
process = processData.processData(None, 4 * 60)
process.reset()
print "State:" + process.state_to_string()
process.processSample(gw1)
print "State:" + process.state_to_string()
process.processSample(gw2)
print "State:" + process.state_to_string()
process.processSample(gw3)
print "State:" + process.state_to_string()
process.processSample(gw4)
print "State:" + process.state_to_string()
process.processSample(gw10)
print "State:" + process.state_to_string()
process.processSample(gw11)
print "State:" + process.state_to_string()
process.processSample(gw5)
print "State:" + process.state_to_string()
process.processSample(gw6)
print "State:" + process.state_to_string()
process.processSample(gw12)
print "State:" + process.state_to_string()
process.reset()
print "State:" + process.state_to_string()
sh.write(0, 4, 'Check?')
sh.write(0, 5, 'Ma so lop')
stt = 1
for element in name:
print("processing " + element)
direction = './input/' + element
if len(name) == 2:
element = element[:-6]
elif len(name) == 1:
element = element[:-4]
output_filename = element + "_result.xls"
digit_name = element
# Start recognize digit
input_img = Image.open(direction).convert('L')
# Process input data
coordinates = processData(direction)
# check empty case
for x in coordinates:
# for debug
# =============================================================================
# if stt != 15:
# stt += 1
# continue
# =============================================================================
img = input_img.crop(x)
check = np.asarray(img)
check.setflags(write=1)
for x in check:
i = 0