def analisisAscendente(entrada):
global resultado
lectura = entrada.lower()
resultado = lector.parse(lectura)
imgarbol.parse(lectura)
consola.config(state=DISABLED)
messagebox.showinfo('Informacion', 'Se ha ejecutado el analisis')
def loadData(idList, conString):
con = cx_Oracle.connect(conString)
datalist = []
flags = []
genes = []
for f in idList:
#print(f)
dt = rd.read(int(f), con)
dt = pr.parse(dt)
if (len(genes) > 0):
if not np.all(np.array(dt[0]) == np.array(genes)):
print('Gene lists do not match')
exit()
genes = dt[0]
datalist.append(dt[2])
flags.append(dt[3])
con.close()
results = []
results.append(genes)
results.append(flags)
results.append(datalist)
return results
def run_norm_mongodb(id_list):
datalist = []
flags = []
genes = []
mongodb = mongo.MongoConecction()
for id in id_list:
dt = mongodb.read_from_mongo(id)
dt = pr.parse(dt)
if (len(genes) > 0):
if (np.all(np.array(dt[0]) == np.array(genes)) != True):
print('Gene lists do not match')
exit()
genes = dt[0] # Gene name
datalist.append(dt[2]) # Gene values
flags.append(dt[3])
return nor.process(genes, dt[1], id_list, datalist, flags)
def runNorm(idList, conString):
con = cx_Oracle.connect(conString)
datalist = []
flags = []
genes = []
for f in idList:
#print(f)
dt = rd.read(int(f), con)
dt = pr.parse(dt)
if (len(genes) > 0):
if (np.all(np.array(dt[0]) == np.array(genes)) != True):
print('Gene lists do not match')
exit()
genes = dt[0]
datalist.append(dt[2])
flags.append(dt[3])
con.close()
return nor.process(genes, dt[1], idList, datalist, flags)
T[61] = 2548.
dump_interval = 5000
run = 500000
thermo = ["step", "temp", "density", "c_msd[4]"]
#therm = ["without","Hoover","Berendsen"]
filename = "DiffSi.in"
rainbow = ['r', 'c', 'm', 'g', 'b']
for i in tqdm.trange(0, N - 3):
#
dumpname = "equil.temp_%f" % T[i]
#os.system('mpirun -np 8 lmp_mpi -v T %f -v dt %f -v Dump %d -v Run %d -v dumpname %s -in %s' % (T[i],dt,dump_interval,run,dumpname,filename))
foo = "diff_temp%f.log" % T[i] #must be activated when producing msd logs!
#os.system("mv log.lammps %s"%foo) #must be activated when producing msd logs!
temp, msd, time = parse2.parse(run, dump_interval, dt, thermo, system_size,
foo, T[i])
#msd = (msd[-1]-msd[0]) / (time[-1]-time[0])
#msd = msd/6. * 10**(-8) #m**2 per sec
color = i % 5
plt.plot(time, msd, '%s' % rainbow[color]) #,label="Temp = %3.1fK"% temp )
plt.title("Diffusion of Si for varius temperatures", size=16)
#plt.legend(loc="best")
#plt.ylabel(r"D[m$^2$/s]",size=19)
plt.xlabel("$t$", size=15)
plt.show()
#parse2.parse_g()
os.system(cmd)
f = open("%sTotal.csv"%(to_path),"a+")
total_header = ['年月','全行外匯活期存款','全行外匯定期存款','全行總額','國內外匯活期存款','國內外匯定期存款','國內總額','海外外匯活期存款','海外外匯定期存款','海外總額']
f.write(",".join(total_header)+"\n")
f.close()
#Use parse.py to extract data from xls to csv before 2011.2
for yy in range(95,100):
for mm in range(1,13):
date = '%d%02d'%(yy,mm)
parse.parse(from_path,to_path,date)
parse.parse(from_path,to_path,'10001')
#Use parse2.py to extract data from xls to csv 2011.2 - now
for mm in range(2,13):
date = '%d%02d'%(100,mm)
parse2.parse(from_path,to_path,date)
for mm in range(1,13):
date = '%d%02d'%(101,mm)
parse2.parse(from_path,to_path,date)
for mm in range(1,13):
date = '%d%02d'%(102,mm)
parse2.parse(from_path,to_path,date)
#parse2.parse(from_path,to_path,'10201')
#parse2.parse(from_path,to_path,'10202')
if __name__ == '__main__':
from_path= '/Users/aha/Dropbox/Project/Financial/Data/'
to_path = '/Users/aha/Dropbox/Project/Financial/Codes/csv/'
cmd = "rm %sTotal.csv"%(to_path)
os.system(cmd)
f = open("%sTotal.csv"%(to_path),"a+")
total_header = ['年月','全行外匯活期存款','全行外匯定期存款','全行總額','國內外匯活期存款','國內外匯定期存款','國內總額','海外外匯活期存款','海外外匯定期存款','海外總額']
f.write(",".join(total_header)+"\n")
f.close()
yy = 100
mm = 2
for yy in range(95,100):
for mm in range(1,13):
date = '%d%02d'%(yy,mm)
parse.parse(from_path,to_path,date)
parse.parse(from_path,to_path,'10001')
for mm in range(2,13):
date = '%d%02d'%(100,mm)
parse2.parse(from_path,to_path,date)
for mm in range(1,13):
date = '%d%02d'%(101,mm)
parse2.parse(from_path,to_path,date)
parse2.parse(from_path,to_path,'10201')
parse2.parse(from_path,to_path,'10202')
def main():
parse()
indexes()
query()
import parse2 as pr
import numpy as np
import read2 as rd
import normalize2 as nor
import cx_Oracle
from scipy import stats as sst
#fileList=['/home/khaosdev7/Downloads/20170901_CART04_RCC/20170901_CART04_56_12.RCC', '/home/khaosdev7/Downloads/20170901_CART04_RCC/20170901_CART04_54_10.RCC', '/home/khaosdev7/Downloads/20170901_CART04_RCC/20170901_CART04_42_11.RCC']
idList = [1, 2]
con = cx_Oracle.connect('webapp/[email protected]:1521')
datalist = []
flags = []
for f in idList:
print(f)
dt = rd.read(f, con)
dt = pr.parse(dt)
datalist.append(dt[2])
flags.append(dt[3])
con.close()
nor.process(dt[0], dt[1], idList, datalist, flags)
#print (results)
