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)