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161 | # -*- coding: utf-8 -*-
from cassandra.cluster import Cluster
import csv
import math
import numpy
import matplotlib.pyplot as plt
import matplotlib.font_manager as fontManager
class LoadRunner:
session = None
def __init__(self):
pass
def connectDB(self, nodes):
try:
cluster = Cluster(nodes)
self.session = cluster.connect()
except (RuntimeError, TypeError, NameError):
pass
def closeDB(self):
if self.session is None:
return
try:
self.session.cluster.shutdown()
except (RuntimeError, TypeError, NameError):
pass
def runSQL(self, cql):
if self.session is None:
return
try:
self.session.execute(cql)
except (RuntimeError, TypeError, NameError):
print(cql)
def runQuery(self, cql):
if self.session is None:
return
resultSetDB = None
try:
resultSetDB = self.session.execute(cql)
except (RuntimeError, TypeError, NameError):
pass
return resultSetDB
def loadDataFromCSV(self, csvFile, stockID='IBM', showDetail=True):
if self.session is None:
return
self.runSQL('TRUNCATE emprogria.stock_hist')
with open(csvFile, 'r') as csvF:
# Date, Open, High, Low, Close, Volume, Adj Close
fieldHead = True
for rowDB in csv.DictReader(csvF, ["日期", "開盤", "最高", "最低", "收盤", "成交量", "盤後"]):
if fieldHead:
fieldHead = False
else:
if (rowDB is not None):
cql = "INSERT INTO emprogria.stock_hist " \
"(stock_date, stock_id, stock_quotes) " \
"VALUES('%s', '%s', [%.2f, %.2f, %.2f, %.2f, %.2f])" % \
(rowDB['日期'], stockID,
float(rowDB['開盤']), float(rowDB['收盤']),
float(rowDB['最高']), float(rowDB['最低']),
math.log(float(rowDB['成交量'])))
self.runSQL(cql)
if showDetail:
print(u"日期:%s\t%s\t盤後:%.2f" % (
float(rowDB['日期']), stockID, float(rowDB['盤後'])))
def plotLine(self, stockID, X, Y):
prop = fontManager.FontProperties(fname='/System/Library/Fonts/PingFang.ttc')
plt.rcParams["font.family"] = prop.get_name()
f, axarr = plt.subplots(3)
axarr[0].set_title(u"%s 收盤指數\n差率 線圖" % stockID, fontproperties=prop)
axarr[1].set_xlabel(u"日期序", fontproperties=prop)
axarr[0].set_ylabel(u"收盤指數", fontproperties=prop)
axarr[0].plot(X, Y, 'r', label=u'差率')
sp = numpy.fft.fft(Y)
freq = numpy.fft.fftfreq(Y.shape[-1])
# 實部
axarr[1].set_ylabel(u"收盤 實部指數", fontproperties=prop)
axarr[1].get_xaxis().set_visible(False)
sp.real[sp.real > 10] = 0
axarr[1].plot(freq, sp.real, 'b', label=u'實部')
# 虛部
axarr[2].set_title(u"傅立葉 線圖", fontproperties=prop)
axarr[2].set_xlabel(u"頻率", fontproperties=prop)
axarr[2].set_ylabel(u"收盤 虛部指數", fontproperties=prop)
axarr[2].plot(freq, sp.imag, 'g', label=u'虛部')
# plt.show()
plt.savefig('%s.png' % stockID)
plt.close()
if __name__ == "__main__":
loadRunner = LoadRunner()
stockID = 'IBM'
csvFile = '%s.csv' % stockID
loadData, showDetail = (False, False)
loadRunner.connectDB(['127.0.0.1'])
if loadData:
loadRunner.loadDataFromCSV(csvFile, stockID, showDetail)
_stockDate = []
_stockClose = []
resultSetDB = loadRunner.runQuery("SELECT stock_date, stock_quotes "
"FROM emprogria.stock_hist WHERE stock_id='%s' ALLOW FILTERING" % stockID)
if resultSetDB is not None:
_resultSetDB = sorted(resultSetDB)
for stockHist in _resultSetDB:
stockQuotes = stockHist[1]
_stockDate.append(stockHist[0])
_stockClose.append(stockQuotes[1])
if showDetail:
print('%s' % stockHist[0], end='\t')
for stockQuote in stockQuotes:
print('%.2f' % stockQuote, end='\t')
print()
loadRunner.closeDB()
stockClose = numpy.array(_stockClose)
stockClose_1 = numpy.diff(stockClose)
stockMagnitude = stockClose_1.max() - stockClose_1.min()
stockClose_2 = (stockClose_1 - stockClose_1.min()) / stockMagnitude
_stockDate_2 = _stockDate[1:]
loadRunner.plotLine(stockID, range(0, len(_stockDate_2)), stockClose_2) |
