def analyze_stock(stock, force=False):
stock = str(stock)
sd = StockData(stock, 'basic', 'today', addition=14 + 60) # today + 14 for observation, 60 for trend line plotting
df = sd.data
if df is None or len(df) == 0:
return
if stock == 'index':
stock_name = 'index'
else:
stock_name = stock_list.loc[stock]['Catagory'] + '-' + stock + '-' + stock_list.loc[stock]['Name']
res = 1
idx = 1
fig = plt.figure()
period = df.index[0] + ' ~ ' + df.index[-1]
fig.suptitle(stock_name + ', ' + datetime.now().date().strftime('%Y/%m/%d') + '更新', fontproperties=my_font)
if res != 0 or force:
plt.subplot(3, 2, idx)
idx += 1
res = stock_filter.is_breakthrough_trend(df['收盤'], observe_days=15, lower_bound=3, upper_bound=7, plot=True)
if res == 0:
res = stock_filter.is_breakthrough_trend(df['收盤'], observe_days=15, lower_bound=3, upper_bound=7, plot=True, direction='down')
res *= -1
plt.title('突破: 3%~7%', fontproperties=my_font)
plt.xlabel(period)
plt.xticks([])
#if res != 0:
#plt.subplot(3, 2, idx)
#idx += 1
#res = stock_filter.is_correction(df['收盤'], check_region=5, percent=2, height_ratio=14, plot_title=stock_name)
if res != 0 or force:
plt.subplot(3, 2, idx)
idx += 1
plot_title = '成交量>3000張'
res *= stock_filter.is_at_least(df['成交股數'] / 1000, check_region=5, quantity=3000, plot=True)
plt.title(plot_title, fontproperties=my_font)
plt.xlabel(period)
plt.xticks([])
if res != 0 or force:
plt.subplot(3, 2, idx)
idx += 1
plot_title = '成交量放大'
res *= stock_filter.is_steeper(df['成交股數'] / 1000, check_region=5, plot=True)
plt.title(plot_title, fontproperties=my_font)
plt.xlabel(period)
plt.xticks([])
if res != 0 or force:
plt.subplot(3, 2, idx)
idx += 1
sd = StockData(stock, 'revenue', '2013/6/1-today')
df = sd.data
if df is not None:
plot_title = '營收'
stock_filter.is_positive_step(df['營業收入'], step=12, plot=True, direction='up')
# ignore ret
plt.title(plot_title, fontproperties=my_font)
plt.xlabel('2013/6/1 ~' + df.index[-1].strftime('%Y/%m/%d'))
plt.xticks([])
else:
res = 0
if res != 0 or force:
plt.subplot(3, 2, idx)
idx += 1
sd = StockData(stock, 'basic', '2012/1/1-today')
df = sd.data
plot_title = '週線'
stock_filter.sample_and_plot(df['收盤'], sample_distance=5, plot=True, check_sample=4)
plt.title(plot_title, fontproperties=my_font)
plt.xlabel('2012/1/1 ~ ' + df.index[-1])
plt.xticks([])
if res != 0 or force:
plt.tight_layout()
plt.subplots_adjust(top=0.90) # put this line after subplot, or it takes no effect
if force:
plt.savefig(output_path + '/interest/' + stock_name + '.png')
elif res == 1:
plt.savefig(output_path + '/up/' + stock_name + '.png')
else:
plt.savefig(output_path + '/down/' + stock_name + '.png')
#plt.clf()
plt.close(fig)
print(stock, res)
print('wait for start time')
time.sleep(5)
batch = []
end_time = datetime.strptime("13:40:00", "%H:%M:%S").time()
group_index = 0
for stock in stock_data.stock_list.index:
stock = str(stock)
print(stock)
sd = StockData(stock, 'basic', '2016/4/1-today')
df = sd.data
if len(df) == 0:
continue
if 0:
res = stock_filter.is_breakthrough_trend(df['收盤'], check_region=5, lower_bound=5,\
upper_bound=10, plot_title='向上突破: 5%~10%', preselection=True)
if not res:
continue
y_tomorrow = res[1]
res = res[0]
#if res == False and y_tomorrow / df['收盤'][-1] >= 1.1:
if 0:
#print(stock, 'is not possible to meet target price')
pass
else:
batch.append([stock, df['收盤'][-1], 10, 3, 1])
if len(batch) >= 30:
p = Process(target=monitor_stocks, args=(batch, end_time, '[group ' + str(group_index) + ']',))
p.start()
group_index += 1
batch = []
