def stock_analyze(basic, kdata, policy_args):
### 基本条件选取
get_index = include_analyze(basic, kdata, policy_args)
if get_index is None:
logger.debug("include_analyze() return None")
return None
else:
[pick_index, take_index] = get_index
### 排它条件过滤
if exclude_analyze(basic, kdata, pick_index, take_index, policy_args):
logger.debug("exclude_analyze() return True")
return None
### 构造结果
result = {}
result[dogen.RST_COL_CODE] = basic.name # 股票代码
result[dogen.RST_COL_NAME] = basic[dogen.NAME] # 证券简写
result[dogen.RST_COL_INDUSTRY] = basic[dogen.INDUSTRY]
result[dogen.RST_COL_TAKE_TRADE] = kdata.index[take_index] # 命中交易日
result[dogen.RST_COL_LAST_CLOSE] = kdata.iloc[0][dogen.P_CLOSE] # 最后一日收盘价
result[dogen.RST_COL_OUTSTANDING] = round(
kdata.iloc[0][dogen.P_CLOSE] * basic[dogen.OUTSTANDING], 2) # 流通市值
result[dogen.RST_COL_SCORE] = score_analyze(basic, kdata, pick_index,
take_index, policy_args) # 打分
result[dogen.RST_COL_MATCH_TIME] = dogen.datetime_now() # 选中时间
result[dogen.RST_COL_INDEX] = '%s_%s' % (
basic.name, kdata.index[take_index]) # 唯一标识，用于持久化去重
return result
def stock_analyze(basic, kdata, policy_args):
### 基本条件选取
get_index = include_analyze(basic, kdata, policy_args)
if get_index is None:
logger.debug("include_analyze() return None")
return None
else:
[pick_index, take_index] = get_index
### 排它条件过滤
if exclude_analyze(basic, kdata, pick_index, take_index, policy_args):
logger.debug("exclude_analyze() return True")
return None
rise_range = dogen.get_last_rise_range(kdata, 0, sIdx=pick_index)
if rise_range is not None:
[pick_index, max_index, inc_close, get_lhigh, tmp_index] = rise_range
### 构造结果
result = {}
result[dogen.RST_COL_CODE] = basic.name # 股票代码
result[dogen.RST_COL_NAME] = basic[dogen.NAME] # 证券简写
result[dogen.RST_COL_INDUSTRY] = basic[dogen.INDUSTRY]
result[dogen.RST_COL_START] = kdata.index[pick_index]
result[dogen.RST_COL_TAKE_TRADE] = kdata.index[take_index] # 命中交易日
result[dogen.RST_COL_LAST_CLOSE] = kdata.iloc[0][dogen.P_CLOSE] # 最后一日收盘价
result[dogen.RST_COL_OUTSTANDING] = round(
kdata.iloc[0][dogen.P_CLOSE] * basic[dogen.OUTSTANDING], 2) # 流通市值
result[dogen.RST_COL_INC_HL] = dogen.get_highlimit_trades(kdata,
eIdx=pick_index +
1).size
result[dogen.RST_COL_SCORE] = score_analyze(basic, kdata, pick_index,
take_index, policy_args)
result[dogen.RST_COL_MATCH_TIME] = dogen.datetime_now() # 选中时间
result[dogen.RST_COL_INDEX] = '%s_%s' % (
basic.name, kdata.index[take_index]) # 唯一标识，用于持久化去重
return result
def __statistics_analyze(db, basic, kdata, save_result, args):
""" 统计单只股票上涨区间
参数说明：
basic - 股票基本信息
kdata - 股票交易数据
mini_rise - 区间最小涨幅
mini_hl - 区间最少涨停板数
"""
### 参数处理
mini_rise = __parse_policy_args(args, MINI_RISE)
mini_hl = __parse_policy_args(args, MINI_HL)
### 循环检查
tmpId = 0
match = []
while True:
rise_range = dogen.get_last_rise_range(kdata, mini_rise, max_fall=round(mini_rise/2, 2), sIdx=tmpId)
if rise_range is None:
break
else:
[min_index, max_index, inc_close, get_hl, tmpId] = rise_range
### 忽略不符合连板要求的区间
outstanding = None
max_hl_serial = 0
tmp_hl_serial = 0
for temp_index in range(min_index, max_index-1, -1):
if kdata.iloc[temp_index][dogen.P_CLOSE] < kdata.iloc[temp_index][dogen.L_HIGH]:
tmp_hl_serial = 0
continue
tmp_hl_serial += 1
if tmp_hl_serial > max_hl_serial:
max_hl_serial = tmp_hl_serial
if tmp_hl_serial > 2 and outstanding is None:
outstanding = round(kdata.iloc[temp_index][dogen.P_CLOSE] * basic[dogen.OUTSTANDING], 2)
pass
if max_hl_serial < mini_hl:
continue
### 保存区间结果
result = {}
result[dogen.RST_COL_CODE] = basic.name
result[dogen.RST_COL_NAME] = basic[dogen.NAME] # 证券简写
result[dogen.RST_COL_INDUSTRY] = basic[dogen.INDUSTRY]
result[dogen.RST_COL_START] = kdata.index[min_index]
result[dogen.RST_COL_END] = kdata.index[max_index]
result[dogen.RST_COL_START_CLOSE] = kdata.iloc[min_index][dogen.P_CLOSE] # 起始收盘价
result[dogen.RST_COL_LAST_CLOSE] = kdata.iloc[max_index][dogen.P_CLOSE] # 最高收盘价
result[dogen.RST_COL_RISE_RATE] = dogen.caculate_incr_percentage(result[dogen.RST_COL_LAST_CLOSE], result[dogen.RST_COL_START_CLOSE])
result[dogen.RST_COL_INC_HL] = get_hl
result[dogen.RST_COL_OUTSTANDING] = outstanding # 流通市值
result[dogen.RST_COL_MATCH_TIME] = dogen.datetime_now() # 选中时间
result[dogen.RST_COL_INDEX] = '%s_%s' % (basic.name, kdata.index[min_index])
match.append(result)
### 保存结果
if save_result:
rdata = db.lookup_statistics_largerise_range(cond={dogen.RST_COL_CODE:basic.name}, descending_by=dogen.RST_COL_START)
if rdata is None or len(rdata)<=0:
db.insert_statistics_largerise_range([result], key_name=dogen.RST_COL_INDEX)
continue
rlast = rdata[0]
if rlast[dogen.RST_COL_END] < result[dogen.RST_COL_START]:
db.insert_statistics_largerise_range([result], key_name=dogen.RST_COL_INDEX)
continue
### 重叠合并
tdata = kdata[(kdata.index > rlast[dogen.RST_COL_END])&(kdata.index <= result[dogen.RST_COL_END])]
rlast[dogen.RST_COL_INC_HL] = rlast[dogen.RST_COL_INC_HL] + tdata[tdata[dogen.P_CLOSE]>=tdata[dogen.L_HIGH]].index.size
rlast[dogen.RST_COL_END] = result[dogen.RST_COL_END]
rlast[dogen.RST_COL_LAST_CLOSE] = result[dogen.RST_COL_LAST_CLOSE]
rlast[dogen.RST_COL_RISE_RATE] = dogen.caculate_incr_percentage(rlast[dogen.RST_COL_LAST_CLOSE], rlast[dogen.RST_COL_START_CLOSE])
rlast[dogen.RST_COL_MATCH_TIME] = result[dogen.RST_COL_MATCH_TIME]
db.insert_statistics_largerise_range([rlast], key_name=dogen.RST_COL_INDEX)
return match