def genStkIdxPic(stk_df, stk_code, current_date, root_save_dir, pic_name='stk_idx.png'):
"""
打印常用指标
"""
# 按升序排序
stk_df = stk_df.sort_values(by='date', ascending=True)
"""
增加指标
'RSI5', 'RSI12', 'RSI30'
'SAR'
'slowk', 'slowd'
'upper', 'middle', 'lower'
'MOM'
"""
stk_df = addStkIndexToDf(stk_df).tail(60)
fig, ax = plt.subplots(nrows=5, ncols=1)
ax[0].plot(range(0, len(stk_df['date'])), stk_df['RSI5'], 'b--', label='RSI5线', linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])), stk_df['RSI12'], 'r--', label='RSI12线', linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])), stk_df['RSI30'], 'g*--', label='RSI30', linewidth=0.5, markersize=1)
ax[1].plot(range(0, len(stk_df['date'])), stk_df['SAR'], 'g*--', label='SAR', linewidth=0.5, markersize=1)
ax[2].plot(range(0, len(stk_df['date'])), stk_df['slowk'], 'g*--', label='slowk', linewidth=0.5, markersize=1)
ax[2].plot(range(0, len(stk_df['date'])), stk_df['slowd'], 'r*--', label='slowd', linewidth=0.5, markersize=1)
ax[3].plot(range(0, len(stk_df['date'])), stk_df['upper'], 'r*--', label='布林上线', linewidth=0.5, markersize=1)
ax[3].plot(range(0, len(stk_df['date'])), stk_df['middle'], 'b*--', label='布林均线', linewidth=0.5, markersize=1)
ax[3].plot(range(0, len(stk_df['date'])), stk_df['lower'], 'g*--', label='布林下线', linewidth=0.5, markersize=1)
ax[4].plot(range(0, len(stk_df['date'])), stk_df['MOM'], 'g*--', label='MOM', linewidth=0.5, markersize=1)
# 准备下标
xlabel_series = stk_df.apply(lambda x: x['date'][2:].replace('-', ''), axis=1)
ax[0] = addXticklabel(ax[0], xlabel_series, 40, rotation=45)
ax[1] = addXticklabel(ax[1], xlabel_series, 40, rotation=45)
ax[2] = addXticklabel(ax[2], xlabel_series, 40, rotation=45)
ax[3] = addXticklabel(ax[3], xlabel_series, 40, rotation=45)
ax[4] = addXticklabel(ax[4], xlabel_series, 40, rotation=45)
for ax_sig in ax:
ax_sig.legend(loc='best', fontsize=5)
# 保存图片
save_dir = root_save_dir+current_date+'/'+str(stk_code)+'/'
if not os.path.exists(save_dir):
os.makedirs(save_dir)
plt.tight_layout()
plt.savefig(save_dir+pic_name, dpi=300)
plt.close()
return save_dir+pic_name
def gen_Idx_Pic(stk_df, stk_code=''):
"""
打印常用指标
"""
# 按升序排序
stk_df = stk_df.sort_values(by='date', ascending=True)
"""
增加指标
'RSI5', 'RSI12', 'RSI30'
'SAR'
'slowk', 'slowd'
'upper', 'middle', 'lower'
'MOM'
"""
stk_df = addStkIndexToDf(stk_df).tail(60)
set_background_color(bc='w')
result_analysis = []
# 检查SAR
attention = False
sar_tail_origin = stk_df.tail(2)
sar_tail = sar_tail_origin.copy()
sar_tail['compare'] = sar_tail_origin.apply(lambda x: x['SAR'] - x['close'], axis=1)
title_tmp = stk_code + ' ' + code2name(stk_code)
if sar_tail.head(1)['compare'].values[0] * sar_tail.tail(1)['compare'].values[0] < 0:
if sar_tail.tail(1)['SAR'].values[0] < sar_tail.tail(1)['close'].values[0]:
title_tmp = stk_code + ' ' + code2name(stk_code) + ' 注意 SAR 指标翻转，后续数天可能上涨！'
result_analysis.append(title_tmp)
set_background_color(bc='b_r')
else:
title_tmp = stk_code + ' ' + code2name(stk_code) + ' 注意 SAR 指标翻转，后续数天可能下跌！'
result_analysis.append(title_tmp)
set_background_color(bc='b_g')
attention = True
fig, ax = plt.subplots(nrows=5, ncols=1)
ax[0].plot(range(0, len(stk_df['date'])), stk_df['RSI5'], 'b--', label='RSI5线', linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])), stk_df['RSI12'], 'r--', label='RSI12线', linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])), stk_df['RSI30'], 'g*--', label='RSI30', linewidth=0.5, markersize=1)
ax[0].plot(range(0, len(stk_df['date'])), [20 for a in range(len(stk_df['date']))], 'b--', linewidth=0.3)
ax[0].plot(range(0, len(stk_df['date'])), [80 for a in range(len(stk_df['date']))], 'b--', linewidth=0.3)
ax[0].set_ylim(0, 100)
ax[1].plot(range(0, len(stk_df['date'])), stk_df['SAR'], 'r--', label='SAR', linewidth=0.5, markersize=1)
ax[1].plot(range(0, len(stk_df['date'])), stk_df['close'], 'g*--', label='close', linewidth=0.5, markersize=1)
ax[2].plot(range(0, len(stk_df['date'])), stk_df['slowk'], 'g*--', label='slowk', linewidth=0.5, markersize=1)
ax[2].plot(range(0, len(stk_df['date'])), stk_df['slowd'], 'r*--', label='slowd', linewidth=0.5, markersize=1)
ax[2].plot(range(0, len(stk_df['date'])), [20 for a in range(len(stk_df['date']))], 'b--', linewidth=0.3)
ax[2].plot(range(0, len(stk_df['date'])), [80 for a in range(len(stk_df['date']))], 'b--', linewidth=0.3)
ax[2].set_ylim(0, 100)
ax[3].plot(range(0, len(stk_df['date'])), stk_df['upper'], 'r*--', label='布林上线', linewidth=0.5, markersize=1)
ax[3].plot(range(0, len(stk_df['date'])), stk_df['middle'], 'b*--', label='布林均线', linewidth=0.5, markersize=1)
ax[3].plot(range(0, len(stk_df['date'])), stk_df['lower'], 'g*--', label='布林下线', linewidth=0.5, markersize=1)
ax[4].plot(range(0, len(stk_df['date'])), stk_df['MOM'], 'g*--', label='MOM', linewidth=0.5, markersize=1)
# 准备下标
xlabel_series = stk_df.apply(lambda x: x['date'][2:].replace('-', ''), axis=1)
ax[0] = addXticklabel(ax[0], xlabel_series, 40, rotation=45)
ax[1] = addXticklabel(ax[1], xlabel_series, 40, rotation=45)
ax[2] = addXticklabel(ax[2], xlabel_series, 40, rotation=45)
ax[3] = addXticklabel(ax[3], xlabel_series, 40, rotation=45)
ax[4] = addXticklabel(ax[4], xlabel_series, 40, rotation=45)
for ax_sig in ax:
ax_sig.legend(loc='best', fontsize=5)
fig.tight_layout() # 调整整体空白
plt.subplots_adjust(wspace=0, hspace=0) # 调整子图间距
ax[0].set_title(title_tmp)
return fig, ax, attention, result_analysis
# encoding=utf-8
def plot_op_result(df):
"""
打印BS操作效果
列名字：
origin_money ：不使用策略时的效益
strategy_money ：使用策略时的效益
BS : 记录操作行为的列
money_remain : 剩余的资金
:param df:
:return:
"""
sh_index = df
fig, ax = plt.subplots(nrows=3, ncols=1)
ax[0].plot(range(len(sh_index['date'])), sh_index['close'], 'b--')
# 打印BS操作
tuple_bs = list(
zip(range(len(sh_index['date'])), sh_index['BS'], sh_index['close']))
tuple_b = list(filter(lambda x: x[1] == 'buy', tuple_bs))
ax[0].plot(list(map(lambda x: x[0], tuple_b)),
list(map(lambda x: x[2], tuple_b)),
'r*',
label='buy')
tuple_s = list(filter(lambda x: x[1] == 'sale', tuple_bs))
ax[0].plot(list(map(lambda x: x[0], tuple_s)),
list(map(lambda x: x[2], tuple_s)),
'g*',
label='sale')
# 打印对比
ax[1].plot(range(len(sh_index['date'])),
sh_index['origin_money'],
'b--',
label='no_use_strategy')
ax[1].plot(range(len(sh_index['date'])),
sh_index['strategy_money'],
'r--',
label='use_strategy')
# 打印stk数量和剩余money
ax[2].plot(range(len(sh_index['date'])),
normal01(sh_index['money_remain']),
'b--',
label='剩余money')
# ax[2].plot(range(len(sh_index['date'])), normal01(sh_index['amount_remain']), 'r--', label='剩余stk数量')
# 整理x轴label
x_label = sh_index.apply(lambda x: str(x['date'])[2:].replace('-', ''),
axis=1)
ax[0] = addXticklabel(ax[0], x_label, 40, rotation=45, fontsize=8)
ax[1] = addXticklabel(ax[1], x_label, 40, rotation=45, fontsize=8)
ax[2] = addXticklabel(ax[2], x_label, 40, rotation=45, fontsize=8)
# ax[3] = addXticklabel(ax[3], x_label, 40, rotation=45, fontsize=8)
for ax_sig in ax:
ax_sig.legend(loc='best')
plt.show()
ax[2].plot(range(len(sh_index['date'])),
normal01(sh_index['money_remain']),
'b--',
label='剩余money')
# ax[2].plot(range(len(sh_index['date'])), normal01(sh_index['amount_remain']), 'r--', label='剩余stk数量')
# # 打印stk数量和剩余money
ax[1].plot(range(len(sh_index['date'])),
sh_index['C-M20'],
'g--',
label='离心力')
ax[1].plot(range(len(sh_index['date'])),
np.zeros(len(sh_index['date'])),
'b--',
label='零线')
# 整理x轴label
x_label = sh_index.apply(lambda x: str(x['date'])[2:].replace('-', ''),
axis=1)
ax[0] = addXticklabel(ax[0], x_label, 40, rotation=45, fontsize=8)
ax[1] = addXticklabel(ax[1], x_label, 40, rotation=45, fontsize=8)
ax[2] = addXticklabel(ax[2], x_label, 40, rotation=45, fontsize=8)
ax[3] = addXticklabel(ax[3], x_label, 40, rotation=45, fontsize=8)
for ax_sig in ax:
ax_sig.legend(loc='best')
plt.show()
end = 0
def genStkIdxPicForQQ(stk_df, stk_code=''):
"""
打印常用指标
"""
# 按升序排序
stk_df = stk_df.sort_values(by='date', ascending=True)
"""
增加指标
'RSI5', 'RSI12', 'RSI30'
'SAR'
'slowk', 'slowd'
'upper', 'middle', 'lower'
'MOM'
"""
stk_df = add_stk_index_to_df(stk_df).tail(60)
fig, ax = plt.subplots(nrows=5, ncols=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['RSI5'],
'b--',
label='RSI5线',
linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['RSI12'],
'r--',
label='RSI12线',
linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['RSI30'],
'g*--',
label='RSI30',
linewidth=0.5,
markersize=1)
ax[0].plot(range(0, len(stk_df['date'])),
[20 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[0].plot(range(0, len(stk_df['date'])),
[80 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[0].set_ylim(0, 100)
ax[1].plot(range(0, len(stk_df['date'])),
stk_df['SAR'],
'r--',
label='SAR',
linewidth=0.5,
markersize=1)
ax[1].plot(range(0, len(stk_df['date'])),
stk_df['close'],
'g*--',
label='close',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df['date'])),
stk_df['slowk'],
'g*--',
label='slowk',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df['date'])),
stk_df['slowd'],
'r*--',
label='slowd',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df['date'])),
[20 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[2].plot(range(0, len(stk_df['date'])),
[80 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[2].set_ylim(0, 100)
ax[3].plot(range(0, len(stk_df['date'])),
stk_df['upper'],
'r*--',
label='布林上线',
linewidth=0.5,
markersize=1)
ax[3].plot(range(0, len(stk_df['date'])),
stk_df['middle'],
'b*--',
label='布林均线',
linewidth=0.5,
markersize=1)
ax[3].plot(range(0, len(stk_df['date'])),
stk_df['lower'],
'g*--',
label='布林下线',
linewidth=0.5,
markersize=1)
ax[4].plot(range(0, len(stk_df['date'])),
stk_df['MOM'],
'g*--',
label='MOM',
linewidth=0.5,
markersize=1)
# 准备下标
xlabel_series = stk_df.apply(lambda x: x['date'][2:].replace('-', ''),
axis=1)
ax[0] = addXticklabel(ax[0], xlabel_series, 40, rotation=45)
ax[1] = addXticklabel(ax[1], xlabel_series, 40, rotation=45)
ax[2] = addXticklabel(ax[2], xlabel_series, 40, rotation=45)
ax[3] = addXticklabel(ax[3], xlabel_series, 40, rotation=45)
ax[4] = addXticklabel(ax[4], xlabel_series, 40, rotation=45)
for ax_sig in ax:
ax_sig.legend(loc='best', fontsize=5)
fig.tight_layout() # 调整整体空白
plt.subplots_adjust(wspace=0, hspace=0) # 调整子图间距
# 检查SAR
attention = False
sar_tail = stk_df.tail(2)
sar_tail['compare'] = sar_tail.apply(lambda x: x['SAR'] - x['close'],
axis=1)
if sar_tail.head(1)['compare'].values[0] * sar_tail.tail(
1)['compare'].values[0] < 0:
plt.title(stk_code + ' 注意 SAR 指标异动！')
attention = True
return fig, ax, attention
def genStkIdxPicForQQ(stk_df):
"""
打印常用指标
"""
# 按升序排序
stk_df = stk_df.sort_values(by='date', ascending=True)
"""
增加指标
'RSI5', 'RSI12', 'RSI30'
'SAR'
'slowk', 'slowd'
'upper', 'middle', 'lower'
'MOM'
"""
stk_df = addStkIndexToDf(stk_df).tail(60)
fig, ax = plt.subplots(nrows=5, ncols=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['RSI5'],
'b--',
label='RSI5线',
linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['RSI12'],
'r--',
label='RSI12线',
linewidth=1)
ax[0].plot(range(0, len(stk_df['date'])),
stk_df['RSI30'],
'g*--',
label='RSI30',
linewidth=0.5,
markersize=1)
ax[0].plot(range(0, len(stk_df['date'])),
[20 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[0].plot(range(0, len(stk_df['date'])),
[80 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[0].set_ylim(0, 100)
ax[1].plot(range(0, len(stk_df['date'])),
stk_df['SAR'],
'r--',
label='SAR',
linewidth=0.5,
markersize=1)
ax[1].plot(range(0, len(stk_df['date'])),
stk_df['close'],
'g*--',
label='close',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df['date'])),
stk_df['slowk'],
'g*--',
label='slowk',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df['date'])),
stk_df['slowd'],
'r*--',
label='slowd',
linewidth=0.5,
markersize=1)
ax[2].plot(range(0, len(stk_df['date'])),
[20 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[2].plot(range(0, len(stk_df['date'])),
[80 for a in range(len(stk_df['date']))],
'b--',
linewidth=0.3)
ax[2].set_ylim(0, 100)
ax[3].plot(range(0, len(stk_df['date'])),
stk_df['upper'],
'r*--',
label='布林上线',
linewidth=0.5,
markersize=1)
ax[3].plot(range(0, len(stk_df['date'])),
stk_df['middle'],
'b*--',
label='布林均线',
linewidth=0.5,
markersize=1)
ax[3].plot(range(0, len(stk_df['date'])),
stk_df['lower'],
'g*--',
label='布林下线',
linewidth=0.5,
markersize=1)
ax[4].plot(range(0, len(stk_df['date'])),
stk_df['MOM'],
'g*--',
label='MOM',
linewidth=0.5,
markersize=1)
# 准备下标
xlabel_series = stk_df.apply(lambda x: x['date'][2:].replace('-', ''),
axis=1)
ax[0] = addXticklabel(ax[0], xlabel_series, 40, rotation=45)
ax[1] = addXticklabel(ax[1], xlabel_series, 40, rotation=45)
ax[2] = addXticklabel(ax[2], xlabel_series, 40, rotation=45)
ax[3] = addXticklabel(ax[3], xlabel_series, 40, rotation=45)
ax[4] = addXticklabel(ax[4], xlabel_series, 40, rotation=45)
for ax_sig in ax:
ax_sig.legend(loc='best', fontsize=5)
return fig, ax
# 展示C-M20的分布
count, bins = np.histogram(sh_index['C-M20'], 100, normed=True)
plt.bar(range(len(count)), count)
plt.show()
fig, ax = plt.subplots(nrows=2, ncols=1)
ax[0].plot(range(0, len(sh_index['date'])),
sh_index['close'],
'r-',
label='20日均线',
linewidth=1)
ax[1].plot(range(0, len(sh_index['date'])),
sh_index['C-M20'],
'g*',
label='C-20日均线',
linewidth=1)
ax[1].plot(range(0, len(sh_index['date'])),
np.zeros(len(sh_index)),
'b',
label='零线')
# 准备下标
ax[0] = addXticklabel(ax[0], sh_index['date'], 40)
ax[1] = addXticklabel(ax[1], sh_index['date'], 40)
for ax_sig in ax:
ax_sig.legend(loc='best')
plt.show()
