def find_trend(df, column, direction, dir_header):
trend = df[column].copy()
more_trend = True
last_end = df.index[0]
trend_gp_id = 0
response = True
while more_trend:
input_df = df[last_end:].copy()
res = trendet.identify_df_trends(df=input_df,
column=column,
identify=direction)
if dir_header in res.columns.to_list():
trend_temp = res[dir_header]
trend_group_list = trend_temp.dropna().unique()
if len(trend_group_list) == 0:
more_trend = False
else:
trend.loc[last_end:] = trend_temp.apply(rename_trend_group,
gp_id=trend_gp_id)
if trend_group_list[-1] == 'Z':
# more trend to be identified
last_end = trend_temp[trend_temp == 'Z'].index[-1]
trend_gp_id = trend_gp_id + 1
else:
more_trend = False
else:
# suddenly the trendet.identify_df_trends fails to create column "Up Trend" or "Down Trend"
trend = pd.Series(np.nan, index=df.index)
more_trend = False
response = False
return trend, response
def minMaxTrend_buylogic_benchmark(self,daysToSubtract=180) :
resizedDf = self.stockValue.iloc[-daysToSubtract:]
trends = identify_df_trends(df=resizedDf, column='Close')
trends.reset_index(inplace=True)
labels = trends['Up Trend'].dropna().unique().tolist()
enterDays = []; exitDays = []
for label in labels :
enterDays.append(trends[trends['Up Trend'] == label]['Date'].iloc[0])
exitDays.append(trends[trends['Up Trend'] == label]['Date'].iloc[-1])
return trends, enterDays, exitDays
def test_trendet():
"""
This function checks that main functions of trendet work properly.
"""
print(trendet.__author__)
print(trendet.__version__)
params = [
{
'stock': 'BBVA',
'country': 'Spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': ['A', 'B'],
'identify': 'both'
},
{
'stock': 'BBVA',
'country': 'Spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': None,
'identify': 'up',
},
{
'stock': 'BBVA',
'country': 'Spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': ['A', 'B'],
'identify': 'up',
},
{
'stock': 'BBVA',
'country': 'Spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': ['A', 'B'],
'identify': 'down',
},
{
'stock': 'BBVA',
'country': 'Spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': None,
'identify': 'down',
}
]
stocks = get_stocks_list(country='Spain')
for stock in stocks[:25]:
obj = {
'stock': stock,
'country': 'Spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 5,
'labels': None,
'identify': 'both',
}
params.append(obj)
for param in params:
trendet.identify_trends(stock=param['stock'],
country=param['country'],
from_date=param['from_date'],
to_date=param['to_date'],
window_size=param['window_size'],
trend_limit=param['trend_limit'],
labels=param['labels'],
identify=param['identify'])
trendet.identify_all_trends(stock=param['stock'],
country=param['country'],
from_date=param['from_date'],
to_date=param['to_date'],
window_size=param['window_size'],
identify=param['identify'])
df = get_stock_historical_data(stock='REP',
country='Spain',
from_date='01/01/2018',
to_date='01/01/2019')
params = [
{
'column': 'Close',
'window_size': 5,
'identify': 'both'
},
{
'column': 'Close',
'window_size': 5,
'identify': 'up'
},
{
'column': 'Close',
'window_size': 5,
'identify': 'down'
},
]
for param in params:
trendet.identify_df_trends(df=df,
column=param['column'],
window_size=param['window_size'],
identify=param['identify'])
def test_errors():
"""
This function raises trendet errors to improve coverage
"""
params = [
{
'equity': ['error'],
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': None,
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'error',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': None,
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'error',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': ['error'],
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': None,
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': None,
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2019',
'to_date': '01/01/2018',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01-2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '_01*01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 0,
'trend_limit': 3,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': -1,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': None,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': None,
'trend_limit': 1,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 'error',
'trend_limit': 1,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 1,
'trend_limit': 'error',
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 2,
'trend_limit': 5,
'labels': None,
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': ['a', 'b'],
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': 'error',
'identify': 'both',
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': ['error'],
},
{
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 3,
'labels': None,
'identify': 'error',
},
]
for param in params:
try:
trendet.identify_trends(equity=param['equity'],
country=param['country'],
from_date=param['from_date'],
to_date=param['to_date'],
window_size=param['window_size'],
trend_limit=param['trend_limit'],
labels=param['labels'],
identify=param['identify'])
except:
pass
try:
trendet.identify_all_trends(equity=param['equity'],
country=param['country'],
from_date=param['from_date'],
to_date=param['to_date'],
window_size=param['window_size'],
identify=param['identify'])
except:
pass
df = investpy.get_historical_data(equity='repsol',
country='spain',
from_date='01/01/2018',
to_date='01/01/2019')
df['str'] = 'error'
params = [
{
'df': None,
'column': 'Close',
'window_size': 5,
'identify': 'both'
},
{
'df': ['error'],
'column': 'Close',
'window_size': 5,
'identify': 'both'
},
{
'df': df,
'column': None,
'window_size': 5,
'identify': 'both'
},
{
'df': df,
'column': ['error'],
'window_size': 5,
'identify': 'both'
},
{
'df': df,
'column': 'error',
'window_size': 5,
'identify': 'both'
},
{
'df': df,
'column': 'str',
'window_size': 5,
'identify': 'both'
},
{
'df': df,
'column': 'Close',
'window_size': None,
'identify': 'both'
},
{
'df': df,
'column': 'Close',
'window_size': 1,
'identify': 'both'
},
{
'df': df,
'column': 'Close',
'window_size': 5,
'identify': ['error']
},
{
'df': df,
'column': 'Close',
'window_size': 5,
'identify': 'error'
},
]
for param in params:
try:
trendet.identify_df_trends(df=param['df'],
column=param['column'],
window_size=param['window_size'],
identify=param['identify'])
except:
pass
def test_trendet():
"""
This function checks that main functions of trendet work properly.
"""
author = trendet.__author__
print(author)
version = trendet.__version__
print(version)
equities = investpy.get_equities(country='spain')
equities = equities['name'].tolist()
params = list()
for equity in equities[:25]:
obj = {
'equity': equity,
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 5,
'labels': None,
'identify': 'both',
}
params.append(obj)
obj = {
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': ['A', 'B'],
'identify': 'both'
}
params.append(obj)
obj = {
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': None,
'identify': 'up',
}
params.append(obj)
obj = {
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': ['A', 'B'],
'identify': 'up',
}
params.append(obj)
obj = {
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': None,
'identify': 'down',
}
params.append(obj)
obj = {
'equity': 'bbva',
'country': 'spain',
'from_date': '01/01/2018',
'to_date': '01/01/2019',
'window_size': 5,
'trend_limit': 2,
'labels': ['A', 'B'],
'identify': 'down',
}
params.append(obj)
for param in params:
trendet.identify_trends(equity=param['equity'],
country=param['country'],
from_date=param['from_date'],
to_date=param['to_date'],
window_size=param['window_size'],
trend_limit=param['trend_limit'],
labels=param['labels'],
identify=param['identify'])
trendet.identify_all_trends(equity=param['equity'],
country=param['country'],
from_date=param['from_date'],
to_date=param['to_date'],
window_size=param['window_size'],
identify=param['identify'])
df = investpy.get_historical_data(equity='repsol',
country='spain',
from_date='01/01/2018',
to_date='01/01/2019')
params = [
{
'df': df,
'column': 'Close',
'window_size': 5,
'identify': 'both'
},
{
'df': df,
'column': 'Close',
'window_size': 5,
'identify': 'up'
},
{
'df': df,
'column': 'Close',
'window_size': 5,
'identify': 'down'
},
]
for param in params:
trendet.identify_df_trends(df=param['df'],
column=param['column'],
window_size=param['window_size'],
identify=param['identify'])