def get_standard_input_data(df):
if df is None:
raise ValueError("Error: Dataframe has not been provided, there is no data to calculate the requested KPI")
input_data = {}
# Set dataFrame keys
adj_close_key = Constants.get_adj_close_key()
close_key = Constants.get_close_key()
if adj_close_key in df.columns is True:
prices_key = adj_close_key
else:
prices_key = close_key
prices_temp = pd.DataFrame()
#TODO: Create a utilities class
df.columns = pd.MultiIndex.from_tuples(df.columns.values)
tickers = df.columns.levels[0]
df_list = []
for ticker in tickers:
df_list.append(
pd.concat(
[df[ticker].loc[:, [prices_key]], prices_temp],
axis=1,
keys=[ticker]
)
)
input_df =\
pd.concat(
df_list,
axis=1
)
input_data[Constants.get_prices_key()] = prices_key
input_data[Constants.get_tickers_key()] = tickers
input_data[Constants.get_input_df_key()] = input_df
return input_data
def plot_stock(self, stock, tickers=None, collapse_indicators=False):
Plotter.legend_id = 0
Plotter.current_color_indicator = 0
if stock is None:
print("There is no ticker Information, nothing to be plot")
return
if tickers is None:
tickers = stock.tickers
elif isinstance(tickers, list) is True:
tickers = tickers
else:
tickers = [tickers]
if self.fig is None or self.axes_main is None or self.axes_indicators is None:
if stock.price_info is None or stock.price_info[tickers].empty:
raise ValueError(
"There is no price information for this stock")
adj_close_key = Constants.get_adj_close_key()
volume_key = Constants.get_volume_key()
self.price_series = {}
self.volume_series = {}
self.x_series = {}
for ticker in tickers:
if (adj_close_key in stock.price_info[ticker]) == False:
adj_close_key = Constants.get_close_key()
self.x_series[ticker] = stock.price_info[ticker].iloc[
-self.period:, :].index
self.price_series[ticker] = stock.price_info[ticker].iloc[
-self.period:, :][adj_close_key]
self.volume_series[ticker] = stock.price_info[ticker].iloc[
-self.period:, :][volume_key]
self.axes_main = dict()
self.axes_indicators = dict()
if len(stock.indicators) == 0:
subplots = 1
elif len(stock.indicators) > 0 and collapse_indicators is True:
extra = len(
list(
filter(
lambda x: x.collapse is False or x.in_main_plot
is False, stock.indicators)))
no_collapse = len(
list(
filter(
lambda x: x.collapse is False and x.
in_main_plot is False, stock.indicators)))
if no_collapse > 0:
no_collapse = no_collapse - 1
fixed = 2
if extra == 0:
fixed = 1
subplots = fixed + no_collapse
else:
subplots = len(
list(
filter(lambda x: x.in_main_plot is False,
stock.indicators))) + 1
heights_list = [2 for i in range(subplots - 1)]
if subplots == 1:
heights_list.insert(0, 2)
else:
heights_list.insert(0, 3)
self.fig = plt.figure(figsize=(8, 6), dpi=80)
gridspec = self.fig.add_gridspec(ncols=1,
nrows=subplots,
height_ratios=heights_list)
# gridspec_kw = {'height_ratios': heights_list}
self.axes_main[Constants.volume_axis] = self.fig.add_subplot(
gridspec[0, 0])
self.set_volume(ticker=ticker)
self.set_stock_price(ticker=ticker, color=self.stock_color)
i = 1 # Indicator axis begins in 2
indicator_axis = None
Plotter.legend_id = 0
for indicator in stock.indicators:
if indicator.in_main_plot is False:
if collapse_indicators == True:
if i > 1:
if indicator.collapse is False:
self.axes_indicators = self.fig.add_subplot(
gridspec[i, 0])
indicator_axis = self.axes_indicators
else:
indicator_axis = indicator_axis.twinx()
else: # Executed first
self.axes_indicators = \
self.fig.add_subplot(
gridspec[i, 0],
sharex=self.axes_main[Constants.prices_axis])
indicator_axis = self.axes_indicators
else:
Plotter.legend_id = 0
sharex = None
if indicator.collapse is True:
sharex = self.axes_main[Constants.prices_axis]
self.axes_indicators = \
self.fig.add_subplot(
gridspec[i, 0],
sharex=sharex)
indicator_axis = self.axes_indicators
if indicator_axis is None:
indicator_axis = self.axes_indicators
i += 1
else:
indicator_axis = self.axes_main[Constants.prices_axis]
self.set_plot_indicator(indicator=indicator,
ticker=ticker,
axis=indicator_axis)
plt.tight_layout()