def preprocess_data(self, X, Y, dataTransform=None):
# Preprocess the variables X and Y
### First we transform everything to python format
X = ul.fnp(X)
Y = ul.fnp(Y)
# Whe can plot several Y over same X. So NcY >= 1, NcX = 0,1
NpX, NcX = X.shape
NpY, NcY = Y.shape
if (X.size == 0): # If the X given is empty
if (Y.size == 0): # If we are also given an empty Y
Y = ul.fnp([])
else:
X = ul.fnp(range(NpY)) # Create X axis with sample values
self.X = X
self.Y = Y
# Get the automatic formatting of the X and Y axes !!
# If we are given values to X, these could be of 3 types:
# - Numerical: Then we do nothing
# - String: Then it is categorical and we set the ticklabels to it
# - Datetimes: We set the formatter ?
self.formatXaxis = detect_AxisFormat(X)
self.formatYaxis = detect_AxisFormat(Y)
# print X,Y, self.formatXaxis, self.formatYaxis
if (type(dataTransform) != type(None)):
if (dataTransform[0] == "intraday"):
# In this case we are going to need to transform the dates.
openhour = dataTransform[1]
closehour = dataTransform[2]
self.formatXaxis = "intraday"
# Virtual transformation of the dates !
self.Xcategories = self.X
transfomedTimes = ul.transformDatesOpenHours(
X, openhour, closehour)
Mydetransfromdata = ul.deformatter_data(openhour, closehour, None)
# Setting the static object of the function
ul.detransformer_Formatter.format_data = Mydetransfromdata
self.X = ul.fnp(transfomedTimes)
if (self.formatXaxis == "categorical"
): # Transform to numbers and later we retransform
self.Xcategories = self.X
self.X = ul.fnp(range(NpX))
if (self.formatYaxis == "categorical"
): # Transform to numbers and later we retransform
self.Ycategories = self.Y
self.Y = ul.fnp(range(NpY))
# if (self.formatXaxis == "dates"): # Transform to numbers and later we retransform
# self.Xcategories = self.X
# self.X = ul.preprocess_dates(range(NpX))
return self.X, self.Y
if (tranformIntraday):
dataTransform = ["intraday", opentime, closetime]
else:
dataTransform = None
## If the timspan is daily or bigger do not transform time.
if (periods[0] >= 1440):
dataTransform = None
# This is how we would obtain the info if we did not use tradingPlot functions
price = timeData.get_timeSeries(["Close"])
volume = timeData.get_timeSeries(["Volume"])
dates = timeData.get_dates()
if (0):
## Try out time mapping func
caca = ul.transformDatesOpenHours(dates, opentime, closetime)
s***n = ul.detransformDatesOpenHours(caca, opentime, closetime)
s***n = pd.to_datetime(s***n)
for i in range(s***n.size):
diff_sec = (s***n[i] - dates[i]).total_seconds()
print(s***n[i], dates[i])
if (diff_sec != 0):
print(diff_sec / 3600)
# Get indicators for the price and volume
nMA1 = 15
EMA_price = timeData.EMA(seriesNames=["Close"], n=nMA1)
SMA_volume = timeData.EMA(seriesNames=["Volume"], n=nMA1)
ax1 = gl.subplot2grid((4, 1), (0, 0), rowspan=3, colspan=1)
if (typeChart == "Line"):