def temp_monthly():
prev_year = dt.date(2017, 8, 23) - dt.timedelta(days=365)
results = session.query(Measurement.tobs).\
filter(Measurement.station == 'USC00519281').\
filter(Measurement.date >= prev_year).all()
temps = list(np.unravel(results))
return jsonify(temps=temps)
def stations:
session = Session(engine)
q = session.query(Station.name)
session.close()
stations = list(np.unravel(q))
return jsonify(stations)
def two_profile_fitting(self, img, peaks, n1, n2):
xy1 = self.peaks.peaks[n1].getDetxy()
xy2 = self.peaks.peaks[n2].getDetxy()
dxy = np.subtract(xy1, xy2)
sub0 = self.getZoomIm(xy1, n1, n2)
sub1 = self.getZoomIm(xy2, n1, n2)
j1 = np.argmax(sub0)
j2 = np.argmax(sub1)
j1ind = np.unravel_index(j1, self.imArray.shape)
j2ind = np.unravel_index(j2, self.imArray.shape)
xy1 = xy1 + j1ind - [2, 2]
xy2 = xy2 + j2ind - [2, 2]
# recenter one more time
sub0 = self.getZoomIm(xy1, n1, n2)
sub1 = self.getZoomIm(xy2, n1, n2)
j1 = np.argmax(sub0)
j2 = np.argmax(sub1)
j1ind = np.unravel(j1, self.imArray.shape)
j2ind = np.unravel(j2, self.imArray.shape)
xy1 = xy1 + j1ind - [2, 2]
xy2 = xy2 + j2ind - [2, 2]
self.peaks.peaks[n1].setDetxy(xy1)
self.peaks.peaks[n2].setDetxy(xy2)
dx2 = np.subtract(xy1, xy2)
middle = (xy1 + xy2) / 2.
d = xy1 - middle
d = sqrt(d[0]**2 + d[1]**2)
xr1 = xy1 - middle
xr2 = xy2 - middle
pic = self.getZoomIm(middle, [d, d])
####
####
# needs testing....
# and then deployment
aaa = self.two2DGaussians(pic, xr1, xr2)