Ejemplo n.º 1
0
        def generate(region, year, temps, **kw):
            temps2 = self.weather_change(temps)
            result = np.nansum(curve(temps2)) / len(temps2)

            if diagnostic.is_recording():
                diagnostic.record(region, year, 'avgv', float(np.nansum(temps2)) / len(temps2))

            if not np.isnan(result):
                yield (year, result)

            if isinstance(curve, AdaptableCurve):
                curve.update(year, temps) # XXX: pass the original temps (labor decision, generalize?)
Ejemplo n.º 2
0
        def generate(region, year, temps, **kw):
            coeffs = self.getter(region, year, temps, curve)
            if len(temps) == len(coeffs):
                result = np.sum(self.weather_change(region, temps).dot(coeffs))
            else:
                raise RuntimeError("Unknown format for temps: " + str(temps.shape) + " <> len " + str(coeffs))

            if diagnostic.is_recording():
                for ii in range(temps.shape[0]):
                    diagnostic.record(region, year, 'var-' + str(ii), temps[ii])

            if not np.isnan(result):
                yield (year, result)

            if isinstance(curve, AdaptableCurve):
                curve.update(year, temps) # Passing in original (not weather-changed data)
Ejemplo n.º 3
0
        def generate(region, year, temps, **kw):
            temps = self.weather_change(temps)
            assert temps.shape[1] == len(curve.curr_curve.ccs), "%d <> %d" % (temps.shape[1], len(curve.curr_curve.ccs))
            #result = np.nansum(np.dot(temps, curve.curr_curve.ccs)) / len(temps)
            result = np.dot(np.sum(temps, axis=0), curve.curr_curve.ccs) / len(temps)

            if diagnostic.is_recording():
                sumtemps = np.sum(temps, axis=0) / len(temps)
                for ii in range(temps.shape[1]):
                    diagnostic.record(region, year, 'avgtk_' + str(ii+1), sumtemps[ii])

            if not np.isnan(result):
                yield (year, result)

            if isinstance(curve, AdaptableCurve):
                curve.update(year, temps)