integrate_loaded

	@timer

	def integrate_peak(self, peak_id, h, peak_std=_peak_std, bkgr_std=_bkgr_std, gap_std=1):

	def integrate_loaded(self, bins):

		for peak_id in range(self.npeaks):

			box_size = self.box_sizes[peak_id]

			if box_size is not None:

				binned_peak = self.bin_peak(peak_id, bins, hkl_box_size=box_size, smooth=False)

				points,_    = histogram_grid(binned_peak)

				peak_mask   = self.peak_funs[peak_id].is_inside_ellipsoid(std=_peak_std, x=points.reshape((-1,3))).reshape([bins]*3)

				bkgr_mask   = ~self.peak_funs[peak_id].is_inside_ellipsoid(std=_peak_std+_gap_std, x=points.reshape((-1,3))).reshape([bins]*3)

				valid_mask  = self.valid_masks[peak_id]

				I,sig = integrate_peak(binned_peak.getSignalArray(), peak_mask, bkgr_mask, valid_mask=valid_mask)

				self.peaks[peak_id].setIntensity(I)

				self.peaks[peak_id].setSigmaIntensity(sig)

		Is = [self.peaks[peak_id].getIntensity() for peak_id in range(self.npeaks)]

		Is = np.array(Is)

		peak_ids = self.peak_ids_by_mnp['0,0,0']

		# peak_ids = np.arange(self.npeaks)

		Is = Is[peak_ids]

		mI = self.peak_mantidI[peak_ids]

		ind = np.argsort(Is)

		plt.close('all')

		plt.semilogy(Is[ind])

		plt.semilogy(mI[ind])

		plt.show()

	@timer

	def integrate_peak(self, peak_id, h, peak_std=_peak_std, bkgr_std=_bkgr_std, gap_std=_gap_std):

		'''Integrate the peak

		Inputs