Source code for pyleecan.Methods.Output.Output.getter.get_fund_harm

# -*- coding: utf-8 -*-
from SciDataTool import VectorField
from .....Functions.Plot import fft_dict

[docs]def get_fund_harm(self, data): """Return the fundamental harmonic of the physical quantity in the data object Parameters ---------- self : Output an Output object data : Data a Data object Returns ------- fund_harm: dict Dict containing axis name as key and frequency/order/wavenumber of fundamental harmonic as value """ if data.symbol in ["B", "AGSF", "Is", "Phi_{wind}"]: # Init output dict fund_harm = dict() axes_list = data.get_axes() # Get machine pole pair number p = self.simu.machine.get_pole_pair_number() # Get electrical fundamental frequency f_elec = self.elec.OP.get_felec() # Loop on axes to express the fundamental harmonic of the Data object # including normalizations for axe in axes_list: # Init fundamental value to None for current axis coeff = None is_match = False # Search if the current axis in SciDataTool axis dictionary if in fft_dict.keys(): # If yes, find the axis name of the fft axe_fft = fft_dict[] is_match = True elif in fft_dict.values(): axe_fft = is_match = True if is_match: # Assign fundamental value depending on axis name if axe_fft == "freqs": coeff = f_elec axe_fft = "frequency" elif axe_fft == "wavenumber": coeff = p # Add in fund_harm dict the values with different normalizations if coeff is not None: # Assign fundamental value depending on physical quantity if data.symbol == "AGSF": coeff = 2 * coeff # Store value in dict fund_harm[axe_fft] = coeff # Add also normalizations in dict for key, norm in axe.normalizations.items(): fund_harm[key] = norm.normalize(fund_harm[axe_fft]) # Cannot calculate dict of fundamental harmonic values else: fund_harm = None return fund_harm