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	generalized read_mesons, added ylabel to Corr.show
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					 2 changed files with 8 additions and 3 deletions
				
			
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			@ -293,7 +293,7 @@ class Corr:
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    #quick and dirty plotting function to view Correlator inside Jupyter
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    #If one would not want to import pyplot, this could easily be replaced by a call to pe.plot_corrs
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    #This might be a bit more flexible later
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    def show(self, x_range=None, comp=None, logscale=False, plateau=None, fit_res=None, save=None):
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    def show(self, x_range=None, comp=None, logscale=False, plateau=None, fit_res=None, save=None, ylabel=None):
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        """Plots the correlator, uses tag as label if available.
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        Parameters
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			@ -345,6 +345,8 @@ class Corr:
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                    , ls='-', marker=',', lw=2)
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        ax1.set_xlabel(r'$x_0 / a$')
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        if ylabel:
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            ax1.set_ylabel(ylabel)
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        ax1.set_xlim([x_range[0] - 0.5, x_range[1] + 0.5])
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        handles, labels = ax1.get_legend_handles_labels()
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			@ -7,7 +7,7 @@ import numpy as np
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from ..pyerrors import Obs
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from ..correlators import Corr
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def read_meson_hd5(path, filestem, ens_id, meson='meson_0'):
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def read_meson_hd5(path, filestem, ens_id, meson='meson_0', tree='meson'):
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    """Read hadrons meson hdf5 file and extract the meson labeled 'meson'
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    Parameters
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			@ -28,6 +28,9 @@ def read_meson_hd5(path, filestem, ens_id, meson='meson_0'):
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        if l.startswith(filestem):
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            files.append(l)
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    if not files:
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        raise Exception('No files starting with', filestem, 'in folder', path)
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    # Sort according to configuration number
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    get_cnfg_number = lambda x : int(x[len(filestem) + 1:-3])
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    files.sort(key=get_cnfg_number)
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			@ -44,7 +47,7 @@ def read_meson_hd5(path, filestem, ens_id, meson='meson_0'):
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    for hd5_file in files:
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        file = h5py.File(path + '/' + hd5_file, "r")
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        raw_data = list(file['meson/' + meson + '/corr'])
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        raw_data = list(file[tree + '/' + meson + '/corr'])
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        real_data = [o[0] for o in raw_data]
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        corr_data.append(real_data)
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    corr_data = np.array(corr_data)
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