def get_focus(self, filt=False, samples=None, subset=None, nominal=False):
        """
        Collect all data from all samples into a single array.
        Data from standards is not collected.

        Parameters
        ----------
        filt : str, dict or bool
            Either logical filter expression contained in a str,
            a dict of expressions specifying the filter string to
            use for each analyte or a boolean. Passed to `grab_filt`.
        samples : str or list
            which samples to get
        subset : str or int
            which subset to get

        Returns
        -------
        None
        """

        if samples is not None:
            subset = self.make_subset(samples)
        
        samples = self._get_samples(subset)

        # t = 0
        focus = {'uTime': []}
        focus.update({a: [] for a in self.analytes})

        for sa in samples:
            s = self.data[sa]
            focus['uTime'].append(s.uTime)
            ind = s.filt.grab_filt(filt)
            for a in self.analytes:
                tmp = s.focus[a].copy()
                tmp[~ind] = np.nan
                focus[a].append(tmp)

        if nominal:
            self.focus.update({k: nominal_values(np.concatenate(v)) for k, v, in focus.items()})
        else:
            self.focus.update({k: np.concatenate(v) for k, v, in focus.items()})

        return
def get_focus(self, filt=False, samples=None, subset=None, nominal=False):
        """
        Collect all data from all samples into a single array.
        Data from standards is not collected.

        Parameters
        ----------
        filt : str, dict or bool
            Either logical filter expression contained in a str,
            a dict of expressions specifying the filter string to
            use for each analyte or a boolean. Passed to `grab_filt`.
        samples : str or list
            which samples to get
        subset : str or int
            which subset to get

        Returns
        -------
        None
        """

        if samples is not None:
            subset = self.make_subset(samples)
        
        samples = self._get_samples(subset)

        # t = 0
        focus = {'uTime': []}
        focus.update({a: [] for a in self.analytes})

        for sa in samples:
            s = self.data[sa]
            focus['uTime'].append(s.uTime)
            ind = s.filt.grab_filt(filt)
            for a in self.analytes:
                tmp = s.focus[a].copy()
                tmp[~ind] = np.nan
                focus[a].append(tmp)

        if nominal:
            self.focus.update({k: nominal_values(np.concatenate(v)) for k, v, in focus.items()})
        else:
            self.focus.update({k: np.concatenate(v) for k, v, in focus.items()})

        return
def get_focus ( self , filt = False , samples = None , subset = None , nominal = False ) : if samples is not None : subset = self . make_subset ( samples ) samples = self . _get_samples ( subset ) # t = 0 focus = { 'uTime' : [ ] } focus . update ( { a : [ ] for a in self . analytes } ) for sa in samples : s = self . data [ sa ] focus [ 'uTime' ] . append ( s . uTime ) ind = s . filt . grab_filt ( filt ) for a in self . analytes : tmp = s . focus [ a ] . copy ( ) tmp [ ~ ind ] = np . nan focus [ a ] . append ( tmp ) if nominal : self . focus . update ( { k : nominal_values ( np . concatenate ( v ) ) for k , v , in focus . items ( ) } ) else : self . focus . update ( { k : np . concatenate ( v ) for k , v , in focus . items ( ) } ) return
Collect all data from all samples into a single array.
        Data from standards is not collected.

        Parameters
        ----------
        filt : str, dict or bool
            Either logical filter expression contained in a str,
            a dict of expressions specifying the filter string to
            use for each analyte or a boolean. Passed to `grab_filt`.
        samples : str or list
            which samples to get
        subset : str or int
            which subset to get

        Returns
        -------
        None
Collect all data from all samples into a single array . Data from standards is not collected .