How to use the treecorr.util function in TreeCorr

with assert_raises(ValueError):
        treecorr.util.gen_write(file_name, ['a', 'b'], [a, b], file_type='Invalid')

    with assert_raises(ValueError):
        treecorr.util.gen_read(file_name, file_type='Invalid')

    # Now some places that do sanity checks for invalid coords or metrics which would already
    # be checked in normal operation.
    with assert_raises(ValueError):
        treecorr.util.parse_metric('Euclidean', 'invalid')
    with assert_raises(ValueError):
        treecorr.util.parse_metric('Invalid', 'flat')
    with assert_raises(ValueError):
        treecorr.util.coord_enum('invalid')
    with assert_raises(ValueError):
        treecorr.util.metric_enum('Invalid')

def test_util():
    # Test some error handling in utility functions that shouldn't be possible to get to
    # in normal running, so we need to call things explicitly to get the coverage.

    # First some I/O sanity checks
    a = np.array([1,2,3])
    b = np.array([4,5,6])
    file_name = 'junk.out'
    with assert_raises(ValueError):
        treecorr.util.gen_write(file_name, ['a', 'b'], [a])
    with assert_raises(ValueError):
        treecorr.util.gen_write(file_name, ['a', 'b'], [a, b, a])
    with assert_raises(ValueError):
        treecorr.util.gen_write(file_name, ['a'], [a, b])
    with assert_raises(ValueError):
        treecorr.util.gen_write(file_name, [], [])
    with assert_raises(ValueError):
        treecorr.util.gen_write(file_name, ['a', 'b'], [a, b[:1]])
    with assert_raises(ValueError):
        treecorr.util.gen_write(file_name, ['a', 'b'], [a, b], file_type='Invalid')

    with assert_raises(ValueError):
        treecorr.util.gen_read(file_name, file_type='Invalid')

    # Now some places that do sanity checks for invalid coords or metrics which would already
    # be checked in normal operation.

col_names = ['RA', 'DEC']
        cols = [info_data[n] for n in col_names]  # These come from wlinfo
        col_names += ['E_1', 'E_2', 'W']
        cols += [ngmix_data[n] for n in col_names[2:]]  # These are in ngmix

        # combine the two sensitivity estimates
        col_names += ['SENS']
        cols += [(ngmix_data['SENS_1'] + ngmix_data['SENS_2'])/2.]

        # Save time by cutting to only flag != 0 objects here.
        use = info_data['NGMIX_FLAG'] == 0
        print('total number of galaxies = ',len(use))
        print('number to use = ',np.sum(use))
        cols = [col[use] for col in cols]
        print('writing merged file: ',source_file)
        treecorr.util.gen_write(source_file, col_names, cols, file_type='FITS')

    return source_file, lens_file

col_names = [ 'r_nom', 'u_nom', 'v_nom',
                      'meand1', 'meanlogd1', 'meand2', 'meanlogd2',
                      'meand3', 'meanlogd3', 'meanu', 'meanv',
                      'zeta', 'sigma_zeta', 'weight', 'ntri' ]
        columns = [ self.rnom, self.u, self.v,
                    self.meand1, self.meanlogd1, self.meand2, self.meanlogd2,
                    self.meand3, self.meanlogd3, self.meanu, self.meanv,
                    self.zeta, np.sqrt(self.varzeta), self.weight, self.ntri ]

        params = { 'coords' : self.coords, 'metric' : self.metric,
                   'sep_units' : self.sep_units, 'bin_type' : self.bin_type }

        if precision is None:
            precision = self.config.get('precision', 4)

        treecorr.util.gen_write(
            file_name, col_names, columns,
            params=params, precision=precision, file_type=file_type, logger=self.logger)

if coords != self.coords:
                self.logger.warning("Detected a change in catalog coordinate systems.\n"+
                                    "This probably doesn't make sense!")
            if metric != self.metric:
                self.logger.warning("Detected a change in metric.\n"+
                                    "This probably doesn't make sense!")
        if metric == 'Periodic':
            if self.xperiod == 0 or self.yperiod == 0 or (coords=='3d' and self.zperiod == 0):
                raise ValueError("Periodic metric requires setting the period to use.")
        else:
            if self.xperiod != 0 or self.yperiod != 0 or self.zperiod != 0:
                raise ValueError("period options are not valid for %s metric."%metric)
        self.coords = coords  # These are the regular string values
        self.metric = metric
        self._coords = treecorr.util.coord_enum(coords)  # These are the C++-layer enums
        self._metric = treecorr.util.metric_enum(metric)

if drr is not None:
                col_names += ['DRR','RDR','RRD','DDR','DRD','RDD']
                columns += [ drr.weight * (self.tot/drr.tot), rdr.weight * (self.tot/rdr.tot),
                             rrd.weight * (self.tot/rrd.tot), ddr.weight * (self.tot/ddr.tot),
                             drd.weight * (self.tot/drd.tot), rdd.weight * (self.tot/rdd.tot) ]
            col_names += [ 'ntri' ]
            columns += [ self.ntri ]

        if precision is None:
            precision = self.config.get('precision', 4)

        params = { 'tot' : self.tot, 'coords' : self.coords, 'metric' : self.metric,
                   'sep_units' : self.sep_units, 'bin_type' : self.bin_type }

        treecorr.util.gen_write(
            file_name, col_names, columns,
            params=params, precision=precision, file_type=file_type, logger=self.logger)

is no loss of information.

        .. warning::

            The `NKCorrelation` object should be constructed with the same configuration
            parameters as the one being read.  e.g. the same min_sep, max_sep, etc.  This is not
            checked by the read function.

        Parameters:
            file_name (str):    The name of the file to read in.
            file_type (str):    The type of file ('ASCII' or 'FITS').  (default: determine the type
                                automatically from the extension of file_name.)
        """
        self.logger.info('Reading NK correlations from %s',file_name)

        data, params = treecorr.util.gen_read(file_name, file_type=file_type, logger=self.logger)
        if 'R_nom' in data.dtype.names:  # pragma: no cover
            self.rnom = data['R_nom']
            self.meanr = data['meanR']
            self.meanlogr = data['meanlogR']
        else:
            self.rnom = data['r_nom']
            self.meanr = data['meanr']
            self.meanlogr = data['meanlogr']
        self.logr = np.log(self.rnom)
        self.xi = data['kappa']
        self.varxi = data['sigma']**2
        self.weight = data['weight']
        self.npairs = data['npairs']
        self.coords = params['coords'].strip()
        self.metric = params['metric'].strip()
        self.sep_units = params['sep_units'].strip()

def _set_metric(self, metric, coords1, coords2=None, coords3=None):
        if metric is None:
            metric = treecorr.config.get(self.config,'metric',str,'Euclidean')
        coords, metric = treecorr.util.parse_metric(metric, coords1, coords2, coords3)
        if self.coords != None or self.metric != None:
            if coords != self.coords:
                self.logger.warning("Detected a change in catalog coordinate systems. "+
                                    "This probably doesn't make sense!")
            if metric != self.metric:
                self.logger.warning("Detected a change in metric. "+
                                    "This probably doesn't make sense!")
        if metric == 'Periodic':
            if self.xperiod == 0 or self.yperiod == 0 or (coords=='3d' and self.zperiod == 0):
                raise ValueError("Periodic metric requires setting the period to use.")
        else:
            if self.xperiod != 0 or self.yperiod != 0 or self.zperiod != 0:
                raise ValueError("period options are not valid for %s metric."%metric)
        self.coords = coords
        self.metric = metric
        self._coords = treecorr.util.coord_enum(coords)

is no loss of information.

        .. warning::

            The `NNCorrelation` object should be constructed with the same configuration
            parameters as the one being read.  e.g. the same min_sep, max_sep, etc.  This is not
            checked by the read function.

        Parameters:
            file_name (str):   The name of the file to read in.
            file_type (str):   The type of file ('ASCII' or 'FITS').  (default: determine the type
                                automatically from the extension of file_name.)
        """
        self.logger.info('Reading NN correlations from %s',file_name)

        data, params = treecorr.util.gen_read(file_name, file_type=file_type, logger=self.logger)
        if 'R_nom' in data.dtype.names:  # pragma: no cover
            self.rnom = data['R_nom']
            self.meanr = data['meanR']
            self.meanlogr = data['meanlogR']
        else:
            self.rnom = data['r_nom']
            self.meanr = data['meanr']
            self.meanlogr = data['meanlogr']
        self.logr = np.log(self.rnom)
        self.weight = data['DD']
        self.npairs = data['npairs']
        self.tot = params['tot']
        self.coords = params['coords'].strip()
        self.metric = params['metric'].strip()
        self.sep_units = params['sep_units'].strip()
        self.bin_type = params['bin_type'].strip()

if self.coords != None or self.metric != None:
            if coords != self.coords:
                self.logger.warning("Detected a change in catalog coordinate systems.\n"+
                                    "This probably doesn't make sense!")
            if metric != self.metric:
                self.logger.warning("Detected a change in metric.\n"+
                                    "This probably doesn't make sense!")
        if metric == 'Periodic':
            if self.xperiod == 0 or self.yperiod == 0 or (coords=='3d' and self.zperiod == 0):
                raise ValueError("Periodic metric requires setting the period to use.")
        else:
            if self.xperiod != 0 or self.yperiod != 0 or self.zperiod != 0:
                raise ValueError("period options are not valid for %s metric."%metric)
        self.coords = coords  # These are the regular string values
        self.metric = metric
        self._coords = treecorr.util.coord_enum(coords)  # These are the C++-layer enums
        self._metric = treecorr.util.metric_enum(metric)