# pyerrors.input.json

View Source

    import json
    import gzip
    import getpass
    import socket
    import datetime
    import platform
    import warnings
    import re
    import gc
    import numpy as np
    from ..obs import Obs
    from ..covobs import Covobs
    from ..correlators import Corr
    from ..misc import _assert_equal_properties
    from .. import version as pyerrorsversion

    def create_json_string(ol, description='', indent=1):
        """Generate the string for the export of a list of Obs or structures containing Obs
        to a .json(.gz) file

        Parameters
        ----------
        ol : list
            List of objects that will be exported. At the moment, these objects can be
            either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        description : str
            Optional string that describes the contents of the json file.
        indent : int
            Specify the indentation level of the json file. None or 0 is permissible and
            saves disk space.
        """

        def _default(self, obj):
            return str(obj)
        my_encoder = json.JSONEncoder
        _default.default = json.JSONEncoder().default
        my_encoder.default = _default

        class Deltalist:
            __slots__ = ['cnfg', 'deltas']

            def __init__(self, li):
                self.cnfg = li[0]
                self.deltas = li[1:]

            def __repr__(self):
                s = '[%d' % (self.cnfg)
                for d in self.deltas:
                    s += ', %1.15e' % (d)
                s += ']'
                return s

            def __str__(self):
                return self.__repr__()

        class Floatlist:
            __slots__ = ['li']

            def __init__(self, li):
                self.li = list(li)

            def __repr__(self):
                s = '['
                for i in range(len(self.li)):
                    if i > 0:
                        s += ', '
                    s += '%1.15e' % (self.li[i])
                s += ']'
                return s

            def __str__(self):
                return self.__repr__()

        def _gen_data_d_from_list(ol):
            dl = []
            for name in ol[0].mc_names:
                ed = {}
                ed['id'] = name
                ed['replica'] = []
                for r_name in ol[0].e_content[name]:
                    rd = {}
                    rd['name'] = r_name
                    if ol[0].is_merged.get(r_name, False):
                        rd['is_merged'] = True
                    rd['deltas'] = []
                    for i in range(len(ol[0].idl[r_name])):
                        rd['deltas'].append([ol[0].idl[r_name][i]])
                        for o in ol:
                            rd['deltas'][-1].append(o.deltas[r_name][i])
                        rd['deltas'][-1] = Deltalist(rd['deltas'][-1])
                    ed['replica'].append(rd)
                dl.append(ed)
            return dl

        def _gen_cdata_d_from_list(ol):
            dl = []
            for name in ol[0].cov_names:
                ed = {}
                ed['id'] = name
                ed['layout'] = str(ol[0].covobs[name].cov.shape).lstrip('(').rstrip(')').rstrip(',')
                ed['cov'] = Floatlist(np.ravel(ol[0].covobs[name].cov))
                ncov = ol[0].covobs[name].cov.shape[0]
                ed['grad'] = []
                for i in range(ncov):
                    ed['grad'].append([])
                    for o in ol:
                        ed['grad'][-1].append(o.covobs[name].grad[i][0])
                    ed['grad'][-1] = Floatlist(ed['grad'][-1])
                dl.append(ed)
            return dl

        def write_Obs_to_dict(o):
            d = {}
            d['type'] = 'Obs'
            d['layout'] = '1'
            if o.tag:
                d['tag'] = [o.tag]
            if o.reweighted:
                d['reweighted'] = o.reweighted
            d['value'] = [o.value]
            data = _gen_data_d_from_list([o])
            if len(data) > 0:
                d['data'] = data
            cdata = _gen_cdata_d_from_list([o])
            if len(cdata) > 0:
                d['cdata'] = cdata
            return d

        def write_List_to_dict(ol):
            _assert_equal_properties(ol)
            d = {}
            d['type'] = 'List'
            d['layout'] = '%d' % len(ol)
            taglist = [o.tag for o in ol]
            if np.any([tag is not None for tag in taglist]):
                d['tag'] = taglist
            if ol[0].reweighted:
                d['reweighted'] = ol[0].reweighted
            d['value'] = [o.value for o in ol]
            data = _gen_data_d_from_list(ol)
            if len(data) > 0:
                d['data'] = data
            cdata = _gen_cdata_d_from_list(ol)
            if len(cdata) > 0:
                d['cdata'] = cdata
            return d

        def write_Array_to_dict(oa):
            ol = np.ravel(oa)
            _assert_equal_properties(ol)
            d = {}
            d['type'] = 'Array'
            d['layout'] = str(oa.shape).lstrip('(').rstrip(')').rstrip(',')
            taglist = [o.tag for o in ol]
            if np.any([tag is not None for tag in taglist]):
                d['tag'] = taglist
            if ol[0].reweighted:
                d['reweighted'] = ol[0].reweighted
            d['value'] = [o.value for o in ol]
            data = _gen_data_d_from_list(ol)
            if len(data) > 0:
                d['data'] = data
            cdata = _gen_cdata_d_from_list(ol)
            if len(cdata) > 0:
                d['cdata'] = cdata
            return d

        def _nan_Obs_like(obs):
            samples = []
            names = []
            idl = []
            for key, value in obs.idl.items():
                samples.append([np.nan] * len(value))
                names.append(key)
                idl.append(value)
            my_obs = Obs(samples, names, idl)
            my_obs._covobs = obs._covobs
            for name in obs._covobs:
                my_obs.names.append(name)
            my_obs.reweighted = obs.reweighted
            my_obs.is_merged = obs.is_merged
            return my_obs

        def write_Corr_to_dict(my_corr):
            first_not_none = next(i for i, j in enumerate(my_corr.content) if np.all(j))
            dummy_array = np.empty((my_corr.N, my_corr.N), dtype=object)
            dummy_array[:] = _nan_Obs_like(my_corr.content[first_not_none].ravel()[0])
            content = [o if o is not None else dummy_array for o in my_corr.content]
            dat = write_Array_to_dict(np.array(content, dtype=object))
            dat['type'] = 'Corr'
            corr_meta_data = str(my_corr.tag)
            if 'tag' in dat.keys():
                dat['tag'].append(corr_meta_data)
            else:
                dat['tag'] = [corr_meta_data]
            taglist = dat['tag']
            dat['tag'] = {}  # tag is now a dictionary, that contains the previous taglist in the key "tag"
            dat['tag']['tag'] = taglist
            if my_corr.prange is not None:
                dat['tag']['prange'] = my_corr.prange
            return dat

        if not isinstance(ol, list):
            ol = [ol]

        d = {}
        d['program'] = 'pyerrors %s' % (pyerrorsversion.__version__)
        d['version'] = '1.0'
        d['who'] = getpass.getuser()
        d['date'] = datetime.datetime.now().astimezone().strftime('%Y-%m-%d %H:%M:%S %z')
        d['host'] = socket.gethostname() + ', ' + platform.platform()

        if description:
            d['description'] = description
        d['obsdata'] = []
        for io in ol:
            if isinstance(io, Obs):
                d['obsdata'].append(write_Obs_to_dict(io))
            elif isinstance(io, list):
                d['obsdata'].append(write_List_to_dict(io))
            elif isinstance(io, np.ndarray):
                d['obsdata'].append(write_Array_to_dict(io))
            elif isinstance(io, Corr):
                d['obsdata'].append(write_Corr_to_dict(io))
            else:
                raise Exception("Unkown datatype.")

        jsonstring = ''
        for chunk in my_encoder(indent=indent, ensure_ascii=False).iterencode(d):
            jsonstring += chunk

        del d
        gc.collect()

        def remove_quotationmarks_split(split):
            """Workaround for un-quoting of delta lists, adds 5% of work
               but is save, compared to a simple replace that could destroy the structure
            """
            deltas = False
            for i in range(len(split)):
                if '"deltas":' in split[i] or '"cov":' in split[i] or '"grad":' in split[i]:
                    deltas = True
                if deltas:
                    split[i] = split[i].replace('"[', '[').replace(']"', ']')
                    if split[i][-1] == ']':
                        deltas = False
            return '\n'.join(split)

        jsonstring = jsonstring.split('\n')
        jsonstring = remove_quotationmarks_split(jsonstring)
        jsonstring = jsonstring.replace('nan', 'NaN')
        return jsonstring

    def dump_to_json(ol, fname, description='', indent=1, gz=True):
        """Export a list of Obs or structures containing Obs to a .json(.gz) file

        Parameters
        ----------
        ol : list
            List of objects that will be exported. At the moment, these objects can be
            either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        fname : str
            Filename of the output file.
        description : str
            Optional string that describes the contents of the json file.
        indent : int
            Specify the indentation level of the json file. None or 0 is permissible and
            saves disk space.
        gz : bool
            If True, the output is a gzipped json. If False, the output is a json file.
        """

        jsonstring = create_json_string(ol, description, indent)

        if not fname.endswith('.json') and not fname.endswith('.gz'):
            fname += '.json'

        if gz:
            if not fname.endswith('.gz'):
                fname += '.gz'

            fp = gzip.open(fname, 'wb')
            fp.write(jsonstring.encode('utf-8'))
        else:
            fp = open(fname, 'w', encoding='utf-8')
            fp.write(jsonstring)
        fp.close()

    def _parse_json_dict(json_dict, verbose=True, full_output=False):
        """Reconstruct a list of Obs or structures containing Obs from a dict that
        was built out of a json string.

        The following structures are supported: Obs, list, numpy.ndarray, Corr
        If the list contains only one element, it is unpacked from the list.

        Parameters
        ----------
        json_string : str
            json string containing the data.
        verbose : bool
            Print additional information that was written to the file.
        full_output : bool
            If True, a dict containing auxiliary information and the data is returned.
            If False, only the data is returned.
        """

        def _gen_obsd_from_datad(d):
            retd = {}
            if d:
                retd['names'] = []
                retd['idl'] = []
                retd['deltas'] = []
                retd['is_merged'] = {}
                for ens in d:
                    for rep in ens['replica']:
                        rep_name = rep['name']
                        if len(rep_name) > len(ens["id"]):
                            if rep_name[len(ens["id"])] != "|":
                                tmp_list = list(rep_name)
                                tmp_list = tmp_list[:len(ens["id"])] + ["|"] + tmp_list[len(ens["id"]):]
                                rep_name = ''.join(tmp_list)
                        retd['names'].append(rep_name)
                        retd['idl'].append([di[0] for di in rep['deltas']])
                        retd['deltas'].append(np.array([di[1:] for di in rep['deltas']]))
                        retd['is_merged'][rep_name] = rep.get('is_merged', False)
            return retd

        def _gen_covobsd_from_cdatad(d):
            retd = {}
            for ens in d:
                retl = []
                name = ens['id']
                layouts = ens.get('layout', '1').strip()
                layout = [int(ls.strip()) for ls in layouts.split(',') if len(ls) > 0]
                cov = np.reshape(ens['cov'], layout)
                grad = ens['grad']
                nobs = len(grad[0])
                for i in range(nobs):
                    retl.append({'name': name, 'cov': cov, 'grad': [g[i] for g in grad]})
                retd[name] = retl
            return retd

        def get_Obs_from_dict(o):
            layouts = o.get('layout', '1').strip()
            if layouts != '1':
                raise Exception("layout is %s has to be 1 for type Obs." % (layouts), RuntimeWarning)

            values = o['value']
            od = _gen_obsd_from_datad(o.get('data', {}))
            cd = _gen_covobsd_from_cdatad(o.get('cdata', {}))

            if od:
                ret = Obs([[ddi[0] + values[0] for ddi in di] for di in od['deltas']], od['names'], idl=od['idl'])
                ret.is_merged = od['is_merged']
            else:
                ret = Obs([], [])
                ret._value = values[0]
            for name in cd:
                co = cd[name][0]
                ret._covobs[name] = Covobs(None, co['cov'], co['name'], grad=co['grad'])
                ret.names.append(co['name'])

            ret.reweighted = o.get('reweighted', False)
            ret.tag = o.get('tag', [None])[0]
            return ret

        def get_List_from_dict(o):
            layouts = o.get('layout', '1').strip()
            layout = int(layouts)
            values = o['value']
            od = _gen_obsd_from_datad(o.get('data', {}))
            cd = _gen_covobsd_from_cdatad(o.get('cdata', {}))

            ret = []
            taglist = o.get('tag', layout * [None])
            for i in range(layout):
                if od:
                    ret.append(Obs([list(di[:, i] + values[i]) for di in od['deltas']], od['names'], idl=od['idl']))
                    ret[-1].is_merged = od['is_merged']
                else:
                    ret.append(Obs([], []))
                    ret[-1]._value = values[i]
                    print('Created Obs with means= ', values[i])
                for name in cd:
                    co = cd[name][i]
                    ret[-1]._covobs[name] = Covobs(None, co['cov'], co['name'], grad=co['grad'])
                    ret[-1].names.append(co['name'])

                ret[-1].reweighted = o.get('reweighted', False)
                ret[-1].tag = taglist[i]
            return ret

        def get_Array_from_dict(o):
            layouts = o.get('layout', '1').strip()
            layout = [int(ls.strip()) for ls in layouts.split(',') if len(ls) > 0]
            N = np.prod(layout)
            values = o['value']
            od = _gen_obsd_from_datad(o.get('data', {}))
            cd = _gen_covobsd_from_cdatad(o.get('cdata', {}))

            ret = []
            taglist = o.get('tag', N * [None])
            for i in range(N):
                if od:
                    ret.append(Obs([di[:, i] + values[i] for di in od['deltas']], od['names'], idl=od['idl']))
                    ret[-1].is_merged = od['is_merged']
                else:
                    ret.append(Obs([], []))
                    ret[-1]._value = values[i]
                for name in cd:
                    co = cd[name][i]
                    ret[-1]._covobs[name] = Covobs(None, co['cov'], co['name'], grad=co['grad'])
                    ret[-1].names.append(co['name'])
                ret[-1].reweighted = o.get('reweighted', False)
                ret[-1].tag = taglist[i]
            return np.reshape(ret, layout)

        def get_Corr_from_dict(o):
            if isinstance(o.get('tag'), list):  # supports the old way
                taglist = o.get('tag')  # This had to be modified to get the taglist from the dictionary
                temp_prange = None
            elif isinstance(o.get('tag'), dict):
                tagdic = o.get('tag')
                taglist = tagdic['tag']
                if 'prange' in tagdic:
                    temp_prange = tagdic['prange']
                else:
                    temp_prange = None
            else:
                raise Exception("The tag is not a list or dict")

            corr_tag = taglist[-1]
            tmp_o = o
            tmp_o['tag'] = taglist[:-1]
            if len(tmp_o['tag']) == 0:
                del tmp_o['tag']
            dat = get_Array_from_dict(tmp_o)
            my_corr = Corr([None if np.isnan(o.ravel()[0].value) else o for o in list(dat)])
            if corr_tag != 'None':
                my_corr.tag = corr_tag

            my_corr.prange = temp_prange
            return my_corr

        prog = json_dict.get('program', '')
        version = json_dict.get('version', '')
        who = json_dict.get('who', '')
        date = json_dict.get('date', '')
        host = json_dict.get('host', '')
        if prog and verbose:
            print('Data has been written using %s.' % (prog))
        if version and verbose:
            print('Format version %s' % (version))
        if np.any([who, date, host] and verbose):
            print('Written by %s on %s on host %s' % (who, date, host))
        description = json_dict.get('description', '')
        if description and verbose:
            print()
            print('Description: ', description)
        obsdata = json_dict['obsdata']
        ol = []
        for io in obsdata:
            if io['type'] == 'Obs':
                ol.append(get_Obs_from_dict(io))
            elif io['type'] == 'List':
                ol.append(get_List_from_dict(io))
            elif io['type'] == 'Array':
                ol.append(get_Array_from_dict(io))
            elif io['type'] == 'Corr':
                ol.append(get_Corr_from_dict(io))
            else:
                raise Exception("Unkown datatype.")

        if full_output:
            retd = {}
            retd['program'] = prog
            retd['version'] = version
            retd['who'] = who
            retd['date'] = date
            retd['host'] = host
            retd['description'] = description
            retd['obsdata'] = ol

            return retd
        else:
            if len(obsdata) == 1:
                ol = ol[0]

            return ol

    def import_json_string(json_string, verbose=True, full_output=False):
        """Reconstruct a list of Obs or structures containing Obs from a json string.

        The following structures are supported: Obs, list, numpy.ndarray, Corr
        If the list contains only one element, it is unpacked from the list.

        Parameters
        ----------
        json_string : str
            json string containing the data.
        verbose : bool
            Print additional information that was written to the file.
        full_output : bool
            If True, a dict containing auxiliary information and the data is returned.
            If False, only the data is returned.
        """

        return _parse_json_dict(json.loads(json_string), verbose, full_output)

    def load_json(fname, verbose=True, gz=True, full_output=False):
        """Import a list of Obs or structures containing Obs from a .json(.gz) file.

        The following structures are supported: Obs, list, numpy.ndarray, Corr
        If the list contains only one element, it is unpacked from the list.

        Parameters
        ----------
        fname : str
            Filename of the input file.
        verbose : bool
            Print additional information that was written to the file.
        gz : bool
            If True, assumes that data is gzipped. If False, assumes JSON file.
        full_output : bool
            If True, a dict containing auxiliary information and the data is returned.
            If False, only the data is returned.
        """
        if not fname.endswith('.json') and not fname.endswith('.gz'):
            fname += '.json'
        if gz:
            if not fname.endswith('.gz'):
                fname += '.gz'
            with gzip.open(fname, 'r') as fin:
                d = json.load(fin)
        else:
            if fname.endswith('.gz'):
                warnings.warn("Trying to read from %s without unzipping!" % fname, UserWarning)
            with open(fname, 'r', encoding='utf-8') as fin:
                d = json.loads(fin.read())

        return _parse_json_dict(d, verbose, full_output)

    def _ol_from_dict(ind, reps='DICTOBS'):
        """Convert a dictionary of Obs objects to a list and a dictionary that contains
        placeholders instead of the Obs objects.

        Parameters
        ----------
        ind : dict
            Dict of JSON valid structures and objects that will be exported.
            At the moment, these object can be either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        reps : str
            Specify the structure of the placeholder in exported dict to be reps[0-9]+.
        """

        obstypes = (Obs, Corr, np.ndarray)

        if not reps.isalnum():
            raise Exception('Placeholder string has to be alphanumeric!')
        ol = []
        counter = 0

        def dict_replace_obs(d):
            nonlocal ol
            nonlocal counter
            x = {}
            for k, v in d.items():
                if isinstance(v, dict):
                    v = dict_replace_obs(v)
                elif isinstance(v, list) and all([isinstance(o, Obs) for o in v]):
                    v = obslist_replace_obs(v)
                elif isinstance(v, list):
                    v = list_replace_obs(v)
                elif isinstance(v, obstypes):
                    ol.append(v)
                    v = reps + '%d' % (counter)
                    counter += 1
                elif isinstance(v, str):
                    if bool(re.match(r'%s[0-9]+' % (reps), v)):
                        raise Exception('Dict contains string %s that matches the placeholder! %s Cannot be savely exported.' % (v, reps))
                x[k] = v
            return x

        def list_replace_obs(li):
            nonlocal ol
            nonlocal counter
            x = []
            for e in li:
                if isinstance(e, list):
                    e = list_replace_obs(e)
                elif isinstance(e, list) and all([isinstance(o, Obs) for o in e]):
                    e = obslist_replace_obs(e)
                elif isinstance(e, dict):
                    e = dict_replace_obs(e)
                elif isinstance(e, obstypes):
                    ol.append(e)
                    e = reps + '%d' % (counter)
                    counter += 1
                elif isinstance(e, str):
                    if bool(re.match(r'%s[0-9]+' % (reps), e)):
                        raise Exception('Dict contains string %s that matches the placeholder! %s Cannot be savely exported.' % (e, reps))
                x.append(e)
            return x

        def obslist_replace_obs(li):
            nonlocal ol
            nonlocal counter
            il = []
            for e in li:
                il.append(e)

            ol.append(il)
            x = reps + '%d' % (counter)
            counter += 1
            return x

        nd = dict_replace_obs(ind)

        return ol, nd

    def dump_dict_to_json(od, fname, description='', indent=1, reps='DICTOBS', gz=True):
        """Export a dict of Obs or structures containing Obs to a .json(.gz) file

        Parameters
        ----------
        od : dict
            Dict of JSON valid structures and objects that will be exported.
            At the moment, these objects can be either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        fname : str
            Filename of the output file.
        description : str
            Optional string that describes the contents of the json file.
        indent : int
            Specify the indentation level of the json file. None or 0 is permissible and
            saves disk space.
        reps : str
            Specify the structure of the placeholder in exported dict to be reps[0-9]+.
        gz : bool
            If True, the output is a gzipped json. If False, the output is a json file.
        """

        if not isinstance(od, dict):
            raise Exception('od has to be a dictionary. Did you want to use dump_to_json?')

        infostring = ('This JSON file contains a python dictionary that has been parsed to a list of structures. '
                      'OBSDICT contains the dictionary, where Obs or other structures have been replaced by '
                      '' + reps + '[0-9]+. The field description contains the additional description of this JSON file. '
                      'This file may be parsed to a dict with the pyerrors routine load_json_dict.')

        desc_dict = {'INFO': infostring, 'OBSDICT': {}, 'description': description}
        ol, desc_dict['OBSDICT'] = _ol_from_dict(od, reps=reps)

        dump_to_json(ol, fname, description=desc_dict, indent=indent, gz=gz)

    def _od_from_list_and_dict(ol, ind, reps='DICTOBS'):
        """Parse a list of Obs or structures containing Obs and an accompanying
        dict, where the structures have been replaced by placeholders to a
        dict that contains the structures.

        The following structures are supported: Obs, list, numpy.ndarray, Corr

        Parameters
        ----------
        ol : list
            List of objects -
            At the moment, these objects can be either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        ind : dict
            Dict that defines the structure of the resulting dict and contains placeholders
        reps : str
            Specify the structure of the placeholder in imported dict to be reps[0-9]+.
        """
        if not reps.isalnum():
            raise Exception('Placeholder string has to be alphanumeric!')

        counter = 0

        def dict_replace_string(d):
            nonlocal counter
            nonlocal ol
            x = {}
            for k, v in d.items():
                if isinstance(v, dict):
                    v = dict_replace_string(v)
                elif isinstance(v, list):
                    v = list_replace_string(v)
                elif isinstance(v, str) and bool(re.match(r'%s[0-9]+' % (reps), v)):
                    index = int(v[len(reps):])
                    v = ol[index]
                    counter += 1
                x[k] = v
            return x

        def list_replace_string(li):
            nonlocal counter
            nonlocal ol
            x = []
            for e in li:
                if isinstance(e, list):
                    e = list_replace_string(e)
                elif isinstance(e, dict):
                    e = dict_replace_string(e)
                elif isinstance(e, str) and bool(re.match(r'%s[0-9]+' % (reps), e)):
                    index = int(e[len(reps):])
                    e = ol[index]
                    counter += 1
                x.append(e)
            return x

        nd = dict_replace_string(ind)

        if counter == 0:
            raise Exception('No placeholder has been replaced! Check if reps is set correctly.')

        return nd

    def load_json_dict(fname, verbose=True, gz=True, full_output=False, reps='DICTOBS'):
        """Import a dict of Obs or structures containing Obs from a .json(.gz) file.

        The following structures are supported: Obs, list, numpy.ndarray, Corr

        Parameters
        ----------
        fname : str
            Filename of the input file.
        verbose : bool
            Print additional information that was written to the file.
        gz : bool
            If True, assumes that data is gzipped. If False, assumes JSON file.
        full_output : bool
            If True, a dict containing auxiliary information and the data is returned.
            If False, only the data is returned.
        reps : str
            Specify the structure of the placeholder in imported dict to be reps[0-9]+.
        """
        indata = load_json(fname, verbose=verbose, gz=gz, full_output=True)
        description = indata['description']['description']
        indict = indata['description']['OBSDICT']
        ol = indata['obsdata']
        od = _od_from_list_and_dict(ol, indict, reps=reps)

        if full_output:
            indata['description'] = description
            indata['obsdata'] = od
            return indata
        else:
            return od

def create_json_string(ol, description='', indent=1):
View Source

    def create_json_string(ol, description='', indent=1):
        """Generate the string for the export of a list of Obs or structures containing Obs
        to a .json(.gz) file

        Parameters
        ----------
        ol : list
            List of objects that will be exported. At the moment, these objects can be
            either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        description : str
            Optional string that describes the contents of the json file.
        indent : int
            Specify the indentation level of the json file. None or 0 is permissible and
            saves disk space.
        """

        def _default(self, obj):
            return str(obj)
        my_encoder = json.JSONEncoder
        _default.default = json.JSONEncoder().default
        my_encoder.default = _default

        class Deltalist:
            __slots__ = ['cnfg', 'deltas']

            def __init__(self, li):
                self.cnfg = li[0]
                self.deltas = li[1:]

            def __repr__(self):
                s = '[%d' % (self.cnfg)
                for d in self.deltas:
                    s += ', %1.15e' % (d)
                s += ']'
                return s

            def __str__(self):
                return self.__repr__()

        class Floatlist:
            __slots__ = ['li']

            def __init__(self, li):
                self.li = list(li)

            def __repr__(self):
                s = '['
                for i in range(len(self.li)):
                    if i > 0:
                        s += ', '
                    s += '%1.15e' % (self.li[i])
                s += ']'
                return s

            def __str__(self):
                return self.__repr__()

        def _gen_data_d_from_list(ol):
            dl = []
            for name in ol[0].mc_names:
                ed = {}
                ed['id'] = name
                ed['replica'] = []
                for r_name in ol[0].e_content[name]:
                    rd = {}
                    rd['name'] = r_name
                    if ol[0].is_merged.get(r_name, False):
                        rd['is_merged'] = True
                    rd['deltas'] = []
                    for i in range(len(ol[0].idl[r_name])):
                        rd['deltas'].append([ol[0].idl[r_name][i]])
                        for o in ol:
                            rd['deltas'][-1].append(o.deltas[r_name][i])
                        rd['deltas'][-1] = Deltalist(rd['deltas'][-1])
                    ed['replica'].append(rd)
                dl.append(ed)
            return dl

        def _gen_cdata_d_from_list(ol):
            dl = []
            for name in ol[0].cov_names:
                ed = {}
                ed['id'] = name
                ed['layout'] = str(ol[0].covobs[name].cov.shape).lstrip('(').rstrip(')').rstrip(',')
                ed['cov'] = Floatlist(np.ravel(ol[0].covobs[name].cov))
                ncov = ol[0].covobs[name].cov.shape[0]
                ed['grad'] = []
                for i in range(ncov):
                    ed['grad'].append([])
                    for o in ol:
                        ed['grad'][-1].append(o.covobs[name].grad[i][0])
                    ed['grad'][-1] = Floatlist(ed['grad'][-1])
                dl.append(ed)
            return dl

        def write_Obs_to_dict(o):
            d = {}
            d['type'] = 'Obs'
            d['layout'] = '1'
            if o.tag:
                d['tag'] = [o.tag]
            if o.reweighted:
                d['reweighted'] = o.reweighted
            d['value'] = [o.value]
            data = _gen_data_d_from_list([o])
            if len(data) > 0:
                d['data'] = data
            cdata = _gen_cdata_d_from_list([o])
            if len(cdata) > 0:
                d['cdata'] = cdata
            return d

        def write_List_to_dict(ol):
            _assert_equal_properties(ol)
            d = {}
            d['type'] = 'List'
            d['layout'] = '%d' % len(ol)
            taglist = [o.tag for o in ol]
            if np.any([tag is not None for tag in taglist]):
                d['tag'] = taglist
            if ol[0].reweighted:
                d['reweighted'] = ol[0].reweighted
            d['value'] = [o.value for o in ol]
            data = _gen_data_d_from_list(ol)
            if len(data) > 0:
                d['data'] = data
            cdata = _gen_cdata_d_from_list(ol)
            if len(cdata) > 0:
                d['cdata'] = cdata
            return d

        def write_Array_to_dict(oa):
            ol = np.ravel(oa)
            _assert_equal_properties(ol)
            d = {}
            d['type'] = 'Array'
            d['layout'] = str(oa.shape).lstrip('(').rstrip(')').rstrip(',')
            taglist = [o.tag for o in ol]
            if np.any([tag is not None for tag in taglist]):
                d['tag'] = taglist
            if ol[0].reweighted:
                d['reweighted'] = ol[0].reweighted
            d['value'] = [o.value for o in ol]
            data = _gen_data_d_from_list(ol)
            if len(data) > 0:
                d['data'] = data
            cdata = _gen_cdata_d_from_list(ol)
            if len(cdata) > 0:
                d['cdata'] = cdata
            return d

        def _nan_Obs_like(obs):
            samples = []
            names = []
            idl = []
            for key, value in obs.idl.items():
                samples.append([np.nan] * len(value))
                names.append(key)
                idl.append(value)
            my_obs = Obs(samples, names, idl)
            my_obs._covobs = obs._covobs
            for name in obs._covobs:
                my_obs.names.append(name)
            my_obs.reweighted = obs.reweighted
            my_obs.is_merged = obs.is_merged
            return my_obs

        def write_Corr_to_dict(my_corr):
            first_not_none = next(i for i, j in enumerate(my_corr.content) if np.all(j))
            dummy_array = np.empty((my_corr.N, my_corr.N), dtype=object)
            dummy_array[:] = _nan_Obs_like(my_corr.content[first_not_none].ravel()[0])
            content = [o if o is not None else dummy_array for o in my_corr.content]
            dat = write_Array_to_dict(np.array(content, dtype=object))
            dat['type'] = 'Corr'
            corr_meta_data = str(my_corr.tag)
            if 'tag' in dat.keys():
                dat['tag'].append(corr_meta_data)
            else:
                dat['tag'] = [corr_meta_data]
            taglist = dat['tag']
            dat['tag'] = {}  # tag is now a dictionary, that contains the previous taglist in the key "tag"
            dat['tag']['tag'] = taglist
            if my_corr.prange is not None:
                dat['tag']['prange'] = my_corr.prange
            return dat

        if not isinstance(ol, list):
            ol = [ol]

        d = {}
        d['program'] = 'pyerrors %s' % (pyerrorsversion.__version__)
        d['version'] = '1.0'
        d['who'] = getpass.getuser()
        d['date'] = datetime.datetime.now().astimezone().strftime('%Y-%m-%d %H:%M:%S %z')
        d['host'] = socket.gethostname() + ', ' + platform.platform()

        if description:
            d['description'] = description
        d['obsdata'] = []
        for io in ol:
            if isinstance(io, Obs):
                d['obsdata'].append(write_Obs_to_dict(io))
            elif isinstance(io, list):
                d['obsdata'].append(write_List_to_dict(io))
            elif isinstance(io, np.ndarray):
                d['obsdata'].append(write_Array_to_dict(io))
            elif isinstance(io, Corr):
                d['obsdata'].append(write_Corr_to_dict(io))
            else:
                raise Exception("Unkown datatype.")

        jsonstring = ''
        for chunk in my_encoder(indent=indent, ensure_ascii=False).iterencode(d):
            jsonstring += chunk

        del d
        gc.collect()

        def remove_quotationmarks_split(split):
            """Workaround for un-quoting of delta lists, adds 5% of work
               but is save, compared to a simple replace that could destroy the structure
            """
            deltas = False
            for i in range(len(split)):
                if '"deltas":' in split[i] or '"cov":' in split[i] or '"grad":' in split[i]:
                    deltas = True
                if deltas:
                    split[i] = split[i].replace('"[', '[').replace(']"', ']')
                    if split[i][-1] == ']':
                        deltas = False
            return '\n'.join(split)

        jsonstring = jsonstring.split('\n')
        jsonstring = remove_quotationmarks_split(jsonstring)
        jsonstring = jsonstring.replace('nan', 'NaN')
        return jsonstring

Generate the string for the export of a list of Obs or structures containing Obs to a .json(.gz) file

###### Parameters

- ol (list): List of objects that will be exported. At the moment, these objects can be either of: Obs, list, numpy.ndarray, Corr. All Obs inside a structure have to be defined on the same set of configurations.
- description (str): Optional string that describes the contents of the json file.
- indent (int): Specify the indentation level of the json file. None or 0 is permissible and saves disk space.

def dump_to_json(ol, fname, description='', indent=1, gz=True):
View Source

    def dump_to_json(ol, fname, description='', indent=1, gz=True):
        """Export a list of Obs or structures containing Obs to a .json(.gz) file

        Parameters
        ----------
        ol : list
            List of objects that will be exported. At the moment, these objects can be
            either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        fname : str
            Filename of the output file.
        description : str
            Optional string that describes the contents of the json file.
        indent : int
            Specify the indentation level of the json file. None or 0 is permissible and
            saves disk space.
        gz : bool
            If True, the output is a gzipped json. If False, the output is a json file.
        """

        jsonstring = create_json_string(ol, description, indent)

        if not fname.endswith('.json') and not fname.endswith('.gz'):
            fname += '.json'

        if gz:
            if not fname.endswith('.gz'):
                fname += '.gz'

            fp = gzip.open(fname, 'wb')
            fp.write(jsonstring.encode('utf-8'))
        else:
            fp = open(fname, 'w', encoding='utf-8')
            fp.write(jsonstring)
        fp.close()

Export a list of Obs or structures containing Obs to a .json(.gz) file

###### Parameters

- ol (list): List of objects that will be exported. At the moment, these objects can be either of: Obs, list, numpy.ndarray, Corr. All Obs inside a structure have to be defined on the same set of configurations.
- fname (str): Filename of the output file.
- description (str): Optional string that describes the contents of the json file.
- indent (int): Specify the indentation level of the json file. None or 0 is permissible and saves disk space.
- gz (bool): If True, the output is a gzipped json. If False, the output is a json file.

def import_json_string(json_string, verbose=True, full_output=False):
View Source

    def import_json_string(json_string, verbose=True, full_output=False):
        """Reconstruct a list of Obs or structures containing Obs from a json string.

        The following structures are supported: Obs, list, numpy.ndarray, Corr
        If the list contains only one element, it is unpacked from the list.

        Parameters
        ----------
        json_string : str
            json string containing the data.
        verbose : bool
            Print additional information that was written to the file.
        full_output : bool
            If True, a dict containing auxiliary information and the data is returned.
            If False, only the data is returned.
        """

        return _parse_json_dict(json.loads(json_string), verbose, full_output)

Reconstruct a list of Obs or structures containing Obs from a json string.

The following structures are supported: Obs, list, numpy.ndarray, Corr If the list contains only one element, it is unpacked from the list.

###### Parameters

- json_string (str): json string containing the data.
- verbose (bool): Print additional information that was written to the file.
- full_output (bool): If True, a dict containing auxiliary information and the data is returned. If False, only the data is returned.

def load_json(fname, verbose=True, gz=True, full_output=False):
View Source

    def load_json(fname, verbose=True, gz=True, full_output=False):
        """Import a list of Obs or structures containing Obs from a .json(.gz) file.

        The following structures are supported: Obs, list, numpy.ndarray, Corr
        If the list contains only one element, it is unpacked from the list.

        Parameters
        ----------
        fname : str
            Filename of the input file.
        verbose : bool
            Print additional information that was written to the file.
        gz : bool
            If True, assumes that data is gzipped. If False, assumes JSON file.
        full_output : bool
            If True, a dict containing auxiliary information and the data is returned.
            If False, only the data is returned.
        """
        if not fname.endswith('.json') and not fname.endswith('.gz'):
            fname += '.json'
        if gz:
            if not fname.endswith('.gz'):
                fname += '.gz'
            with gzip.open(fname, 'r') as fin:
                d = json.load(fin)
        else:
            if fname.endswith('.gz'):
                warnings.warn("Trying to read from %s without unzipping!" % fname, UserWarning)
            with open(fname, 'r', encoding='utf-8') as fin:
                d = json.loads(fin.read())

        return _parse_json_dict(d, verbose, full_output)

Import a list of Obs or structures containing Obs from a .json(.gz) file.

The following structures are supported: Obs, list, numpy.ndarray, Corr If the list contains only one element, it is unpacked from the list.

###### Parameters

- fname (str): Filename of the input file.
- verbose (bool): Print additional information that was written to the file.
- gz (bool): If True, assumes that data is gzipped. If False, assumes JSON file.
- full_output (bool): If True, a dict containing auxiliary information and the data is returned. If False, only the data is returned.

def dump_dict_to_json(od, fname, description='', indent=1, reps='DICTOBS', gz=True):
View Source

    def dump_dict_to_json(od, fname, description='', indent=1, reps='DICTOBS', gz=True):
        """Export a dict of Obs or structures containing Obs to a .json(.gz) file

        Parameters
        ----------
        od : dict
            Dict of JSON valid structures and objects that will be exported.
            At the moment, these objects can be either of: Obs, list, numpy.ndarray, Corr.
            All Obs inside a structure have to be defined on the same set of configurations.
        fname : str
            Filename of the output file.
        description : str
            Optional string that describes the contents of the json file.
        indent : int
            Specify the indentation level of the json file. None or 0 is permissible and
            saves disk space.
        reps : str
            Specify the structure of the placeholder in exported dict to be reps[0-9]+.
        gz : bool
            If True, the output is a gzipped json. If False, the output is a json file.
        """

        if not isinstance(od, dict):
            raise Exception('od has to be a dictionary. Did you want to use dump_to_json?')

        infostring = ('This JSON file contains a python dictionary that has been parsed to a list of structures. '
                      'OBSDICT contains the dictionary, where Obs or other structures have been replaced by '
                      '' + reps + '[0-9]+. The field description contains the additional description of this JSON file. '
                      'This file may be parsed to a dict with the pyerrors routine load_json_dict.')

        desc_dict = {'INFO': infostring, 'OBSDICT': {}, 'description': description}
        ol, desc_dict['OBSDICT'] = _ol_from_dict(od, reps=reps)

        dump_to_json(ol, fname, description=desc_dict, indent=indent, gz=gz)

Export a dict of Obs or structures containing Obs to a .json(.gz) file

###### Parameters

- od (dict): Dict of JSON valid structures and objects that will be exported. At the moment, these objects can be either of: Obs, list, numpy.ndarray, Corr. All Obs inside a structure have to be defined on the same set of configurations.
- fname (str): Filename of the output file.
- description (str): Optional string that describes the contents of the json file.
- indent (int): Specify the indentation level of the json file. None or 0 is permissible and saves disk space.
- reps (str): Specify the structure of the placeholder in exported dict to be reps[0-9]+.
- gz (bool): If True, the output is a gzipped json. If False, the output is a json file.

def load_json_dict(fname, verbose=True, gz=True, full_output=False, reps='DICTOBS'):
View Source

    def load_json_dict(fname, verbose=True, gz=True, full_output=False, reps='DICTOBS'):
        """Import a dict of Obs or structures containing Obs from a .json(.gz) file.

        The following structures are supported: Obs, list, numpy.ndarray, Corr

        Parameters
        ----------
        fname : str
            Filename of the input file.
        verbose : bool
            Print additional information that was written to the file.
        gz : bool
            If True, assumes that data is gzipped. If False, assumes JSON file.
        full_output : bool
            If True, a dict containing auxiliary information and the data is returned.
            If False, only the data is returned.
        reps : str
            Specify the structure of the placeholder in imported dict to be reps[0-9]+.
        """
        indata = load_json(fname, verbose=verbose, gz=gz, full_output=True)
        description = indata['description']['description']
        indict = indata['description']['OBSDICT']
        ol = indata['obsdata']
        od = _od_from_list_and_dict(ol, indict, reps=reps)

        if full_output:
            indata['description'] = description
            indata['obsdata'] = od
            return indata
        else:
            return od

Import a dict of Obs or structures containing Obs from a .json(.gz) file.

The following structures are supported: Obs, list, numpy.ndarray, Corr

###### Parameters

- fname (str): Filename of the input file.
- verbose (bool): Print additional information that was written to the file.
- gz (bool): If True, assumes that data is gzipped. If False, assumes JSON file.
- full_output (bool): If True, a dict containing auxiliary information and the data is returned. If False, only the data is returned.
- reps (str): Specify the structure of the placeholder in imported dict to be reps[0-9]+.