ntv-numpy.ntv_numpy.numpy_ntv_connector

  1# -*- coding: utf-8 -*-
  2"""
  3@author: Philippe@loco-labs.io
  4
  5The `numpy_ntv_connector` module is part of the `ntv-numpy.ntv_numpy` package
  6([specification document](
  7https://loco-philippe.github.io/ES/JSON%20semantic%20format%20(JSON-NTV).htm)).
  8
  9A NtvConnector is defined by:
 10- clas_obj: str - define the class name of the object to convert
 11- clas_typ: str - define the NTVtype of the converted object
 12- to_obj_ntv: method - converter from JsonNTV to the object
 13- to_json_ntv: method - converter from the object to JsonNTV
 14
 15It contains the child classes of `NTV.json_ntv.ntv.NtvConnector` abstract class:
 16    - `NarrayConnec`: 'narray' connector for np.ndarray data
 17    - `NdarrayConnec`: 'ndarray'   connector for Ndarray data
 18    - `XndarrayConnec`: 'xndarray' connector for Xndarray data
 19    - `XdatasetConnec`: 'xdataset' connector for Xdataset data
 20"""
 21from json_ntv import NtvConnector
 22
 23from ntv_numpy.ndarray import Ndarray
 24from ntv_numpy.xndarray import Xndarray
 25from ntv_numpy.xdataset import Xdataset
 26
 27"""def read_json(jsn, **kwargs):
 28    ''' convert JSON text or JSON Value to Numpy ndarray.
 29
 30    *parameters*
 31
 32    - **noadd** : boolean (default False) - If True additional data is not include
 33    - **header** : boolean (default True) - If True NTV entity with NTVtype is included
 34    - **convert** : boolean (default True) - If True, convert json data with
 35    non Numpy ntv_type into Xndarray with python type
 36    '''
 37    option = {'noadd': False, 'header': True, 'convert': True} | kwargs
 38    jso = json.loads(jsn) if isinstance(jsn, str) else jsn
 39    if isinstance(jso, dict) and len(jso) == 1:
 40        if 'xndarray' in list(jso)[0]:
 41            arr = XndarrayConnec.to_obj_ntv(list(jso.values())[0], **option)
 42            return arr
 43        else:
 44            arr = NdarrayConnec.to_obj_ntv(list(jso.values())[0], **option)
 45            return arr
 46    if isinstance(jso, list):
 47        option = {'noadd': False, 'header': False} | kwargs
 48        arr =  NdarrayConnec.to_obj_ntv(jso, **option)
 49        return arr
 50    return None
 51
 52
 53def to_json(ndarray, **kwargs):
 54    ''' convert Numpy ndarray to JSON text or JSON Value.
 55
 56    *parameters*
 57    - **encoded** : Boolean (default False) - json value if False else json text
 58    - **header** : Boolean (default True) - including ndarray or xndarray type
 59    - **notype** : Boolean (default False) - including data type if True
 60    - **noshape** : Boolean (default True) - if True, without shape if dim < 1
 61    - **novalue** : Boolean (default False) - including value if False
 62    - **name** : string (default None) - name of the ndarray
 63    - **typ** : string (default None) - type of the NTV object,
 64    - **format** : string (default 'full') - representation format of the ndarray,
 65    - **extension** : string (default None) - type extension
 66    - **add** : dict (default None) - additional data :
 67        - **attrs** : dict (default none) - metadata
 68        - **dims** : array (default none) - name of axis
 69        - **coords** : dict (default none) - dict of 'xndarray'
 70    '''
 71    option = {'encoded': False, 'format': 'full', 'header': True,
 72              'name': None, 'typ': None, 'extension':None, 'notype': False,
 73              'noshape': True, 'novalue': False, 'add': None} | kwargs
 74    if ndarray.__class__.__name__ == 'ndarray' and not kwargs.get('add'):
 75        jsn, nam, typ = NdarrayConnec.to_json_ntv(ndarray, **option)
 76    else:
 77        jsn, nam, typ = XndarrayConnec.to_json_ntv(ndarray, **option)
 78    name = nam if nam else ''
 79    return Nutil.json_ntv(name, typ, jsn, header=option['header'],
 80                           encoded=option['encoded'])"""
 81
 82"""def to_json_tab(ndarray, add=None, header=True):
 83    period = ndarray.shape
 84    dim = ndarray.ndim
 85    coefi = ndarray.size
 86    coef = []
 87    for per in period:
 88        coefi = coefi // per
 89        coef.append(coefi)
 90
 91    add = add if add else {}
 92    axe_n = add['dims'] if 'dims' in add else ['dim_' + str(i) for i in range(dim)]
 93    axe_v = [add['coords'][axe] for axe in axe_n if axe in add['coords']] if 'coords' in add else []
 94    axe_v = [axe[-1] for axe in axe_v] if len(axe_v) == len(axe_n) else [
 95                      list(range(period[i])) for i in range(dim)]
 96    jsn = {nam: [var, [coe]] for nam, var, coe in zip(axe_n, axe_v, coef)} | {
 97           'data::' + ndarray.dtype.name: ndarray.flatten().tolist()}
 98    if header:
 99        return {':tab': jsn}
100    return jsn
101
102def read_json_tab(js):
103    js = js[':tab'] if ':tab' in js else js
104    shape = []
105    axes_n = []
106    axes_v = []
107    coef = []
108    nda = None
109    for name, val in js.items():
110        if len(val) == 2 and isinstance(val[1], list) and len(val[1]) == 1:
111            shape.append(len(val[0]))
112            coef.append(val[1])
113            axes_v.append(val[0])
114            axes_n.append(name)
115        else:
116            spl = name.split('::')
117            nda = np.array(val, dtype=spl[1]) if len(spl)==2 else np.array(val)
118    coef, shape, axes_n, axes_v = list(zip(*sorted(zip(coef, shape, axes_n,
119                                                       axes_v), reverse=True)))
120    return (nda.reshape(shape), {'dims': list(axes_n),
121            'coords': {axe_n: [axe_v] for axe_n, axe_v in zip(axes_n, axes_v)}})"""
122
123
124class NarrayConnec(NtvConnector):
125
126    '''NTV connector for Numpy ndarray.'''
127
128    clas_obj = 'ndarray'
129    clas_typ = 'narray'
130
131    @staticmethod
132    def to_obj_ntv(ntv_value, **kwargs):
133        ''' convert json ntv_value into a np.ndarray.
134
135        *Parameters*
136
137        - **convert** : boolean (default True) - If True, convert json data with
138        non Numpy ntv_type into data with python type'''
139        return Ndarray.read_json(ntv_value, **kwargs).darray
140
141    @staticmethod
142    def to_json_ntv(value, name=None, typ=None, **kwargs):
143        ''' convert a np.ndarray (value, name, type) into NTV json (json-value, name, ntv_type).
144
145        *Parameters*
146
147        - **typ** : string (default None) - ntv_type of the np.ndarray object,
148        - **name** : string (default None) - name of the ndarray object
149        - **value** : np.ndarray value
150        - **noshape** : Boolean (default True) - if True, without shape if dim < 1
151        - **notype** : Boolean (default False) - including data type if False
152        - **novalue** : Boolean (default False) - including value if False
153        - **format** : string (default 'full') - representation format of the ndarray,
154        - **encoded** : Boolean (default False) - json-value if False else json-text
155        - **header** : Boolean (default True) - including ndarray type
156        '''
157        option = {'format': 'full', 'header': True, 'encoded': False,
158                  'notype': False, 'noshape': True, 'novalue': False} | kwargs
159        if not option['format'] in ['full', 'complete']:
160            option['noshape'] = False
161        option['header'] = False
162        return (Ndarray(value).to_json(**option), name, 'narray')
163
164
165class NdarrayConnec(NtvConnector):
166
167    '''NTV connector for Ndarray.'''
168
169    clas_obj = 'Ndarray'
170    clas_typ = 'ndarray'
171
172    @staticmethod
173    def to_obj_ntv(ntv_value, **kwargs):
174        ''' convert json ntv_value into a Ndarray.
175
176        *Parameters*
177
178        - **convert** : boolean (default True) - If True, convert json data with
179        non-Numpy ntv_type into data with python type'''
180        return Ndarray.read_json(ntv_value, **kwargs)
181
182    @staticmethod
183    def to_json_ntv(value, name=None, typ=None, **kwargs):
184        ''' convert a Ndarray (value, name, type) into NTV json (json-value, name, ntv_type).
185
186        *Parameters*
187
188        - **typ** : string (default None) - ntv_type of the ndarray object,
189        - **name** : string (default None) - name of the ndarray object
190        - **value** : Ndarray value (or np.ndarray value)
191        - **noshape** : Boolean (default True) - if True, without shape if dim < 1
192        - **notype** : Boolean (default False) - including data type if False
193        - **novalue** : Boolean (default False) - including value if False
194        - **format** : string (default 'full') - representation format of the ndarray,
195        - **encoded** : Boolean (default False) - json-value if False else json-text
196        - **header** : Boolean (default True) - including ndarray type
197        '''
198        option = {'format': 'full', 'header': True, 'encoded': False,
199                  'notype': False, 'noshape': True, 'novalue': False} | kwargs
200        if not option['format'] in ['full', 'complete']:
201            option['noshape'] = False
202        return (Ndarray(value).to_json(**option), name, 'ndarray')
203
204
205class XndarrayConnec(NtvConnector):
206
207    '''NTV connector for Xndarray.'''
208
209    clas_obj = 'Xndarray'
210    clas_typ = 'xndarray'
211
212    @staticmethod
213    def to_obj_ntv(ntv_value, **kwargs):
214        ''' convert json ntv_value into a Xndarray.
215
216        *Parameters*
217
218        - **convert** : boolean (default True) - If True, convert json data with
219        non-umpy ntv_type into Xndarray with python type
220        '''
221        print(ntv_value)
222        return Xndarray.read_json(ntv_value, **kwargs)
223
224    @staticmethod
225    def to_json_ntv(value, name=None, typ=None, **kwargs):
226        ''' convert a Xndarray (value) into NTV json (json-value, name, ntv_type).
227
228        *Parameters*
229
230        - **typ** : string (default None) - not used,
231        - **name** : string (default None) - not used
232        - **value** : Xndarray values
233        - **encoded** : Boolean (default False) - json-value if False else json-text
234        - **header** : Boolean (default True) - including xndarray type
235        - **notype** : Boolean (default False) - including data type if False
236        - **novalue** : Boolean (default False) - including value if False
237        - **noshape** : Boolean (default True) - if True, without shape if dim < 1
238        - **format** : string (default 'full') - representation format of the ndarray,
239        - **extension** : string (default None) - type extension
240        '''
241        option = {'notype': False, 'extension': None, 'format': 'full',
242                  'noshape': True, 'header': True, 'encoded': False,
243                  'novalue': False, 'noname': False} | kwargs
244        if not option['format'] in ['full', 'complete']:
245            option['noshape'] = False
246        return (value.to_json(**option), name, 'xndarray')
247
248
249class XdatasetConnec(NtvConnector):
250
251    '''NTV connector for Xdataset.'''
252
253    clas_obj = 'Xdataset'
254    clas_typ = 'xdataset'
255
256    @staticmethod
257    def to_obj_ntv(ntv_value, **kwargs):  # reindex=True, decode_str=False):
258        ''' convert json ntv_value into a Xdataset.
259
260        *Parameters*
261
262        - **convert** : boolean (default True) - If True, convert json data with
263        non-Numpy ntv_type into Xdataset with python type
264        '''
265        return Xdataset.read_json(ntv_value, **kwargs)
266
267    @staticmethod
268    def to_json_ntv(value, name=None, typ=None, **kwargs):
269        ''' convert a Xdataset (value) into NTV json (json-value, name, ntv_type).
270
271        *Parameters*
272
273        - **typ** : string (default None) - not used,
274        - **name** : string (default None) - not used
275        - **value** : Xdataset entity
276        - **encoded** : Boolean (default False) - json value if False else json text
277        - **header** : Boolean (default True) - including 'xdataset' type
278        - **notype** : list of Boolean (default list of None) - including data type if False
279        - **novalue** : Boolean (default False) - including value if False
280        - **noshape** : Boolean (default False) - if True, without shape if dim < 1
281        - **format** : list of string (default list of 'full') - representation format 
282        of the np.ndarray,
283        '''
284        option = {'notype': False, 'extension': None, 'format': 'full',
285                  'noshape': True, 'header': True, 'encoded': False,
286                  'novalue': False, 'noname': False} | kwargs
287        if not option['format'] in ['full', 'complete']:
288            option['noshape'] = False
289        option['noname'] = True
290        return (value.to_json(**option), name, 'xdataset')