WIP: Add versioning functionality to spaces

nifty/probing/__init__.py

 # -*- coding: utf-8 -*-
 
 from prober import Prober
-from operator_prober import OperatorProber
 from diagonal_prober import *
 from trace_prober import *

nifty/spaces/gl_space/gl_space.py

 from __future__ import division
 
+import pickle
+
 import itertools
 import numpy as np
 
 import d2o
 from d2o import STRATEGIES as DISTRIBUTION_STRATEGIES
+from keepers import Versionable
 
 from nifty.spaces.space import Space
 from nifty.config import nifty_configuration as gc,\
@@ -16,7 +19,7 @@ gl = gdi.get('libsharp_wrapper_gl')
 GL_DISTRIBUTION_STRATEGIES = DISTRIBUTION_STRATEGIES['global']
 
 
-class GLSpace(Space):
+class GLSpace(Versionable, Space):
     """
         ..                 __
         ..               /  /
@@ -69,6 +72,8 @@ class GLSpace(Space):
             An array containing the pixel sizes.
     """
 
+    _serializable = ('nlat', 'nlon', 'dtype')
+
     # ---Overwritten properties and methods---
 
     def __init__(self, nlat=2, nlon=None, dtype=np.dtype('float')):
@@ -208,3 +213,17 @@ class GLSpace(Space):
                 self.logger.warn("nlon was set to an unrecommended value: "
                                  "nlon <> 2*nlat-1.")
         return nlon
+
+    # ---Serialization---
+
+    def _to_hdf5(self, hdf5_group):
+        hdf5_group['serialized'] = [
+            pickle.dumps(getattr(self, item)) for item in self._serializable
+        ]
+        return None
+
+    @classmethod
+    def _from_hdf5(cls, hdf5_group, loopback_get):
+        result = cls(
+            *[pickle.loads(item) for item in hdf5_group['serialized']])
+        return result

nifty/spaces/hp_space/hp_space.py

@@ -33,9 +33,12 @@
 """
 from __future__ import division
 
+import pickle
+
 import numpy as np
 
 import d2o
+from keepers import Versionable
 
 from nifty.spaces.space import Space
 from nifty.config import nifty_configuration as gc, \
@@ -44,7 +47,7 @@ from nifty.config import nifty_configuration as gc, \
 hp = gdi.get('healpy')
 
 
-class HPSpace(Space):
+class HPSpace(Versionable, Space):
     """
         ..        __
         ..      /  /
@@ -94,6 +97,8 @@ class HPSpace(Space):
             An array with one element containing the pixel size.
     """
 
+    _serializable = ('nside', 'dtype')
+
     # ---Overwritten properties and methods---
 
     def __init__(self, nside=2, dtype=np.dtype('float')):
@@ -203,3 +208,17 @@ class HPSpace(Space):
             raise ValueError(
                 "nside must be positive and a multiple of 2.")
         return nside
+
+    # ---Serialization---
+
+    def _to_hdf5(self, hdf5_group):
+        hdf5_group['serialized'] = [
+            pickle.dumps(getattr(self, item)) for item in self._serializable
+        ]
+        return None
+
+    @classmethod
+    def _from_hdf5(cls, hdf5_group, loopback_get):
+        result = cls(
+            *[pickle.loads(item) for item in hdf5_group['serialized']])
+        return result

nifty/spaces/power_space/power_space.py

 # -*- coding: utf-8 -*-
 
+import pickle
 import numpy as np
 
+from keepers import Versionable
+
 import d2o
 
 from power_index_factory import PowerIndexFactory
@@ -11,13 +14,16 @@ from nifty.spaces.rg_space import RGSpace
 from nifty.nifty_utilities import cast_axis_to_tuple
 
 
-class PowerSpace(Space):
+class PowerSpace(Versionable, Space):
+
+    _serializable = ('log', 'nbin', 'binbounds', 'kindex', 'rho',
+                     'pundex', 'dtype')
 
     # ---Overwritten properties and methods---
 
     def __init__(self, harmonic_domain=RGSpace((1,)),
                  distribution_strategy='not',
-                 log=False, nbin=None, binbounds=None,
+                 log=False, nbin=None, binbounds=None, power_index=None,
                  dtype=np.dtype('float')):
 
         super(PowerSpace, self).__init__(dtype)
@@ -32,12 +38,13 @@ class PowerSpace(Space):
                 "harmonic_domain must be a harmonic space.")
         self._harmonic_domain = harmonic_domain
 
-        power_index = PowerIndexFactory.get_power_index(
-                        domain=self.harmonic_domain,
-                        distribution_strategy=distribution_strategy,
-                        log=log,
-                        nbin=nbin,
-                        binbounds=binbounds)
+        if power_index is None:
+            power_index = PowerIndexFactory.get_power_index(
+                            domain=self.harmonic_domain,
+                            distribution_strategy=distribution_strategy,
+                            log=log,
+                            nbin=nbin,
+                            binbounds=binbounds)
 
         config = power_index['config']
         self._log = config['log']
@@ -154,3 +161,42 @@ class PowerSpace(Space):
     @property
     def k_array(self):
         return self._k_array
+
+    # ---Serialization---
+
+    def _to_hdf5(self, hdf5_group):
+        hdf5_group['serialized'] = [
+            pickle.dumps(getattr(self, item)) for item in self._serializable
+        ]
+
+        return {
+            'harmonic_domain': self.harmonic_domain,
+            'pindex': self.pindex,
+            'k_array': self.k_array
+        }
+
+    @classmethod
+    def _from_hdf5(cls, hdf5_group, loopback_get):
+        deserialized =\
+            [pickle.loads(item) for item in hdf5_group['serialized']]
+
+        dtype = deserialized[6]
+        harmonic_domain = loopback_get('harmonic_domain')
+        power_index = {
+            'config': {
+                'log': deserialized[0], 'nbin': deserialized[1],
+                'binbounds': deserialized[2]
+            },
+            'pindex': loopback_get('pindex'),
+            'kindex': deserialized[3],
+            'rho': deserialized[4],
+            'pundex': deserialized[5],
+            'k_array': loopback_get('k_array')
+        }
+
+        result = cls(
+            harmonic_domain=harmonic_domain,
+            power_index=power_index,
+            dtype=dtype
+        )
+        return result

nifty/spaces/rg_space/rg_space.py

@@ -33,15 +33,19 @@
 """
 from __future__ import division
 
+import pickle
+
 import numpy as np
 
+from keepers import Versionable
+
 from d2o import distributed_data_object,\
                 STRATEGIES as DISTRIBUTION_STRATEGIES
 
 from nifty.spaces.space import Space
 
 
-class RGSpace(Space):
+class RGSpace(Versionable, Space):
     """
         ..      _____   _______
         ..    /   __/ /   _   /
@@ -103,6 +107,8 @@ class RGSpace(Space):
             Whether or not the grid represents a Fourier basis.
     """
 
+    _serializable = ('shape', 'zerocenter', 'distances', 'harmonic', 'dtype')
+
     # ---Overwritten properties and methods---
 
     def __init__(self, shape=(1,), zerocenter=False, distances=None,
@@ -320,3 +326,17 @@ class RGSpace(Space):
         temp = np.empty(len(self.shape), dtype=bool)
         temp[:] = zerocenter
         return tuple(temp)
+
+    # ---Serialization---
+
+    def _to_hdf5(self, hdf5_group):
+        hdf5_group['serialized'] = [
+            pickle.dumps(getattr(self, item)) for item in self._serializable
+        ]
+        return None
+
+    @classmethod
+    def _from_hdf5(cls, hdf5_group, loopback_get):
+        result = cls(
+            *[pickle.loads(item) for item in hdf5_group['serialized']])
+        return result