feat!: dump methods now export to the json.gz format by default. Pickle

format can be chosen via parameter.

examples/03_pcac_example.ipynb

@@ -320,7 +320,7 @@
    "outputs": [],
    "source": [
     "pcac_plateau.tag = \"O(a) improved PCAC mass extracted on the test ensemble\"\n",
-    "pe.input.json.dump_to_json(pcac_plateau, \"pcac_plateau_test_ensemble\")"
+    "pcac_plateau.dump(\"pcac_plateau_test_ensemble\", datatype=\"json.gz\")"
    ]
   },
   {

pyerrors/correlators.py

@@ -280,8 +280,8 @@ class Corr:
         .................
         C(t+(n-1)) c(t+n) ... c(t+2(n-1))
 
-        Parameters:
-        -----------
+        Parameters
+        ----------
         N : int
             Dimension of the Hankel matrix
         periodic : bool, optional
@@ -666,17 +666,29 @@ class Corr:
 
         return
 
-    def dump(self, filename, **kwargs):
-        """Dumps the Corr into a pickle file
+    def dump(self, filename, datatype="json.gz", **kwargs):
+        """Dumps the Corr into a file of chosen type
         Parameters
         ----------
         filename : str
-            Name of the file
+            Name of the file to be saved.
+        datatype : str
+            Format of the exported file. Supported formats include
+            "json.gz" and "pickle"
         path : str
             specifies a custom path for the file (default '.')
         """
-        dump_object(self, filename, **kwargs)
-        return
+        if datatype == "json.gz":
+            from .input.json import dump_to_json
+            if 'path' in kwargs:
+                file_name = kwargs.get('path') + '/' + filename
+            else:
+                file_name = filename
+            dump_to_json(self, file_name)
+        elif datatype == "pickle":
+            dump_object(self, filename, **kwargs)
+        else:
+            raise Exception("Unknown datatype " + str(datatype))
 
     def print(self, range=[0, None]):
         print(self.__repr__(range))

pyerrors/obs.py

@@ -590,22 +590,32 @@ class Obs:
 
         return dict(zip(self.e_names, sizes))
 
-    def dump(self, name, **kwargs):
-        """Dump the Obs to a pickle file 'name'.
+    def dump(self, filename, datatype="json.gz", **kwargs):
+        """Dump the Obs to a file 'name' of chosen format.
 
         Parameters
         ----------
-        name : str
+        filename : str
             name of the file to be saved.
+        datatype : str
+            Format of the exported file. Supported formats include
+            "json.gz" and "pickle"
         path : str
             specifies a custom path for the file (default '.')
         """
         if 'path' in kwargs:
-            file_name = kwargs.get('path') + '/' + name + '.p'
+            file_name = kwargs.get('path') + '/' + filename
         else:
-            file_name = name + '.p'
-        with open(file_name, 'wb') as fb:
-            pickle.dump(self, fb)
+            file_name = filename
+
+        if datatype == "json.gz":
+            from .input.json import dump_to_json
+            dump_to_json([self], file_name)
+        elif datatype == "pickle":
+            with open(file_name + '.p', 'wb') as fb:
+                pickle.dump(self, fb)
+        else:
+            raise Exception("Unknown datatype " + str(datatype))
 
     def export_jackknife(self):
         """Export jackknife samples from the Obs

tests/correlators_test.py

@@ -131,11 +131,20 @@ def test_utility():
     corr.print([2, 4])
     corr.show()
 
-    corr.dump('test_dump', path='.')
-    corr.dump('test_dump')
+    corr.dump('test_dump', datatype="pickle", path='.')
+    corr.dump('test_dump', datatype="pickle")
     new_corr = pe.load_object('test_dump.p')
     os.remove('test_dump.p')
     for o_a, o_b in zip(corr.content, new_corr.content):
         assert np.isclose(o_a[0].value, o_b[0].value)
         assert np.isclose(o_a[0].dvalue, o_b[0].dvalue)
         assert np.allclose(o_a[0].deltas['t'], o_b[0].deltas['t'])
+
+    corr.dump('test_dump', datatype="json.gz", path='.')
+    corr.dump('test_dump', datatype="json.gz")
+    new_corr = pe.input.json.load_json('test_dump')
+    os.remove('test_dump.json.gz')
+    for o_a, o_b in zip(corr.content, new_corr.content):
+        assert np.isclose(o_a[0].value, o_b[0].value)
+        assert np.isclose(o_a[0].dvalue, o_b[0].dvalue)
+        assert np.allclose(o_a[0].deltas['t'], o_b[0].deltas['t'])

tests/io_test.py

@@ -111,7 +111,7 @@ def test_json_corr_io():
 
 
 def test_json_corr_2d_io():
-    obs_list = [np.array([[pe.pseudo_Obs(1.0 + i, 0.1 * i, 'test'), pe.pseudo_Obs(0.0, 0.1 * i, 'test')], [pe.pseudo_Obs(0.0, 0.1 * i, 'test'), pe.pseudo_Obs(1.0 + i, 0.1 * i, 'test')]]) for i in range(8)]
+    obs_list = [np.array([[pe.pseudo_Obs(1.0 + i, 0.1 * i, 'test'), pe.pseudo_Obs(0.0, 0.1 * i, 'test')], [pe.pseudo_Obs(0.0, 0.1 * i, 'test'), pe.pseudo_Obs(1.0 + i, 0.1 * i, 'test')]]) for i in range(4)]
 
     for tag in [None, "test"]:
         obs_list[3][0, 1].tag = tag

tests/obs_test.py

@@ -57,11 +57,16 @@ def test_dump():
     value = np.random.normal(5, 10)
     dvalue = np.abs(np.random.normal(0, 1))
     test_obs = pe.pseudo_Obs(value, dvalue, 't')
-    test_obs.dump('test_dump', path=".")
-    test_obs.dump('test_dump')
+    test_obs.dump('test_dump', datatype="pickle", path=".")
+    test_obs.dump('test_dump', datatype="pickle")
     new_obs = pe.load_object('test_dump.p')
     os.remove('test_dump.p')
-    assert test_obs.deltas['t'].all() == new_obs.deltas['t'].all()
+    assert test_obs == new_obs
+    test_obs.dump('test_dump', dataype="json.gz", path=".")
+    test_obs.dump('test_dump', dataype="json.gz")
+    new_obs = pe.input.json.load_json("test_dump")
+    os.remove('test_dump.json.gz')
+    assert test_obs == new_obs
 
 
 def test_comparison():