NeuralEnsemble#278 Create neo.units module

And remove Quantities import in the code (except for units module)

doc/source/api_reference.rst

@@ -6,4 +6,4 @@ API Reference
 .. testsetup:: *
 
     from neo import SpikeTrain
-    import quantities as pq
+    from neo import units as un

doc/source/images/generate_diagram.py

@@ -10,8 +10,8 @@
 from datetime import datetime
 
 import numpy as np
-from neo.units import Units
-Units = Units() 
+from neo import units as un
+
 from matplotlib import pyplot
 from matplotlib.patches import Rectangle, ArrowStyle, FancyArrowPatch
 from matplotlib.font_manager import FontProperties
@@ -174,7 +174,7 @@ def generate_diagram(filename, rect_pos, rect_width, figsize):
             else:
                 t1 = attrname
 
-            if attrtype == Units.Quantity:
+            if attrtype == un.Quantity:
                 if attr[2] == 0:
                     t2 = 'Quantity scalar'
                 else:

neo/core/analogsignal.py

@@ -410,7 +410,7 @@ def rescale(self, units):
         Return a copy of the AnalogSignal converted to the specified
         units
         '''
-        to_dims = Units.quantity.validate_dimensionality(units)
+        to_dims = un.quantity.validate_dimensionality(units)
         if self.dimensionality == to_dims:
             to_u = self.units
             signal = np.array(self)

neo/core/block.py

@@ -27,7 +27,7 @@ class Block(Container):
 
         >>> from neo.core import (Block, Segment, ChannelIndex,
         ...                       AnalogSignal)
-        >>> from quantities import nA, kHz
+        >>> from neo.units import nA, kHz
         >>> import numpy as np
         >>>
         >>> # create a Block with 3 Segment and 2 ChannelIndex objects

neo/core/channelindex.py

@@ -32,7 +32,7 @@ class ChannelIndex(Container):
 
         >>> from neo.core import (Block, Segment, ChannelIndex,
         ...                       AnalogSignal)
-        >>> from quantities import nA, kHz
+        >>> from neo.units import nA, kHz
         >>> import numpy as np
         >>>
         >>> # create a Block with 3 Segment and 2 ChannelIndex objects

neo/core/epoch.py

@@ -84,7 +84,7 @@ def __new__(cls, times=None, durations=None, labels=None, units=None,
             if hasattr(units, 'dimensionality'):
                 dim = units.dimensionality
             else:
-                dim = Units.quantity.validate_dimensionality(units)
+                dim = un.quantity.validate_dimensionality(units)
         # check to make sure the units are time
         # this approach is much faster than comparing the
         # reference dimensionality

neo/core/event.py

@@ -27,7 +27,7 @@ class Event(BaseNeo, un.Quantity):
     *Usage*::
 
         >>> from neo.core import Event
-        >>> from quantities import s
+        >>> from neo.units import s
         >>> import numpy as np
         >>>
         >>> evt = Event(np.arange(0, 30, 10)*s,

neo/core/irregularlysampledsignal.py

@@ -51,7 +51,7 @@ class IrregularlySampledSignal(BaseNeo, un.Quantity):
     *Usage*::
 
         >>> from neo.core import IrregularlySampledSignal
-        >>> from quantities import s, nA
+        >>> from neo.units import s, nA
         >>>
         >>> irsig0 = IrregularlySampledSignal([0.0, 1.23, 6.78], [1, 2, 3],
         ...                                   units='mV', time_units='ms')
@@ -133,12 +133,12 @@ def __new__(cls, times, signal, units=None, time_units=None, dtype=None,
                 time_units = times.units
             else:
                 raise ValueError("Time units must be specified")
-        elif isinstance(times, Units.Quantity):
+        elif isinstance(times, un.Quantity):
             # could improve this test, what if units is a string?
             if time_units != times.units:
                 times = times.rescale(time_units)
         # should check time units have correct dimensions
-        obj = Units.Quantity.__new__(cls, signal, units=units,
+        obj = un.Quantity.__new__(cls, signal, units=units,
                                   dtype=dtype, copy=copy)
         if obj.ndim == 1:
             obj = obj.reshape(-1, 1)

neo/core/segment.py

@@ -27,7 +27,7 @@ class Segment(Container):
 
     *Usage*::
         >>> from neo.core import Segment, SpikeTrain, AnalogSignal
-        >>> from quantities import Hz, s
+        >>> from neo.units import Hz, s
         >>>
         >>> seg = Segment(index=5)
         >>>

neo/core/spiketrain.py

@@ -225,7 +225,7 @@ def __new__(cls, times, t_stop, units=None, dtype=None, copy=True,
             if hasattr(units, 'dimensionality'):
                 dim = units.dimensionality
             else:
-                dim = Units.quantity.validate_dimensionality(units)
+                dim = un.quantity.validate_dimensionality(units)
 
             if hasattr(times, 'dimensionality'):
                 if times.dimensionality.items() == dim.items():

neo/io/blackrockio.py

@@ -1557,7 +1557,7 @@ def __transform_times(self, n, default_n):
         """
         highest_res = self.__nev_params('event_unit')
 
-        if isinstance(n, Units.Quantity):
+        if isinstance(n, un.Quantity):
             n = [n.rescale(highest_res)]
         elif hasattr(n, "__len__"):
             n = [tp.rescale(highest_res) if tp is not None
@@ -1867,16 +1867,16 @@ def __read_unit(self, unit_id, channel_idx):
         desc = 'Unit from channel: {0}, id: {1}'.format(
             channel_idx, self.__get_unit_classification(unit_id))
 
-        un = Unit(
+        unit_to_return = Unit(
             name=name,
             description=desc,
             file_origin='.'.join([self._filenames['nev'], 'nev']))
 
         # add additional annotations
-        un.annotate(ch_idx=int(channel_idx))
-        un.annotate(unit_id=int(unit_id))
+        unit_to_return.annotate(ch_idx=int(channel_idx))
+        unit_to_return.annotate(unit_id=int(unit_id))
 
-        return un
+        return unit_to_return
 
     def __read_recordingchannelgroup(
             self, channel_idx, index=None, channel_units=None, cascade=True):
@@ -1885,6 +1885,7 @@ def __read_recordingchannelgroup(
         given index for the given channels containing a neo.core.unit.Unit
         object list of the given units.
         """
+        from neo import units as un
 
         rcg = ChannelIndex(
             np.array([channel_idx]),