in-place multiply and divide for UniformTime

nitime/tests/test_timeseries.py

@@ -813,8 +813,14 @@ def assign_to_one_element_of(t): t[0]=42
 
     # same as utime, but with a lower sampling rate
     utime_2 = ts.UniformTime(t0=10, length=10, sampling_interval=2)
-    utime += np.arange(10)
+    utime += np.arange(10) # make utime match utime_2
     npt.assert_equal(utime,utime_2)
+    npt.assert_equal(utime.sampling_interval,utime_2.sampling_interval)
+
+    utime = ts.UniformTime(t0=5, length=10, sampling_rate=1)
+    utime *= 2 # alternative way to make utime match utime_2
+    npt.assert_equal(utime.sampling_interval,utime_2.sampling_interval)
+    npt.assert_equal(utime.sampling_rate,utime_2.sampling_rate)
 
     nonuniform = np.concatenate((range(2),range(3), range(5)))
     def iadd_nonuniform(t): t+=nonuniform

nitime/timeseries.py

@@ -617,7 +617,7 @@ def __setitem__(self, key, val):
             You can either use += on the full array, OR
             create a new TimeArray from this UniformTime""")
 
-    def _convert_and_check_uniformity(self,val):
+    def _convert_and_check_uniformity(self, val):
         # look at the units - convert the values to what they need to be (in
         # the base_unit) and then delegate to the ndarray.__iadd__
         if not hasattr(val, '_conversion_factor'):
@@ -649,6 +649,19 @@ def __isub__(self, val):
         val = self._convert_and_check_uniformity(val)
         return np.ndarray.__isub__(self, val)
 
+    def __imul__(self, val):
+        np.ndarray.__imul__(self, val)
+        self.sampling_interval *= val
+        self.sampling_rate = Frequency(self.sampling_rate / val)
+        return self
+
+    def __idiv__(self, val):
+        np.ndarray.__idiv__(self, val)
+        self.sampling_interval /= val
+        self.sampling_rate = Frequency(self.sampling_rate * val)
+        return self
+
+
     def index_at(self, t, boolean=False):
         """Find the index that corresponds to the time bin containing t