np.complex and np.float deprecated

pyrpl/hardware_modules/asg.py

@@ -301,7 +301,7 @@ def data(self):
             #    self._reads(self._DATA_OFFSET, self.data_length),
             #             dtype=np.int32)
             x[x >= 2 ** 13] -= 2 ** 14
-            return np.array(x, dtype=np.float) / 2 ** 13
+            return np.array(x, dtype=float) / 2 ** 13
 
         @data.setter
         def data(self, data):

pyrpl/hardware_modules/iir/iir.py

@@ -682,7 +682,7 @@ def transfer_function(self, frequencies, extradelay=0):
 
         Returns
         -------
-        tf: np.array(..., dtype=np.complex)
+        tf: np.array(..., dtype=complex)
             The complex open loop transfer function of the module.
         If kind=='all', a list of plotdata tuples is returned that can be
         passed directly to iir.bodeplot().

pyrpl/hardware_modules/iir/iir_theory.py

@@ -90,7 +90,7 @@ def freqs(sys, w):
 
     Returns
     -------
-    np.array(..., dtype=np.complex) with the response
+    np.array(..., dtype=complex) with the response
     """
     z, p, k = sys
     s = np.array(w, dtype=np.complex128) * 1j
@@ -135,7 +135,7 @@ def freqz_(sys, w, dt=8e-9):
 
     Returns
     -------
-    np.array(..., dtype=np.complex) with the response
+    np.array(..., dtype=complex) with the response
     """
     z, p, k = sys
     b, a = sig.zpk2tf(z, p, k)
@@ -877,7 +877,7 @@ def tf_inputfilter(self, inputfilter=None, frequencies=None):  # input
             inputfilter = self.inputfilter
         if frequencies is None:
             frequencies = self.frequencies
-        frequencies = np.asarray(frequencies, dtype=np.complex)
+        frequencies = np.asarray(frequencies, dtype=complex)
         try:
             len(inputfilter)
         except:
@@ -924,7 +924,7 @@ def tf_continuous(self, frequencies=None):
             frequencies to compute the transfer function for
         Returns
         -------
-        np.array(..., dtype=np.complex)
+        np.array(..., dtype=complex)
         """
         if frequencies is None:
             frequencies = self.frequencies
@@ -948,7 +948,7 @@ def tf_partialfraction(self, frequencies=None):
 
         Returns
         -------
-        np.array(..., dtype=np.complex)
+        np.array(..., dtype=complex)
         """
         # this code is more or less a direct copy of get_coeff()
         if frequencies is None:
@@ -985,7 +985,7 @@ def tf_discrete(self, rp_discrete=None, frequencies=None):
 
         Returns
         -------
-        np.array(..., dtype=np.complex)
+        np.array(..., dtype=complex)
         """
         if frequencies is None:
             frequencies = self.frequencies
@@ -1023,7 +1023,7 @@ def tf_coefficients(self, frequencies=None, coefficients=None,
 
         Returns
         -------
-        np.array(..., dtype=np.complex)
+        np.array(..., dtype=complex)
         """
         if frequencies is None:
             frequencies = self.frequencies
@@ -1071,7 +1071,7 @@ def tf_rounded(self, frequencies=None, delay=False):
 
         Returns
         -------
-        np.array(..., dtype=np.complex)
+        np.array(..., dtype=complex)
         """
         return self.tf_coefficients(frequencies=frequencies,
                                     coefficients=self.coefficients_rounded,
@@ -1099,7 +1099,7 @@ def tf_final(self, frequencies=None):
 
         Returns
         -------
-        np.array(..., dtype=np.complex)
+        np.array(..., dtype=complex)
         """
         return self.tf_rounded(frequencies=frequencies, delay=True) * \
                self.tf_inputfilter(frequencies=frequencies)

pyrpl/hardware_modules/iq.py

@@ -544,15 +544,15 @@ def transfer_function(self, frequencies, extradelay=0):
 
         Returns
         -------
-        tf: np.array(..., dtype=np.complex)
+        tf: np.array(..., dtype=complex)
             The complex open loop transfer function of the module.
         """
         quadrature_delay = 2  # the delay experienced by the signal when it
         # is represented as a quadrature (=lower frequency, less phaseshift)
         # the remaining delay of the module
         module_delay = self._delay - quadrature_delay
-        frequencies = np.array(frequencies, dtype=np.complex)
-        tf = np.array(frequencies * 0, dtype=np.complex) + self.gain
+        frequencies = np.array(frequencies, dtype=complex)
+        tf = np.array(frequencies * 0, dtype=complex) + self.gain
         # bandpass filter
         for f in self.bandwidth:
             if f == 0:

pyrpl/hardware_modules/pid.py

@@ -382,7 +382,7 @@ def transfer_function(self, frequencies, extradelay=0):
 
         Returns
         -------
-        tf: np.array(..., dtype=np.complex)
+        tf: np.array(..., dtype=complex)
             The complex open loop transfer function of the module.
         """
         return Pid._transfer_function(frequencies,

pyrpl/software_modules/network_analyzer.py

@@ -240,13 +240,13 @@ def transfer_function(self, frequencies, extradelay=0):
 
         Returns
         -------
-        tf: np.array(..., dtype=np.complex)
+        tf: np.array(..., dtype=complex)
             The complex open loop transfer function of the module.
         """
         module_delay = self._delay
         frequencies = np.array(np.array(frequencies, dtype=np.float),
-                               dtype=np.complex)
-        tf = np.array(frequencies*0, dtype=np.complex) + 1.0
+                               dtype=complex)
+        tf = np.array(frequencies*0, dtype=complex) + 1.0
         # input filter modelisation
         f = self.iq.inputfilter  # no for loop here because only one filter
         # stage
@@ -598,7 +598,7 @@ def _prepare_averaging(self):
         self.data_x = self.frequencies if not self.is_zero_span() else \
             np.nan*np.ones(self.points) # Will be filled during acquisition
         self.data_avg = np.zeros(self.points,      # np.empty can create nan
-                                 dtype=np.complex) #and nan*current_avg = nan
+                                 dtype=complex) #and nan*current_avg = nan
                                                    # even if current_avg = 0
 
     @property

pyrpl/software_modules/spectrum_analyzer.py

@@ -421,7 +421,7 @@ def _get_filtered_iq_data(self):
         :return: the product between the complex iq data and the filter_window
         """
         return self._get_iq_data() * np.asarray(self.filter_window(),
-                                            dtype=np.complex)
+                                            dtype=complex)
 
     def useful_index_obsolete(self):
         """

pyrpl/test/test_hardware_modules/test_pid_na_iq.py

@@ -46,7 +46,7 @@ def test_na(self):
             data = na.single()
             f = na.data_x
             theory = np.array(f * 0 + 1.0,
-                              dtype=np.complex)
+                              dtype=complex)
             # obsolete since na data now comes autocorrected:
             # theory = na.transfer_function(f, extradelay=extradelay)
             relerror = np.abs((data - theory) / theory)
@@ -110,7 +110,7 @@ def test_inputfilter(self):
             theory = pid.transfer_function(f, extradelay=extradelay)
             relerror = np.abs((data - theory) / theory)
             # get max error for values > -50 dB (otherwise its just NA noise)
-            mask = np.asarray(np.abs(theory) > 3e-3, dtype=np.float)
+            mask = np.asarray(np.abs(theory) > 3e-3, dtype=float)
             maxerror = np.max(relerror*mask)
             if maxerror > error_threshold:
                 print(maxerror)