Adapted other modules to data_table structure

DataModule/data_complex.py

@@ -159,7 +159,7 @@ class data_complex(data_table):
         return self.get_phase()
 
     def get_phase(self, unit='deg', unwrap=True):
-        """This function returns a data_line module with the selected data of
+        """This function returns a data_table module with the selected data of
         this data module converted in amplitude (dB). Data Module parameters
         are copied as well.
 

DataModule/data_grid.py

@@ -173,7 +173,7 @@ class data_grid(data_module_base):
         Returns
         --------
         DataModule
-            data_line module
+            data_table module
         """
         x, y = self.df.dims[:2]
         ex = self.df.sel(x=x0, method='nearest')
@@ -209,7 +209,7 @@ class data_grid(data_module_base):
         Returns
         --------
         DataModule
-            data_line module
+            data_table module
         """
         x, y = self.df.dims[:2]
         ex = self.df.sel(y=y0, method='nearest')
@@ -410,7 +410,7 @@ class data_grid(data_module_base):
         Returns
         --------
         DataModule
-            A `data_line` DataModule. Values depend on argument keyword (see
+            A `data_table` DataModule. Values depend on argument keyword (see
             above)
         """
         if nnB == 1:
@@ -465,7 +465,7 @@ class data_grid(data_module_base):
         Returns
         --------
         DataModule
-            A `data_line` DataModule. Values depend on argument keyword (see
+            A `data_table` DataModule. Values depend on argument keyword (see
             above)
         """
         if nnB == 1:
@@ -522,7 +522,7 @@ class data_grid(data_module_base):
         Returns
         --------
         DataModule
-            A `data_line` DataModule. Values depend on argument keyword (see
+            A `data_table` DataModule. Values depend on argument keyword (see
             above)
         """
         tmp = np.zeros_like(self.y)
@@ -598,7 +598,7 @@ class data_grid(data_module_base):
         Returns
         --------
         DataModule
-            A `data_line` DataModule. Values depend on argument keyword (see
+            A `data_table` DataModule. Values depend on argument keyword (see
             above)
         """
         tmp = np.zeros_like(self.y)

DataModule/data_table.py

@@ -176,7 +176,7 @@ class data_table(data_module_base):
                         self.df[order_names[i]][df_idx] = data_arrays[i][idx]
             else:
                 self.df = self.df.append({key: value[idx] for key, value
-                                         in zip(order_names, data_arrays)},
+                                          in zip(order_names, data_arrays)},
                                          ignore_index=True)
                 pass
 
@@ -341,23 +341,28 @@ class data_table(data_module_base):
                 legend = ""
 
             # Plot Data
-            for kw in style:
-                if kw == '-':
-                    fig.line(x * xscale, y * yscale, line_color=c,
-                             line_width=linewidth, legend=legend, **kwargs)
-                elif kw == 'o':
-                    fig.circle(x, y, fill_color=c, line_color=c,
-                               size=markersize, legend=legend, **kwargs)
-                    if ("{} Errors".format(self.name_y) in self.df.keys() and
-                            plot_errors):
-                        err_xs = []
-                        err_ys = []
-                        errs = self.df[self.name_y + ' Errors'][
-                               self.idx_min:self.idx_max]
-                        for xs, ys, yerr in zip(x, y, errs):
-                            err_xs.append((xs, xs))
-                            err_ys.append((ys - yerr, ys+ yerr))
-                        fig.multi_line(err_xs, err_ys, color=c)
+            if ("{} Errors".format(self.name_y) in self.df.keys() and
+                    plot_errors):
+                # Just plot dots if error bars given
+                fig.circle(x, y, fill_color=c, line_color=c,
+                           size=markersize, legend=legend, **kwargs)
+
+                err_xs = []
+                err_ys = []
+                errs = self.df[self.name_y + ' Errors'][
+                       self.idx_min:self.idx_max]
+                for xs, ys, yerr in zip(x, y, errs):
+                    err_xs.append((xs, xs))
+                    err_ys.append((ys - yerr, ys + yerr))
+                fig.multi_line(err_xs, err_ys, color=c)
+            else:
+                for kw in style:
+                    if kw == '-':
+                        fig.line(x * xscale, y * yscale, line_color=c,
+                                 line_width=linewidth, legend=legend, **kwargs)
+                    elif kw == 'o':
+                        fig.circle(x, y, fill_color=c, line_color=c,
+                                   size=markersize, legend=legend, **kwargs)
 
             # Plot Fit
             if plot_fit and self._fit_executed:
@@ -367,7 +372,7 @@ class data_table(data_module_base):
                 else:
                     fc = fitcolor
                 # Plot fit
-                fig.line(x*xscale, fitfunc(x, *self._fit_parameters)*yscale,
+                fig.line(x * xscale, fitfunc(x, *self._fit_parameters) * yscale,
                          line_color=fc, line_width=fit_linewidth)
 
             # Format nicer HoverTool
@@ -521,8 +526,9 @@ class data_table(data_module_base):
         self._fit_parameters = fit_p_fit
         self._fit_par_errors = np.sqrt(np.diag(err))
         # Chi squared
-        self._fit_data_error = (np.sum((fitfunc(xsel, *fit_p_fit) - ysel) ** 2) /
-                                (len(xsel) - 2))
+        self._fit_data_error = (
+                np.sum((fitfunc(xsel, *fit_p_fit) - ysel) ** 2) /
+                (len(xsel) - 2))
         self._fit_labels = labels
 
         if plot_params:

IQCALIBRATION.py

@@ -998,7 +998,7 @@ class IQCalAM(object):
         
         # Completing the measurement
         x, y = self._SpecAna.Read()
-        tmp = dm.data_line(x/1e9, y)
+        tmp = dm.data_table([x/1e9, y], ['Frequency (GHz)', 'PSD (dB)'])
         
         # Obtain the data for the LSB, carrier and RSB
         tmp.select([LSB - peaks_span, LSB + peaks_span])

IQCALIBRATIONNEW.py

@@ -975,7 +975,7 @@ class IQCalAM(object):
         
         # Completing the measurement
         x, y = self._SpecAna.Read()
-        tmp = dm.data_line(x/1e9, y)
+        tmp = dm.data_table([x/1e9, y], ['Frequency (GHz)', 'PSD (dB)'])
         
         # Obtain the data for the LSB, carrier and RSB
         tmp.select([LSB - peaks_span, LSB + peaks_span])

Instruments/SA.py

@@ -88,7 +88,7 @@ class SA(object):
     def meas(self, f1, f2, filename, avgs=1, bw_res='auto',
              points=32001, center=False, sweep_time='auto',
              **dm_parameters):
-        """Take a spectrum and save it as a data_line datamodule
+        """Take a spectrum and save it as a data_table datamodule
 
         Parameters
         -----------

Instruments/VNA.py

@@ -80,7 +80,7 @@ class VNA(object):
     #          parameters={}, power_port2=False):
     #     """VNA Measurement
     #
-    #     Automatically save as data_line datamodule if not specified
+    #     Automatically save as data_table datamodule if not specified
     #     otherwise (autoSave=False).
     #
     #     Parameters

Notebooks/New lib-IQ.ipynb

@@ -420,7 +420,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data_e = dm.data_line(sweep[:-1],measurement_ph[:-1])"
+    "data_e = dm.data_table([sweep[:-1],measurement_ph[:-1]])"
    ]
   },
   {

QUBEXP.py

@@ -1883,7 +1883,7 @@ class Qubexp(object):
         
 #----------------------------------------------------------------------------------------------- q07 Utilities functions    
     def create_dm_before(self,Temp_reading=True):
-        data = dm.data_line()
+        data = dm.data_table()
         
         if Temp_reading is True:
             sr = SensorReader(self.CryoID)
@@ -1897,7 +1897,7 @@ class Qubexp(object):
     
     def create_dm_after(self,data,x,y,Temp_reading=True):
         if data is None:
-            data = dm.data_line()
+            data = dm.data_table()
         
         if Temp_reading is True:
             sr = SensorReader(self.CryoID)