Merge branch 'master' into precomp

.gitignore

@@ -114,6 +114,9 @@ $RECYCLE.BIN/
 # Pycqed specific files
 # ======================
 
+# Multiprocessing dask generated files
+*dask-worker-space*
+
 # code generated qasm files
 *.qasm
 # micro instruction assembly files
@@ -127,6 +130,7 @@ $RECYCLE.BIN/
 *.txt
 *.png
 pycqed/measurement/openql_experiments/output/*
+*.qmap
 
 # data files
 # test data files should be explicitly added by hand (overriding .gitignore)

examples/AWG8_examples/AWG8_staircase_test.py

@@ -47,8 +47,8 @@
 #  2. Starting AWG8 test program in CCL  #
 ##########################################
 
-AWG_type = 'microwave'
-# AWG_type = 'flux'
+# AWG_type = 'microwave'
+AWG_type = 'flux'
 
 if AWG_type == 'microwave':
     example_fp = os.path.abspath(
@@ -64,6 +64,7 @@
 CCL.start()
 
 
+
 ##########################################
 #  3. Configuring the DIO protocol       #
 ##########################################
@@ -72,17 +73,17 @@
 import numpy as np
 
 waveform_type = 'square'
-# waveform_type = 'cos'
+# waveform_type = 'sin'
 
 if waveform_type == 'square':
     for ch in range(8):
         for i in range(32):
             AWG8.set('wave_ch{}_cw{:03}'.format(ch+1, i), (np.ones(48)*i/32))
-elif waveform_type == 'cos':
+elif waveform_type == 'sin':
     for ch in range(8):
         for i in range(32):
             AWG8.set('wave_ch{}_cw{:03}'.format(ch+1, i),
-                     (np.cos(np.arange(48)/2)*i/32))
+                     (np.sin(np.arange(48)/48*2*np.pi*i)*i/32))
 else:
     raise KeyError()
 
@@ -95,7 +96,29 @@
 ##########################################
 #  4. Configuring the DIO protocol       #
 ##########################################
-AWG8.cfg_codeword_protocol('microwave')  # <- ensures all bits are uploaded
+AWG8.cfg_codeword_protocol(AWG_type)  # <- ensures all bits are uploaded
 AWG8.configure_codeword_protocol()
 AWG8.upload_codeword_program()
-AWG8.calibrate_dio_protocol()
+
+
+success = AWG8.calibrate_dio_protocol()
+
+
+#######################################################################
+#  4. Verifying the DIO calibration with back to back staircase       #
+#######################################################################
+
+if AWG_type == 'microwave':
+    example_fp = os.path.abspath(
+        os.path.join(pq.__path__[0], '..',
+                     'examples', 'CCLight_example', 'qisa_test_assembly',
+                     'consecutive_cws_double_back_to_back.qisa'))
+elif AWG_type == 'flux':
+    example_fp = os.path.abspath(
+        os.path.join(pq.__path__[0], '..',
+                     'examples', 'CCLight_example', 'qisa_test_assembly',
+                     'consecutive_cws_flux_back_to_back.qisa'))
+
+print(example_fp)
+CCL.eqasm_program(example_fp)
+CCL.start()

examples/CCLight_example/qisa_test_assembly/consecutive_cws_double.qisa

@@ -11,8 +11,8 @@ LDI  r4, 150
 LDI r3, 2
 SUB r3, r4, r3
 Loop:
-    qwait 100
-    bs 2 CW_01 s6
+    qwait 500
+
     bs 2 CW_01 s0 | CW_31 s2
     bs 2 CW_02 s0 | CW_30 s2
     bs 2 CW_03 s0 | CW_29 s2
@@ -44,6 +44,8 @@ Loop:
     bs 2 CW_29 s0 | CW_03 s2
     bs 2 CW_30 s0 | CW_02 s2
     bs 2 CW_31 s0 | CW_01 s2
+    bs 2 CW_01 s6
+    qwait 500
     bs 1 MeasZ s0
     BR always, loop
     NOP

examples/CCLight_example/qisa_test_assembly/consecutive_cws_flux.qisa

@@ -9,28 +9,22 @@ smis s7, {0, 1, 2, 3, 4, 5, 6}
 smis s8, {0, 1, 5, 6}
 smis s9, {2, 3, 4}
 smit t0, {(2, 0)}
-smit t0, {(3, 1)}
+smit t1, {(3, 1)}
+smit t2, {(6, 4)}
+smit t3, {(3, 5)}
 
 start:
     bs 1    prepz s0 | prepz s2
-    qwait 9999
-    bs 2 CW_01 s6
-    bs 4 FL_CW_00 t0  | FL_CW_00 t1
-    qwait 4
-    bs 4 FL_CW_01 t0  | FL_CW_01 t1
-    qwait 4
-    bs 4 FL_CW_02 t0  | FL_CW_02 t1
-    qwait 4
-    bs 4 FL_CW_03 t0  | FL_CW_03 t1
-    qwait 4
-    bs 4 FL_CW_04 t0  | FL_CW_04 t1
-    qwait 4
-    bs 4 FL_CW_05 t0  | FL_CW_05 t1
-    qwait 4
-    bs 4 FL_CW_06 t0  | FL_CW_06 t1
-    qwait 4
-    bs 4 FL_CW_07 t0  | FL_CW_07 t1
-    qwait 4
+    qwait 20
+    bs 2 FL_CW_00 t0 | FL_CW_00 t1 | FL_CW_00 t2 | FL_CW_00 t3
+    bs 2 FL_CW_01 t0 | FL_CW_01 t1 | FL_CW_01 t2 | FL_CW_01 t3
+    bs 2 FL_CW_02 t0 | FL_CW_02 t1 | FL_CW_02 t2 | FL_CW_02 t3
+    bs 2 FL_CW_03 t0 | FL_CW_03 t1 | FL_CW_03 t2 | FL_CW_03 t3
+    bs 2 FL_CW_04 t0 | FL_CW_04 t1 | FL_CW_04 t2 | FL_CW_04 t3
+    bs 2 FL_CW_05 t0 | FL_CW_05 t1 | FL_CW_05 t2 | FL_CW_05 t3
+    bs 2 FL_CW_06 t0 | FL_CW_06 t1 | FL_CW_06 t2 | FL_CW_06 t3
+    bs 2 FL_CW_07 t0 | FL_CW_07 t1 | FL_CW_07 t2 | FL_CW_07 t3
+    bs 2 CW_01 s7
     br always, start
     nop
     nop

pycqed/analysis/analysis_toolbox.py

@@ -420,6 +420,7 @@ def get_data_from_ma_v2(ma, param_names, numeric_params=None):
                     temp = ma.data_file
                 else:
                     extract_param = False
+                    print(ma.folder)
                     warnings.warn(
                         'The data file attribute %s does not exist or hasn''t been coded for extraction.' % (param))
                 if extract_param:
@@ -433,7 +434,6 @@ def get_data_from_ma_v2(ma, param_names, numeric_params=None):
         if numeric_params is not None:
             if param in numeric_params:
                 data[param] = np.double(data[param])
-
     return data
 
 
@@ -739,6 +739,7 @@ def get_timestamps_in_range(timestamp_start, timestamp_end=None,
                       for dirname in all_measdirs]
         timestamps.reverse()
         all_timestamps += timestamps
+    # print(folder, exact_label_match, all_timestamps, datetime_start, datetime_end, days_delta, all_measdirs)
     # Ensures the order of the timestamps is ascending
     all_timestamps.sort()
     return all_timestamps
@@ -1626,6 +1627,8 @@ def datetime_from_timestamp(timestamp):
             return datetime.datetime.strptime(timestamp, "%Y%m%d%H%M%S")
         elif len(timestamp) == 15:
             return datetime.datetime.strptime(timestamp, "%Y%m%d_%H%M%S")
+        else:
+            raise ValueError
     except Exception as e:
         print('Invalid timestamp :"{}"'.format(timestamp))
         raise e
@@ -1861,8 +1864,10 @@ def linecut_plot(x, y, z, fig, ax,
     z must be a 2D array with shape(len(x),len(y)).
     '''
     colormap = plt.cm.get_cmap('RdYlBu')
-    plt.gca().set_color_cycle([colormap(i) for i in np.linspace(
+    ax.set_prop_cycle('color', [colormap(i) for i in np.linspace(
                               0, 0.9, len(y))])
+
+
     for i in range(len(y)):
         label = '{}: {:.4g} {}'.format(
             y_name, y[i], y_unit)

pycqed/analysis/fitting_models.py

@@ -92,7 +92,7 @@ def TwinLorentzFunc(f, A_gf_over_2, A, f0_gf_over_2, f0,
 def Qubit_dac_to_freq(dac_voltage, f_max, E_c,
                       dac_sweet_spot, V_per_phi0=None,
                       dac_flux_coefficient=None,
-                      asymmetry=0):
+                      asymmetry=0, **kwargs):
     '''
     The cosine Arc model for uncalibrated flux for asymmetric qubit.
 
@@ -122,7 +122,7 @@ def Resonator_dac_to_freq(dac_voltage, f_max_qubit, f_0_res,
                           E_c, dac_sweet_spot,
                           coupling, V_per_phi0=None,
                           dac_flux_coefficient=None,
-                          asymmetry=0):
+                          asymmetry=0, **kwargs):
     qubit_freq = Qubit_dac_to_freq(dac_voltage=dac_voltage, f_max=f_max_qubit, E_c=E_c,
                                    dac_sweet_spot=dac_sweet_spot, V_per_phi0=V_per_phi0,
                                    dac_flux_coefficient=dac_flux_coefficient,
@@ -668,35 +668,53 @@ def arc_guess(freq, dac, dd=0.1):
     return fmax, fmin, dac[dac_ss_index], arc_len
 
 
-def Resonator_dac_arch_guess(model, freq, dac_voltage, f_max_qubit: float = None, E_c: float = None):
-    fmax, fmin, dac_ss, period = arc_guess(freq=freq, dac=dac_voltage)
-    coup_guess = 15e6
+def Resonator_dac_arch_guess(model, data, dac_voltage,
+                             E_c: float = None, values=None):
+    if values is None:
+        values = {}
+
+    fmax, fmin, dac_ss, period = arc_guess(freq=data, dac=dac_voltage)
 
     # todo make better f_res guess
-    f_res = np.mean(freq)  # - (coup_guess ** 2 / (f_max_qubit - fmax))
+    f_res = np.mean(data)  # - (coup_guess ** 2 / (f_max_qubit - fmax))
+    f_res = values.get('f_res', f_res)
+    f_max_qubit = values.get('f_max_qubit', None)
+    dac_ss = values.get('dac_sweet_spot', dac_ss)
+    period = values.get('V_per_phi0', period)
+    EC = values.get('E_c', 260e6)
+    coup_guess = values.get('coup_guess', 15e6)
+    asymmetry = values.get('asymmetry', 0)
+
     f_max_qubit_vary = f_max_qubit is None
     f_max_qubit = f_max_qubit or f_res - 500e6
 
     model.set_param_hint('f_0_res', value=f_res, min=f_res / 2, max=2 * f_res)
     model.set_param_hint('f_max_qubit', value=f_max_qubit, min=3e9, max=8.5e9, vary=f_max_qubit_vary)
     model.set_param_hint('dac_sweet_spot', value=dac_ss, min=(dac_ss - 0.005) / 2, max=2 * (dac_ss + 0.005))
     model.set_param_hint('V_per_phi0', value=period, min=(period - 0.005) / 3, max=5 * (period + 0.005))
-    model.set_param_hint('asymmetry', value=0, max=1, min=-1)
+    model.set_param_hint('asymmetry', value=asymmetry, max=1, min=-1)
     model.set_param_hint('coupling', value=coup_guess, min=1e6, max=80e6)
-    E_c = E_c or 260e6
-    model.set_param_hint('E_c', value=E_c, min=50e6, max=400e6)
+    model.set_param_hint('E_c', value=EC, min=50e6, max=400e6)
 
     params = model.make_params()
     return params
 
 
-def Qubit_dac_arch_guess(model, freq, dac_voltage):
-    fmax, fmin, dac_ss, period = arc_guess(freq=freq, dac=dac_voltage)
+def Qubit_dac_arch_guess(model, data, dac_voltage, values=None):
+    if values is None:
+        values = {}
+    fmax, fmin, dac_ss, period = arc_guess(freq=data, dac=dac_voltage)
+    fmax = values.get('f_max', fmax)
+    dac_ss = values.get('dac_sweet_spot', dac_ss)
+    period = values.get('V_per_phi0', period)
+    EC = values.get('E_c', 260e6)
+    asymmetry = values.get('asymmetry', 0)
+
     model.set_param_hint('f_max', value=fmax, min=0.7 * fmax, max=1.3 * fmax)
     model.set_param_hint('dac_sweet_spot', value=dac_ss, min=(dac_ss - 0.005) / 2, max=2 * (dac_ss + 0.005))
     model.set_param_hint('V_per_phi0', value=period, min=(period - 0.005) / 3, max=5 * (period + 0.005))
-    model.set_param_hint('asymmetry', value=0, max=1, min=-1)
-    model.set_param_hint('E_c', value=260e6, min=50e6, max=400e6)
+    model.set_param_hint('asymmetry', value=asymmetry, max=1, min=-1)
+    model.set_param_hint('E_c', value=EC, min=50e6, max=400e6)
 
     params = model.make_params()
     return params