Merge pull request #1041 from seanaqyoung/themis_state_support_fix

Propagating suffix to dataname strings throughout THEMIS spinmodel when loading state data.

pyspedas/projects/themis/state/spinmodel/spinmodel.py

@@ -10,7 +10,8 @@
 
 def get_sm_data(probe: str,
                 valname: str,
-                correction_level: int) -> (np.ndarray, np.ndarray):
+                correction_level: int,
+                suffix: str = '') -> (np.ndarray, np.ndarray):
     """ Return the times and values for a spin model tplot variable
 
     Args:
@@ -25,7 +26,7 @@ def get_sm_data(probe: str,
         infix = '_'
     else:
         infix = '_ecl_'
-    tvar_name = 'th' + probe + '_spin' + infix + valname
+    tvar_name = 'th' + probe + '_spin' + infix + valname + suffix
     if data_exists(tvar_name):
         res = get_data(tvar_name)
         return res.times, res.y
@@ -556,7 +557,8 @@ def get_eclipse_times(self, min_shadow_duration:float=60.0):
 
     def __init__(self,
                  probe,
-                 correction_level):
+                 correction_level,
+                 suffix=''):
         self.lastseg = SpinmodelSegment(t1=0.0, t2=0.0, c1=0, c2=0, b=0.0, c=0.0, npts=0, maxgap=0.0, phaserr=0.0,
                                         initial_delta_phi=0.0, idpu_spinper=0.0, segflags=0)
         self.seg_times = np.zeros(1, float)
@@ -573,18 +575,18 @@ def __init__(self,
         self.seg_segflags = np.zeros(1, int)
         self.seg_count = 0
         self.seg_list = []
-        seg_times, tend_data = get_sm_data(probe, 'tend', correction_level)
-        t, spinper_data = get_sm_data(probe, 'spinper', correction_level)
-        t, c_data = get_sm_data(probe, 'c', correction_level)
-        t, phaserr_data = get_sm_data(probe, 'phaserr', correction_level)
-        t, nspins_data = get_sm_data(probe, 'nspins', correction_level)
-        t, npts_data = get_sm_data(probe, 'npts', correction_level)
-        t, maxgap_data = get_sm_data(probe, 'maxgap', correction_level)
-        t, initial_delta_phi_data = get_sm_data(probe, 'initial_delta_phi', correction_level)
-        t, idpu_spinper_data = get_sm_data(probe, 'idpu_spinper', correction_level)
-        t, segflags_data = get_sm_data(probe, 'segflags', correction_level)
+        seg_times, tend_data = get_sm_data(probe, 'tend', correction_level, suffix)
+        _, spinper_data = get_sm_data(probe, 'spinper', correction_level, suffix)
+        _, c_data = get_sm_data(probe, 'c', correction_level, suffix)
+        _, phaserr_data = get_sm_data(probe, 'phaserr', correction_level, suffix)
+        _, nspins_data = get_sm_data(probe, 'nspins', correction_level, suffix)
+        _, npts_data = get_sm_data(probe, 'npts', correction_level, suffix)
+        _, maxgap_data = get_sm_data(probe, 'maxgap', correction_level, suffix)
+        _, initial_delta_phi_data = get_sm_data(probe, 'initial_delta_phi', correction_level, suffix)
+        _, idpu_spinper_data = get_sm_data(probe, 'idpu_spinper', correction_level, suffix)
+        _, segflags_data = get_sm_data(probe, 'segflags', correction_level, suffix)
         # The spin_correction variable only exists in V03 state CDFs, and has its own time variable
-        tmp = get_sm_data(probe, 'correction', 0)
+        tmp = get_sm_data(probe, 'correction', 0, suffix)
         if tmp is None:
             logging.info('spin_correction variable not available, defaulting to 0.0')
             self.spin_corr_times = [0.0, 1.0]
@@ -593,14 +595,14 @@ def __init__(self,
             self.spin_corr_times, self.spin_corr_vals = tmp
 
         # The fgm_corr_offset and fgm_corr_tend variables may not exist, and have their own time variable
-        tmp = get_sm_data(probe, 'fgm_corr_offset', correction_level)
+        tmp = get_sm_data(probe, 'fgm_corr_offset', correction_level, suffix)
         if tmp is None:
             do_fgm_corr = False
             logging.info('FGM correction variables not available')
         else:
             do_fgm_corr = True
             fgm_corr_time, fgm_corr_offset = tmp
-            t, fgm_corr_tend = get_sm_data(probe, 'fgm_corr_tend', correction_level)
+            _, fgm_corr_tend = get_sm_data(probe, 'fgm_corr_tend', correction_level, suffix)
 
         seg_count = len(seg_times)
         # tlast = seg_times[0]

pyspedas/projects/themis/state/spinmodel/spinmodel_postprocess.py

@@ -3,7 +3,7 @@
 from pytplot import data_exists
 
 
-def spinmodel_postprocess(probe: str):
+def spinmodel_postprocess(probe: str, suffix: str=''):
     """ Create and initialize three Spinmodel objects using tplot variables loaded from the STATE CDFs.
 
         The three models correspond to the three available correction levels: 0 = no corrections, 1 = waveform
@@ -24,8 +24,8 @@ def spinmodel_postprocess(probe: str):
                      'segflags']
     missing_var = False
     for v in sm_quantities:
-        non_ecl_v = 'th' + probe + '_spin_' + v
-        ecl_v = 'th' + probe + '_spin_ecl_' + v
+        non_ecl_v = 'th' + probe + '_spin_' + v + suffix
+        ecl_v = 'th' + probe + '_spin_ecl_' + v + suffix
         if not (data_exists(non_ecl_v) and data_exists(ecl_v)):
             missing_var = True
 
@@ -36,11 +36,11 @@ def spinmodel_postprocess(probe: str):
     logging.info("Creating spin model for probe " + probe + " correction level 0")
     # Expect a warning message here: That name is currently not in tplot.
     # Maybe there's a better idiom in pytplot for checking whether a variable exists?
-    model0 = Spinmodel(probe, 0)
+    model0 = Spinmodel(probe, 0, suffix)
     save_spinmodel(probe, 0, model0)
     logging.info("Creating spin model for probe " + probe + " correction level 1")
-    model1 = Spinmodel(probe, 1)
+    model1 = Spinmodel(probe, 1, suffix)
     save_spinmodel(probe, 1, model1)
     logging.info("Creating spin model for probe " + probe + " correction level 2")
-    model2 = Spinmodel(probe, 2)
+    model2 = Spinmodel(probe, 2, suffix)
     save_spinmodel(probe, 2, model2)

pyspedas/projects/themis/state/state.py

@@ -115,18 +115,18 @@ def state(trange=['2007-03-23', '2007-03-24'],
     if get_support_data:
         for p in probe:
             # Process spin model variables
-            spinmodel_postprocess(p)
+            spinmodel_postprocess(p,suffix)
             if not keep_spin:
                 spinvar_pattern = 'th' + p + '_spin_*'
                 del_data(spinvar_pattern)
             # Perform spin axis RA and Dec corrections
-            spinras_var = 'th' + p + '_spinras'
-            delta_spinras_var = 'th' + p + '_spinras_correction'
-            corrected_spinras_var = 'th' + p + '_spinras_corrected'
+            spinras_var = 'th' + p + '_spinras' + suffix
+            delta_spinras_var = 'th' + p + '_spinras_correction' + suffix
+            corrected_spinras_var = 'th' + p + '_spinras_corrected' + suffix
 
-            spindec_var = 'th' + p + '_spindec'
-            delta_spindec_var = 'th' + p + '_spindec_correction'
-            corrected_spindec_var = 'th' + p + '_spindec_corrected'
+            spindec_var = 'th' + p + '_spindec' + suffix
+            delta_spindec_var = 'th' + p + '_spindec_correction' + suffix
+            corrected_spindec_var = 'th' + p + '_spindec_corrected' + suffix
 
             apply_spinaxis_corrections(spinras=spinras_var, delta_spinras=delta_spinras_var,
                                        corrected_spinras=corrected_spinras_var, spindec=spindec_var,