Fix AEQDSK problems in mapping

Some variables have different names in MDS+ and EFIT which is complicated by the fact that some of the names in MDS+ match the EFIT names but have different or missing data...
gafusion · Jul 20, 2023 · 2a69ca6 · 2a69ca6
1 parent 9ea3801
commit 2a69ca6
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Showing 2 changed files with 31 additions and 24 deletions.
diff --git a/omas/machine_mappings/_efit.json b/omas/machine_mappings/_efit.json
@@ -37,17 +37,25 @@
   "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.GEQDSK.ZBBBS','\\{EFIT_tree}::TOP.RESULTS.GEQDSK.RBBBS',0)",
   "treename": "{EFIT_tree}"
  },
- "equilibrium.time_slice.:.boundary.x_point.:.r": {
+ "equilibrium.time_slice.:.boundary.x_point.0.r": {
   "NANFILTER": true,
-  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RSEPS','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RSEPS',0)",
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT1','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT1',0)",
   "treename": "{EFIT_tree}",
-  "TRANSPOSE": [1,0]
  },
- "equilibrium.time_slice.:.boundary.x_point.:.z": {
+ "equilibrium.time_slice.:.boundary.x_point.1.r": {
   "NANFILTER": true,
-  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZSEPS','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZSEPS',0)",
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT2','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT2',0)",
+  "treename": "{EFIT_tree}",
+ },
+ "equilibrium.time_slice.:.boundary.x_point.0.z": {
+  "NANFILTER": true,
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT1','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT1',0)",
+  "treename": "{EFIT_tree}",
+ },
+ "equilibrium.time_slice.:.boundary.x_point.1.z": {
+  "NANFILTER": true,
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT2','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT2',0)",
   "treename": "{EFIT_tree}",
-  "TRANSPOSE": [1,0]
  },
  "equilibrium.time_slice.:.boundary_separatrix.outline.r": {
   "NANFILTER": true,
@@ -59,28 +67,36 @@
   "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.GEQDSK.ZBBBS','\\{EFIT_tree}::TOP.RESULTS.GEQDSK.RBBBS',0)",
   "treename": "{EFIT_tree}"
  },
- "equilibrium.time_slice.:.boundary_separatrix.x_point.:.r": {
+ "equilibrium.time_slice.:.boundary_separatrix.x_point.0.r": {
+  "NANFILTER": true,
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT1','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT1',0)",
+  "treename": "{EFIT_tree}",
+ },
+ "equilibrium.time_slice.:.boundary_separatrix.x_point.1.r": {
+  "NANFILTER": true,
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT2','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RXPT2',0)",
+  "treename": "{EFIT_tree}",
+ },
+ "equilibrium.time_slice.:.boundary_separatrix.x_point.0.z": {
   "NANFILTER": true,
-  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RSEPS','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RSEPS',0)",
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT1','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT1',0)",
   "treename": "{EFIT_tree}",
-  "TRANSPOSE": [1,0]
  },
- "equilibrium.time_slice.:.boundary_separatrix.x_point.:.z": {
+ "equilibrium.time_slice.:.boundary_separatrix.x_point.1.z": {
   "NANFILTER": true,
-  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZSEPS','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZSEPS',0)",
+  "eval2TDI": "py2tdi(nan_where,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT2','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZXPT2',0)",
   "treename": "{EFIT_tree}",
-  "TRANSPOSE": [1,0]
  },
  "equilibrium.time_slice.:.boundary_separatrix.geometric_axis.r": {
-  "TDI": "data(\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ROUT)/100.",
+  "TDI": "data(\\{EFIT_tree}::TOP.RESULTS.AEQDSK.RSURF)/100.",
   "treename": "{EFIT_tree}"
  },
  "equilibrium.time_slice.:.boundary_separatrix.geometric_axis.z": {
-  "TDI": "data(\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZOUT)/100.",
+  "TDI": "data(\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZSURF)/100.",
   "treename": "{EFIT_tree}"
  },
  "equilibrium.time_slice.:.boundary_separatrix.closest_wall_point.distance": {
-  "eval2TDI": "py2tdi(min_4,'\\{EFIT_tree}::TOP.RESULTS.AEQDSK.GAPIN/100.','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.GAPTOP/100.','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.GAPOUT/100.','\\{EFIT_tree}::TOP.RESULTS.AEQDSK.GAPBOT/100.')",
+  "TDI": "data(\\{EFIT_tree}::TOP.RESULTS.AEQDSK.ZEPLIM)/100.",
   "treename": "{EFIT_tree}"
  },
  "equilibrium.time_slice.:.boundary_separatrix.gap.0.name": {

diff --git a/omas/machine_mappings/python_tdi.py b/omas/machine_mappings/python_tdi.py
@@ -28,15 +28,6 @@ def nan_where(a, b, n):
     a[b == n] = np.NaN
     return a
 
-def min_4_w_scale(a, b, c, d, scale):
-    import numpy as np
-
-    a = a.data()
-    b = b.data()
-    c = c.data()
-    d = d.data()
-    return np.min(np.vstack([a,b,c,d]), axis=0) * scale
-
 def get_largest_axis_value(a, b):
     import numpy as np