Remove biggus test skipper: fix pp field data (#2473)

* pp save return field's data as masked array; fix test to check fill value of cube not data, and cube's dtype * Fix bmdis of fields that were saved from global.pp test data
SciTools · Apr 6, 2017 · c0a77b7 · c0a77b7
1 parent 91eaef6
commit c0a77b7
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Showing 8 changed files with 147 additions and 133 deletions.
diff --git a/lib/iris/etc/pp_save_rules.txt b/lib/iris/etc/pp_save_rules.txt
@@ -761,12 +761,12 @@ THEN
 
 #MDI
 IF
-    ma.isMaskedArray(cm.data)
+    not cm.fill_value is None
 THEN
-    pp.bmdi = cm.data.fill_value
+    pp.bmdi = cm.fill_value
 
 IF
-    not ma.isMaskedArray(cm.data)
+    cm.fill_value is None
 THEN
     pp.bmdi = -1e30
 

diff --git a/lib/iris/fileformats/pp.py b/lib/iris/fileformats/pp.py
@@ -1286,7 +1286,7 @@ def data(self):
             self.bmdi = -9999
         if is_lazy_data(self._data):
             self._data = as_concrete_data(self._data,
-                                          nans_replacement=self.bmdi)
+                                          nans_replacement=ma.masked)
         return self._data
 
     @data.setter

diff --git a/lib/iris/tests/results/cdm/masked_save_pp.txt b/lib/iris/tests/results/cdm/masked_save_pp.txt
@@ -51,124 +51,134 @@
    bdx: 1.0
    bmdi: 123456.0
    bmks: 1.0
-   data.data: [[ 0.          0.          0.          0.          0.          0.64589411
-   0.4375872   0.89177299  0.96366274  0.38344151  0.79172504  0.5288949
-   0.56804454  0.92559665  0.07103606  0.0871293   0.0202184   0.83261985
-   0.77815676  0.87001216]
- [ 0.          0.          0.          0.          0.          0.63992101
-   0.14335328  0.94466889  0.52184832  0.41466194  0.2645556   0.7742337
-   0.45615032  0.56843394  0.0187898   0.61763549  0.61209571  0.616934
-   0.94374806  0.68182027]
- [ 0.          0.          0.          0.          0.          0.67063785
-   0.21038257  0.12892629  0.31542835  0.36371076  0.57019675  0.43860152
-   0.98837382  0.10204481  0.20887676  0.16130951  0.6531083   0.25329161
-   0.46631077  0.24442559]
- [ 0.          0.          0.          0.          0.          0.36872518
-   0.82099324  0.09710128  0.83794492  0.09609841  0.97645944  0.46865121
-   0.9767611   0.60484552  0.73926359  0.03918779  0.28280696  0.12019656
-   0.29614019  0.11872772]
- [ 0.          0.          0.          0.          0.          0.2653895
-   0.52324808  0.09394051  0.57594651  0.9292962   0.31856894  0.66741037
-   0.13179787  0.71632719  0.28940609  0.18319136  0.58651292  0.02010755
-   0.82894003  0.00469548]
- [ 0.67781651  0.27000797  0.73519403  0.96218854  0.24875315  0.57615733
-   0.59204191  0.57225192  0.22308163  0.95274901  0.44712538  0.84640867
-   0.69947928  0.29743695  0.81379783  0.39650574  0.88110322  0.5812729
-   0.88173538  0.69253159]
- [ 0.7252543   0.50132436  0.95608366  0.64399022  0.42385504  0.60639322
-   0.0191932   0.30157483  0.66017354  0.2900776   0.61801541  0.42876869
-   0.13547407  0.29828233  0.56996489  0.59087276  0.57432526  0.65320081
-   0.65210325  0.43141845]
- [ 0.8965466   0.36756188  0.43586493  0.89192337  0.80619401  0.7038886
-   0.10022689  0.91948259  0.71424133  0.99884701  0.14944831  0.86812603
-   0.16249293  0.61555958  0.12381998  0.84800822  0.80731899  0.56910074
-   0.40718329  0.069167  ]
- [ 0.69742876  0.45354268  0.72205561  0.8663823   0.9755215   0.85580337
-   0.01171408  0.35997805  0.72999054  0.17162968  0.52103662  0.05433799
-   0.19999653  0.0185218   0.79369771  0.22392468  0.34535167  0.92808127
-   0.70441443  0.03183893]
- [ 0.16469416  0.62147838  0.57722861  0.23789282  0.934214    0.61396593
-   0.53563279  0.58990997  0.73012203  0.31194499  0.39822108  0.20984375
-   0.186193    0.94437242  0.73955077  0.49045882  0.22741462  0.25435647
-   0.05802916  0.43441662]
- [ 0.31179589  0.69634348  0.37775183  0.17960368  0.02467873  0.06724963
-   0.67939276  0.45369685  0.53657919  0.8966713   0.99033892  0.21689698
-   0.66307819  0.26332238  0.020651    0.75837862  0.32001716  0.38346389
-   0.5883171   0.83104843]
- [ 0.62898183  0.87265068  0.27354205  0.79804683  0.18563594  0.95279163
-   0.68748826  0.21550767  0.94737059  0.73085582  0.25394166  0.21331197
-   0.5182007   0.02566272  0.20747007  0.42468548  0.37416998  0.46357542
-   0.27762872  0.58678436]
- [ 0.8638556   0.11753186  0.51737911  0.13206811  0.7168597   0.39605969
-   0.56542128  0.18327984  0.14484777  0.48805627  0.35561273  0.94043195
-   0.76532525  0.7486636   0.90371972  0.08342244  0.55219245  0.58447605
-   0.96193635  0.29214752]
- [ 0.24082878  0.10029394  0.01642963  0.92952931  0.66991657  0.78515291
-   0.28173012  0.58641016  0.06395527  0.48562759  0.97749513  0.87650526
-   0.33815897  0.96157014  0.23170163  0.94931883  0.9413777   0.79920256
-   0.63044792  0.87428796]
- [ 0.29302028  0.84894353  0.61787671  0.01323686  0.3472335   0.14814086
-   0.9818294   0.47837031  0.49739137  0.63947254  0.3685846   0.13690028
-   0.82211775  0.18984792  0.51131898  0.22431703  0.09784448  0.8621915
-   0.97291946  0.96083468]
- [ 0.90655547  0.77404732  0.33314514  0.08110139  0.40724117  0.23223414
-   0.13248764  0.05342718  0.72559434  0.01142746  0.77058077  0.14694664
-   0.07952208  0.08960304  0.67204779  0.24536721  0.42053947  0.55736881
-   0.86055118  0.72704428]
- [ 0.2703279   0.13148279  0.05537432  0.30159864  0.26211816  0.45614058
-   0.68328136  0.69562542  0.28351885  0.37992695  0.18115096  0.78854549
-   0.05684808  0.69699723  0.7786954   0.77740759  0.25942257  0.37381315
-   0.58759964  0.2728219 ]
- [ 0.3708528   0.19705428  0.45985588  0.0446123   0.79979587  0.07695644
-   0.51883513  0.30681011  0.57754296  0.95943332  0.64557022  0.03536244
-   0.43040243  0.51001686  0.53617752  0.68139249  0.27759609  0.12886056
-   0.39267567  0.9564057 ]
- [ 0.1871309   0.90398395  0.54380596  0.45691141  0.88204139  0.45860395
-   0.72416764  0.39902532  0.90404439  0.69002503  0.69962204  0.3277204
-   0.75677866  0.63606107  0.24002028  0.16053882  0.79639149  0.95916659
-   0.45813882  0.59098417]
- [ 0.85772264  0.45722345  0.95187449  0.57575119  0.8207671   0.9088437
-   0.8155238   0.15941447  0.62889844  0.39843425  0.06271295  0.42403224
-   0.25868407  0.8490383   0.03330463  0.95898271  0.35536885  0.35670689
-   0.0163285   0.18523233]]
-   data.mask: [[ True  True  True  True  True False False False False False False False
-  False False False False False False False False]
- [ True  True  True  True  True False False False False False False False
-  False False False False False False False False]
- [ True  True  True  True  True False False False False False False False
-  False False False False False False False False]
- [ True  True  True  True  True False False False False False False False
-  False False False False False False False False]
- [ True  True  True  True  True False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]
- [False False False False False False False False False False False False
-  False False False False False False False False]]
+   data: [[-- -- -- -- -- 0.6458941102027893 0.4375872015953064 0.891772985458374
+  0.9636627435684204 0.3834415078163147 0.7917250394821167
+  0.5288949012756348 0.5680445432662964 0.9255966544151306
+  0.07103605568408966 0.08712930232286453 0.020218396559357643
+  0.832619845867157 0.7781567573547363 0.8700121641159058]
+ [-- -- -- -- -- 0.6399210095405579 0.14335328340530396 0.9446688890457153
+  0.5218483209609985 0.4146619439125061 0.26455560326576233
+  0.7742336988449097 0.4561503231525421 0.568433940410614
+  0.018789799883961678 0.6176354885101318 0.6120957136154175
+  0.6169340014457703 0.9437480568885803 0.681820273399353]
+ [-- -- -- -- -- 0.670637845993042 0.21038256585597992 0.12892629206180573
+  0.31542834639549255 0.36371076107025146 0.5701967477798462
+  0.4386015236377716 0.9883738160133362 0.10204481333494186
+  0.20887675881385803 0.16130951046943665 0.6531082987785339
+  0.25329160690307617 0.4663107693195343 0.24442559480667114]
+ [-- -- -- -- -- 0.3687251806259155 0.8209932446479797 0.09710127860307693
+  0.8379449248313904 0.0960984081029892 0.9764594435691833
+  0.4686512053012848 0.9767611026763916 0.6048455238342285
+  0.7392635941505432 0.03918779268860817 0.28280696272850037
+  0.12019655853509903 0.296140193939209 0.11872772127389908]
+ [-- -- -- -- -- 0.26538950204849243 0.5232480764389038 0.09394051134586334
+  0.5759465098381042 0.9292961955070496 0.3185689449310303
+  0.6674103736877441 0.13179786503314972 0.7163271903991699
+  0.28940609097480774 0.18319135904312134 0.5865129232406616
+  0.02010754682123661 0.8289400339126587 0.004695476032793522]
+ [0.6778165102005005 0.2700079679489136 0.7351940274238586
+  0.9621885418891907 0.2487531453371048 0.5761573314666748
+  0.5920419096946716 0.5722519159317017 0.22308163344860077
+  0.9527490139007568 0.4471253752708435 0.8464086651802063
+  0.6994792819023132 0.2974369525909424 0.8137978315353394
+  0.396505743265152 0.8811032176017761 0.5812729001045227
+  0.8817353844642639 0.6925315856933594]
+ [0.7252542972564697 0.5013243556022644 0.9560836553573608
+  0.6439902186393738 0.4238550364971161 0.6063932180404663
+  0.019193198531866074 0.30157482624053955 0.6601735353469849
+  0.2900775969028473 0.6180154085159302 0.42876869440078735
+  0.1354740709066391 0.29828232526779175 0.5699648857116699
+  0.5908727645874023 0.5743252635002136 0.6532008051872253
+  0.6521032452583313 0.43141844868659973]
+ [0.8965466022491455 0.36756187677383423 0.4358649253845215
+  0.8919233679771423 0.806194007396698 0.7038885951042175
+  0.10022688657045364 0.9194825887680054 0.7142413258552551
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+  0.16249293088912964 0.6155595779418945 0.1238199844956398
+  0.8480082154273987 0.8073189854621887 0.5691007375717163
+  0.40718328952789307 0.06916699558496475]
+ [0.6974287629127502 0.45354267954826355 0.7220556139945984
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+  0.011714084073901176 0.359978049993515 0.729990541934967
+  0.17162968218326569 0.5210366249084473 0.054337989538908005
+  0.19999653100967407 0.01852179504930973 0.793697714805603
+  0.2239246815443039 0.3453516662120819 0.9280812740325928
+  0.704414427280426 0.031838931143283844]
+ [0.1646941602230072 0.6214783787727356 0.5772286057472229
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+  0.5356327891349792 0.5899099707603455 0.7301220297813416
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+  0.49045881628990173 0.22741462290287018 0.2543564736843109
+  0.058029159903526306 0.43441662192344666]
+ [0.3117958903312683 0.6963434815406799 0.37775182723999023
+  0.1796036809682846 0.024678727611899376 0.06724963337182999
+  0.6793927550315857 0.4536968469619751 0.5365791916847229
+  0.8966712951660156 0.990338921546936 0.21689698100090027
+  0.6630781888961792 0.2633223831653595 0.02065099962055683
+  0.7583786249160767 0.32001715898513794 0.38346388936042786
+  0.5883170962333679 0.8310484290122986]
+ [0.6289818286895752 0.872650682926178 0.27354204654693604
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+  0.6874882578849792 0.21550767123699188 0.9473705887794495
+  0.7308558225631714 0.2539416551589966 0.21331197023391724
+  0.518200695514679 0.02566271834075451 0.20747007429599762
+  0.4246854782104492 0.3741699755191803 0.46357542276382446
+  0.27762871980667114 0.5867843627929688]
+ [0.8638556003570557 0.11753185838460922 0.517379105091095
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+  0.5654212832450867 0.1832798421382904 0.14484776556491852
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+  0.7653252482414246 0.748663604259491 0.9037197232246399
+  0.08342243731021881 0.5521924495697021 0.5844760537147522
+  0.961936354637146 0.29214751720428467]
+ [0.24082878232002258 0.10029394179582596 0.016429629176855087
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+  0.28173011541366577 0.5864101648330688 0.06395526975393295
+  0.48562759160995483 0.9774951338768005 0.8765052556991577
+  0.3381589651107788 0.961570143699646 0.23170162737369537
+  0.9493188261985779 0.9413776993751526 0.799202561378479
+  0.6304479241371155 0.8742879629135132]
+ [0.2930202782154083 0.8489435315132141 0.6178767085075378
+  0.013236857950687408 0.34723350405693054 0.14814086258411407
+  0.9818294048309326 0.4783703088760376 0.49739137291908264
+  0.6394725441932678 0.36858460307121277 0.13690027594566345
+  0.8221177458763123 0.1898479163646698 0.5113189816474915
+  0.2243170291185379 0.09784448146820068 0.8621914982795715
+  0.9729194641113281 0.9608346819877625]
+ [0.9065554738044739 0.774047315120697 0.3331451416015625
+  0.08110138773918152 0.40724116563796997 0.2322341352701187
+  0.13248763978481293 0.053427182137966156 0.7255943417549133
+  0.011427458375692368 0.7705807685852051 0.14694663882255554
+  0.07952208071947098 0.08960303664207458 0.6720477938652039
+  0.24536721408367157 0.4205394685268402 0.557368814945221
+  0.8605511784553528 0.7270442843437195]
+ [0.2703278958797455 0.131482794880867 0.05537432059645653
+  0.3015986382961273 0.2621181607246399 0.45614057779312134
+  0.6832813620567322 0.6956254243850708 0.28351885080337524
+  0.3799269497394562 0.18115095794200897 0.7885454893112183
+  0.05684807524085045 0.6969972252845764 0.7786954045295715
+  0.7774075865745544 0.25942257046699524 0.3738131523132324
+  0.5875996351242065 0.27282190322875977]
+ [0.3708527982234955 0.19705428183078766 0.4598558843135834
+  0.044612299650907516 0.7997958660125732 0.07695644348859787
+  0.5188351273536682 0.3068101108074188 0.5775429606437683
+  0.9594333171844482 0.6455702185630798 0.03536243736743927
+  0.4304024279117584 0.5100168585777283 0.5361775159835815 0.6813924908638
+  0.2775960862636566 0.12886056303977966 0.3926756680011749
+  0.9564056992530823]
+ [0.1871308982372284 0.9039839506149292 0.5438059568405151
+  0.4569114148616791 0.8820413947105408 0.45860394835472107
+  0.7241676449775696 0.3990253210067749 0.9040443897247314
+  0.6900250315666199 0.6996220350265503 0.32772040367126465
+  0.7567786574363708 0.6360610723495483 0.2400202751159668
+  0.16053882241249084 0.796391487121582 0.9591665863990784
+  0.4581388235092163 0.5909841656684875]
+ [0.8577226400375366 0.45722344517707825 0.9518744945526123
+  0.5757511854171753 0.8207671046257019 0.9088436961174011
+  0.8155238032341003 0.15941447019577026 0.6288984417915344
+  0.39843425154685974 0.06271295249462128 0.4240322411060333
+  0.25868406891822815 0.849038302898407 0.03330462798476219
+  0.9589827060699463 0.35536885261535645 0.3567068874835968
+  0.01632850244641304 0.18523232638835907]]
 ]
diff --git a/lib/iris/tests/results/cube_to_pp/append_single.txt b/lib/iris/tests/results/cube_to_pp/append_single.txt
@@ -49,7 +49,7 @@
    bdy: -2.5
    bzx: -3.75
    bdx: 3.75
-   bmdi: -1e+30
+   bmdi: 9999.0
    bmks: 1.0
    data: [[ 254.64399719  254.64399719  254.64399719 ...,  254.64399719
    254.64399719  254.64399719]
@@ -115,7 +115,7 @@
    bdy: -2.5
    bzx: -3.75
    bdx: 3.75
-   bmdi: -1e+30
+   bmdi: 9999.0
    bmks: 1.0
    data: [[ 254.64399719  254.64399719  254.64399719 ...,  254.64399719
    254.64399719  254.64399719]

diff --git a/lib/iris/tests/results/cube_to_pp/replace_single.txt b/lib/iris/tests/results/cube_to_pp/replace_single.txt
@@ -49,7 +49,7 @@
    bdy: -2.5
    bzx: -3.75
    bdx: 3.75
-   bmdi: -1e+30
+   bmdi: 9999.0
    bmks: 1.0
    data: [[ 254.64399719  254.64399719  254.64399719 ...,  254.64399719
    254.64399719  254.64399719]

diff --git a/lib/iris/tests/results/cube_to_pp/simple.txt b/lib/iris/tests/results/cube_to_pp/simple.txt
@@ -49,7 +49,7 @@
    bdy: -2.5
    bzx: -3.75
    bdx: 3.75
-   bmdi: -1e+30
+   bmdi: 9999.0
    bmks: 1.0
    data: [[ 254.64399719  254.64399719  254.64399719 ...,  254.64399719
    254.64399719  254.64399719]

diff --git a/lib/iris/tests/results/cube_to_pp/user_rules.txt b/lib/iris/tests/results/cube_to_pp/user_rules.txt
@@ -49,7 +49,7 @@
    bdy: -2.5
    bzx: -3.75
    bdx: 3.75
-   bmdi: -1e+30
+   bmdi: 9999.0
    bmks: 1.0
    data: [[ 254.64399719  254.64399719  254.64399719 ...,  254.64399719
    254.64399719  254.64399719]

diff --git a/lib/iris/tests/test_cdm.py b/lib/iris/tests/test_cdm.py
@@ -1175,28 +1175,32 @@ def test_slicing(self):
         self.assertIsInstance(partial_slice.data, ma.core.MaskedArray)
         self.assertEqual(ma.count_masked(partial_slice.data), 25)
 
-    @tests.skip_biggus
     def test_save_and_merge(self):
         cube = self._load_3d_cube()
+        dtype = cube.dtype
+        fill_value = 123456
 
         # extract the 2d field that has SOME missing values
         masked_slice = cube[0]
-        masked_slice.data.fill_value = 123456
+        masked_slice.fill_value = fill_value
 
         # test saving masked data
         reference_txt_path = tests.get_result_path(('cdm', 'masked_save_pp.txt'))
         with self.cube_save_test(reference_txt_path, reference_cubes=masked_slice) as temp_pp_path:
             iris.save(masked_slice, temp_pp_path)
-        
+
             # test merge keeps the mdi we just saved
             cube1 = iris.load_cube(temp_pp_path)
+            self.assertEqual(cube1.dtype, dtype)
+
             cube2 = cube1.copy()
             # make cube1 and cube2 differ on a scalar coord, to make them mergeable into a 3d cube
             cube2.coord("pressure").points = [1001.0]
             merged_cubes = iris.cube.CubeList([cube1, cube2]).merge()
             self.assertEqual(len(merged_cubes), 1, "expected a single merged cube")
             merged_cube = merged_cubes[0]
-            self.assertEqual(merged_cube.data.fill_value, 123456)
+            self.assertEqual(merged_cube.dtype, dtype)
+            self.assertEqual(merged_cube.fill_value, fill_value)
 
 
 @tests.skip_data