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Commit 780fac25 authored by Thibault Hallouin's avatar Thibault Hallouin
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include newly added prob. metric CONT_TBL in evalhyd-cpp

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xtensor @ 44b56bba
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Subproject commit e534928cc30eb3a4a05539747d98e1d6868c2d62 Subproject commit 44b56bbae2185ebf19e6f617ac5690344b9e35a4
environment.yml
+ 1
− 1
View file @ 780fac25
...@@ -12,7 +12,7 @@ dependencies: ...@@ -12,7 +12,7 @@ dependencies:
- numpy - numpy
- pybind11 - pybind11
- xtl==0.7.5 - xtl==0.7.5
- xtensor==0.24.6 - xtensor==0.24.7
- xtensor-python==0.26.1 - xtensor-python==0.26.1
# - evalhyd-cpp==0.1.0 # - evalhyd-cpp==0.1.0
# Test dependencies # Test dependencies
......
tests/expected/evalp/CONT_TBL.csv 0 → 100644
+ 208
− 0
View file @ 780fac25
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0.33118971,0.66881029,0.,0.
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0.28938907,0.02572347,0.04180064,0.64308682
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0.28938907,0.02572347,0.04180064,0.64308682
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0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
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0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
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0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
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0.28938907,0.02572347,0.04180064,0.64308682
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
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0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
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0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
0.38585209,0.04501608,0.06109325,0.50803859
0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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0.28938907,0.02572347,0.04180064,0.64308682
0.20578778,0.0192926,0.06752412,0.7073955
nan,nan,nan,nan
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tests/test_probabilist.py
+ 7
− 2
View file @ 780fac25
...@@ -20,7 +20,7 @@ _all_metrics = ( ...@@ -20,7 +20,7 @@ _all_metrics = (
# quantile-based # quantile-based
'QS', 'CRPS_FROM_QS', 'QS', 'CRPS_FROM_QS',
# contingency table-based # contingency table-based
'POD', 'POFD', 'FAR', 'CSI', 'ROCSS', 'CONT_TBL', 'POD', 'POFD', 'FAR', 'CSI', 'ROCSS',
# ranks-based # ranks-based
'RANK_HIST', 'DS', 'AS', 'RANK_HIST', 'DS', 'AS',
# intervals # intervals
...@@ -68,8 +68,13 @@ class TestMetrics(unittest.TestCase): ...@@ -68,8 +68,13 @@ class TestMetrics(unittest.TestCase):
metric: ( metric: (
numpy.genfromtxt(f"./expected/evalp/{metric}.csv", delimiter=',') numpy.genfromtxt(f"./expected/evalp/{metric}.csv", delimiter=',')
[numpy.newaxis, numpy.newaxis, numpy.newaxis, numpy.newaxis, ...] [numpy.newaxis, numpy.newaxis, numpy.newaxis, numpy.newaxis, ...]
) for metric in ('POD', 'POFD', 'FAR', 'CSI', 'ROCSS') ) for metric in ('CONT_TBL', 'POD', 'POFD', 'FAR', 'CSI', 'ROCSS')
} }
# /!\ stacked-up thresholds in CSV file for CONT_TBL
# because 7D metric so need to reshape array
expected_ct['CONT_TBL'] = (
expected_ct['CONT_TBL'].reshape(expected_ct['POD'].shape + (4,))
)
expected_rk = { expected_rk = {
metric: ( metric: (
......
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