Model skill visualisation

import modelskill as ms

Model skill visualisation#

fn = 'data/SW/HKZN_local_2017_DutchCoast.dfsu'
mr = ms.model_result(fn, name='HKZN_local', item=0)

obs = [ms.PointObservation('data/SW/HKZA_Hm0.dfs0', item=0, x=3.9, y=52.7, name="HKZA"),
        ms.PointObservation('data/SW/HKZA_Hm0.dfs0', item=0, x=3.8, y=52.5, name="HKZA_2"),
        ms.PointObservation('data/SW/HKZA_Hm0.dfs0', item=0, x=3.5, y=52.6, name="HKZA_3"),
        ms.PointObservation('data/SW/HKNA_Hm0.dfs0', item=0, x=4.2420, y=52.6887, name="HKNA"),
        ms.PointObservation('data/SW/HKNA_Hm0.dfs0', item=0, x=4.2, y=52.6, name="HKNA_2"),
        ms.PointObservation('data/SW/HKNA_Hm0.dfs0', item=0, x=4.3, y=52.7, name="HKNA_3"),
        ms.PointObservation("data/SW/eur_Hm0.dfs0", item=0, x=3.2760, y=51.9990, name="EPL"),
        ms.PointObservation("data/SW/eur_Hm0.dfs0", item=0, x=3.2, y=51.9, name="EPL_2"),
        ms.PointObservation("data/SW/eur_Hm0.dfs0", item=0, x=3.3, y=51.95, name="EPL_3")
]

cc = ms.match(obs=obs, mod=mr)
cc

/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(
/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/mikeio/dataset/_dataset.py:505: FutureWarning: 'inplace' parameter is deprecated and will be removed in future versions. Use ds = ds.rename(...) instead.
  warnings.warn(

<ComparerCollection>
Comparers:
0: HKZA - Significant wave height [m]
1: HKZA_2 - Significant wave height [m]
2: HKZA_3 - Significant wave height [m]
3: HKNA - Significant wave height [m]
4: HKNA_2 - Significant wave height [m]
5: HKNA_3 - Significant wave height [m]
6: EPL - Significant wave height [m]
7: EPL_2 - Significant wave height [m]
8: EPL_3 - Significant wave height [m]

Data analysis#

cc.skill()

/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/modelskill/metrics.py:344: RuntimeWarning: divide by zero encountered in scalar divide
  return 1 - SSr / SSt
n bias rmse urmse mae cc si r2
observation
HKZA 1 0.546863 0.546863 0.0 0.546863 NaN 0.0 -inf
HKZA_2 1 0.527374 0.527374 0.0 0.527374 NaN 0.0 -inf
HKZA_3 1 0.523389 0.523389 0.0 0.523389 NaN 0.0 -inf
HKNA 1 0.186511 0.186511 0.0 0.186511 NaN 0.0 -inf
HKNA_2 1 0.164091 0.164091 0.0 0.164091 NaN 0.0 -inf
HKNA_3 1 0.172111 0.172111 0.0 0.172111 NaN 0.0 -inf
EPL 1 0.518057 0.518057 0.0 0.518057 NaN 0.0 -inf
EPL_2 1 0.474516 0.474516 0.0 0.474516 NaN 0.0 -inf
EPL_3 1 0.508518 0.508518 0.0 0.508518 NaN 0.0 -inf 
s = cc.skill()
type(s)

/opt/hostedtoolcache/Python/3.13.12/x64/lib/python3.13/site-packages/modelskill/metrics.py:344: RuntimeWarning: divide by zero encountered in scalar divide
  return 1 - SSr / SSt

modelskill.skill.SkillTable

s.rmse.plot.bar();
_images/b24a8e26d5e1a002dc2204d2b3f0bb5353f6e11b0d31624a62f9ab0a4ea9de23.png 
s['urmse'].plot.line();
_images/eba9f3fedcc56786a1f422dcff64a9d91a640216f955fe4edd91155967edf6c8.png

Custom plot#

All skill statistics are available in a dataframe, and in case you need a tailor-made plot, you can get data and use matplotlib to get exactly what you need.

import matplotlib.pyplot as plt

df = s.to_dataframe().sort_values('bias')
x = df.bias
y = df.index

plt.subplots(figsize=(6,6))
plt.scatter(x,y,marker='D',c='red',s=100)
plt.xlim(-0.35,0.35)
plt.axvline(0,linestyle='--')
plt.xlabel("Bias (m)")
plt.title(mr.name)
plt.grid()
_images/136627751519ab730e367bd2b93b6ec2e98acf2d9a8ae2e377322b7c972052f8.png
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