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heptaflarheptaflar
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Fix: clear figures eventually
1 parent e4b31f8 commit 62c770c

4 files changed

Lines changed: 63 additions & 63 deletions

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‎wqf/val/mov.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -45,7 +45,7 @@ def plot_analysis(chl: DataArray, period: Period):
4545
xlocs=(1.0, 2.5, 4.0, 5.5, 7.0, 8.5, 10.0),
4646
vmin=0.0,
4747
vmax=100.0,
48-
)
48+
).clear()
4949

5050

5151
def plot_forecast(
@@ -76,7 +76,7 @@ def plot_forecast(
7676
xlocs=(1.0, 2.5, 4.0, 5.5, 7.0, 8.5, 10.0),
7777
vmin=0.0,
7878
vmax=100.0,
79-
)
79+
).clear()
8080

8181

8282
def plot_observed(chl: DataArray, period: Period, fwhm: Number | None):
@@ -105,7 +105,7 @@ def plot_observed(chl: DataArray, period: Period, fwhm: Number | None):
105105
xlocs=(1.0, 2.5, 4.0, 5.5, 7.0, 8.5, 10.0),
106106
vmin=0.0,
107107
vmax=100.0,
108-
)
108+
).clear()
109109

110110

111111
def generate_figures(args):

‎wqf/val/pvp.py‎

Lines changed: 21 additions & 21 deletions
Original file line numberDiff line numberDiff line change
@@ -429,88 +429,88 @@ def generate_figures(args, period: tuple[int, int]):
429429
"Mockup chlorophyll forecast",
430430
"bias_mockup_series",
431431
xlim=period,
432-
)
432+
).clear()
433433
plot_bias_scene(
434434
Bias().image(ref, pre),
435435
"Mockup chlorophyll forecast",
436436
"bias_mockup_image",
437-
)
437+
).clear()
438438
plot_error_histogram(
439439
Bias.err(ref, pre),
440440
"Mockup chlorophyll forecast",
441441
"err_mockup_hist",
442-
)
442+
).clear()
443443
plot_relative_error_histogram(
444444
Bias.rer(ref, pre, condition=ref > 1.0),
445445
"Mockup chlorophyll forecast",
446446
"rer_mockup_hist",
447-
)
447+
).clear()
448448

449449
plot_count_scene(
450450
Count().image(ref, pre),
451451
"Mockup chlorophyll forecast",
452452
"count_mockup_image",
453-
)
453+
).clear()
454454

455455
plot_determination_coefficient_time_series(
456456
R2().series(ref, pre),
457457
"Mockup chlorophyll forecast",
458458
"det_mockup_series",
459459
xlim=period,
460-
)
460+
).clear()
461461
plot_determination_coefficient_scene(
462462
R2().image(ref, pre),
463463
"Mockup chlorophyll forecast",
464464
"det_mockup_image",
465-
)
465+
).clear()
466466

467467
plot_mad_time_series(
468468
MAD().series(ref, pre),
469469
"Mockup chlorophyll forecast",
470470
"mad_mockup_series",
471471
xlim=period,
472-
)
472+
).clear()
473473
plot_mad_scene(
474474
MAD().image(ref, pre),
475475
"Mockup chlorophyll forecast",
476476
"mad_mockup_image",
477-
)
477+
).clear()
478478

479479
plot_mapd_time_series(
480480
MAPD().series(ref, pre, condition=ref > 1.0),
481481
"Mockup chlorophyll forecast",
482482
"mapd_mockup_series",
483483
xlim=period,
484-
)
484+
).clear()
485485
plot_mapd_scene(
486486
MAPD().image(ref, pre, condition=ref > 1.0),
487487
"Mockup chlorophyll forecast",
488488
"mapd_mockup_image",
489-
)
489+
).clear()
490490

491491
plot_rmse_time_series(
492492
RMSE().series(ref, pre),
493493
"Mockup chlorophyll forecast",
494494
"rmse_mockup_series",
495495
xlim=period,
496-
)
496+
).clear()
497497
plot_rmse_scene(
498498
RMSE().image(ref, pre),
499499
"Mockup chlorophyll forecast",
500500
"rmse_mockup_image",
501-
)
501+
).clear()
502502

503503
plot_wrmsse_time_series(
504504
WRMSSE().series(ref, pre, condition=ref > 1.0),
505505
"Mockup chlorophyll forecast",
506506
"wrmsse_mockup_series",
507507
xlim=period,
508-
)
508+
).clear()
509509
plot_wrmsse_scene(
510510
WRMSSE().image(ref, pre, condition=ref > 1.0),
511511
"Mockup chlorophyll forecast",
512512
"wrmsse_mockup_image",
513-
)
513+
).clear()
514514

515515
x = ref.loc[f"{period[0]}-01-01" :f"{period[1]}-01-01", :, :]
516516
y = pre.loc[f"{period[0]}-01-01" :f"{period[1]}-01-01", :, :]
@@ -519,32 +519,32 @@ def generate_figures(args, period: tuple[int, int]):
519519
(x, y),
520520
"Mockup chlorophyll forecast",
521521
"val_mockup_density",
522-
)
522+
).clear()
523523
plot_value_scatter(
524524
(x, y),
525525
"Mockup chlorophyll forecast",
526526
"val_mockup_scatter",
527-
)
527+
).clear()
528528
plot_error_density(
529529
(x, y - x),
530530
"Mockup chlorophyll forecast",
531531
"err_mockup_density",
532-
)
532+
).clear()
533533
plot_error_scatter(
534534
(x, y - x),
535535
"Mockup chlorophyll forecast",
536536
"err_mockup_scatter",
537-
)
537+
).clear()
538538
plot_relative_error_density(
539539
(x, (y - x) / x),
540540
"Mockup chlorophyll forecast",
541541
"rer_mockup_density",
542-
)
542+
).clear()
543543
plot_relative_error_scatter(
544544
(x, (y - x) / x),
545545
"Mockup chlorophyll forecast",
546546
"rer_mockup_scatter",
547-
)
547+
).clear()
548548

549549

550550
if __name__ == "__main__":

‎wqf/val/pvr.py‎

Lines changed: 21 additions & 21 deletions
Original file line numberDiff line numberDiff line change
@@ -80,27 +80,27 @@ def plot_bias_diagrams(
8080
title,
8181
f"bias_{method}_series_{period.str('_')}",
8282
xlim=period.lim,
83-
)
83+
).clear()
8484
plot_bias_scene(
8585
Bias().image(ref, pre),
8686
title,
8787
f"bias_{method}_image_{period.str('_')}",
88-
)
88+
).clear()
8989
plot_error_histogram(
9090
Bias().err(ref, pre),
9191
title,
9292
f"err_{method}_hist_{period.str('_')}",
93-
)
93+
).clear()
9494
plot_relative_error_histogram(
9595
Bias().rer(ref, pre, condition=ref > 1.0),
9696
title,
9797
f"rer_{method}_hist_{period.str('_')}",
98-
)
98+
).clear()
9999
plot_count_scene(
100100
Count().image(ref, pre),
101101
title,
102102
f"count_{method}_image_{period.str('_')}",
103-
)
103+
).clear()
104104

105105

106106
def plot_det_coefficient_diagrams(
@@ -121,12 +121,12 @@ def plot_det_coefficient_diagrams(
121121
title,
122122
f"det_{method}_series_{period.str('_')}",
123123
xlim=period.lim,
124-
)
124+
).clear()
125125
plot_determination_coefficient_scene(
126126
R2().image(ref, pre),
127127
title,
128128
f"det_{method}_image_{period.str('_')}",
129-
)
129+
).clear()
130130

131131

132132
def plot_mad_diagrams(
@@ -147,12 +147,12 @@ def plot_mad_diagrams(
147147
title,
148148
f"mad_{method}_series_{period.str('_')}",
149149
xlim=period.lim,
150-
)
150+
).clear()
151151
plot_mad_scene(
152152
MAD().image(ref, pre),
153153
title,
154154
f"mad_{method}_image_{period.str('_')}",
155-
)
155+
).clear()
156156

157157

158158
def plot_mapd_diagrams(
@@ -173,12 +173,12 @@ def plot_mapd_diagrams(
173173
title,
174174
f"mapd_{method}_series_{period.str('_')}",
175175
xlim=period.lim,
176-
)
176+
).clear()
177177
plot_mapd_scene(
178178
MAPD().image(ref, pre, condition=ref > 1.0),
179179
title,
180180
f"mapd_{method}_image_{period.str('_')}",
181-
)
181+
).clear()
182182

183183

184184
def plot_rmse_diagrams(
@@ -199,12 +199,12 @@ def plot_rmse_diagrams(
199199
title,
200200
f"rmse_{method}_series_{period.str('_')}",
201201
xlim=period.lim,
202-
)
202+
).clear()
203203
plot_rmse_scene(
204204
RMSE().image(ref, pre),
205205
title,
206206
f"rmse_{method}_image_{period.str('_')}",
207-
)
207+
).clear()
208208

209209

210210
def plot_wrmsse_diagrams(
@@ -225,12 +225,12 @@ def plot_wrmsse_diagrams(
225225
title,
226226
f"wrmsse_{method}_series_{period.str('_')}",
227227
xlim=period.lim,
228-
)
228+
).clear()
229229
plot_wrmsse_scene(
230230
WRMSSE().image(ref, pre, condition=ref > 1.0),
231231
title,
232232
f"wrmsse_{method}_image_{period.str('_')}",
233-
)
233+
).clear()
234234

235235

236236
def plot_density_diagrams(
@@ -243,32 +243,32 @@ def plot_density_diagrams(
243243
(x, y),
244244
f"{method} forecast {period}",
245245
f"val_{method}_density_{period.str('_')}",
246-
)
246+
).clear()
247247
plot_error_density(
248248
(x, y - x),
249249
f"{method} forecast {period}",
250250
f"err_{method}_density_{period.str('_')}",
251-
)
251+
).clear()
252252
plot_relative_error_density(
253253
(x, (y - x) / x),
254254
f"{method} forecast {period}",
255255
f"rer_{method}_density_{period.str('_')}",
256-
)
256+
).clear()
257257
plot_value_scatter(
258258
(x, y),
259259
f"{method} forecast {period}",
260260
f"val_{method}_scatter_{period.str('_')}",
261-
)
261+
).clear()
262262
plot_error_scatter(
263263
(x, y - x),
264264
f"{method} forecast {period}",
265265
f"err_{method}_scatter_{period.str('_')}",
266-
)
266+
).clear()
267267
plot_relative_error_scatter(
268268
(x, (y - x) / x),
269269
f"{method} forecast {period}",
270270
f"rer_{method}_scatter_{period.str('_')}",
271-
)
271+
).clear()
272272

273273

274274
def plot_diagnostic_diagrams(ref: DataArray, pre: DataArray, method: str):

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