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Update: figures for PVP and PVR
1 parent 545178e commit c8b4ddf

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2 files changed

+111
-29
lines changed

2 files changed

+111
-29
lines changed

‎wqf/val/pvp.py‎

Lines changed: 91 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -24,6 +24,7 @@
2424
from wqf.val.metrics import MAPD
2525
from wqf.val.metrics import R2
2626
from wqf.val.metrics import RMSE
27+
from wqf.val.metrics import RMSLE
2728
from wqf.val.metrics import WRMSSE
2829
from wqf.val.plots import DensityPlot
2930
from wqf.val.plots import HistogramPlot
@@ -82,13 +83,37 @@ def plot_count_scene(
8283
data,
8384
title=title,
8485
fn=fn,
85-
cbar_label="number of forecasts",
86+
cbar_label="number of observations",
8687
vmin=0.0,
8788
vmax=250.0,
8889
xlocs=(1.0, 2.5, 4.0, 5.5, 7.0, 8.5, 10.0),
8990
)
9091

9192

93+
def plot_count_time_series(
94+
data: DataArray,
95+
title: str | None = None,
96+
fn: str | None = None,
97+
xlim: tuple[int, int] | None = None,
98+
ylim: tuple[Any, Any] = (0.0, 150),
99+
) -> Figure:
100+
return TimeSeriesPlot().plot(
101+
data,
102+
ylabel=r"number of observations ($10^3$)",
103+
xlim=(
104+
(
105+
np.datetime64(f"{xlim[0]}-01-01"),
106+
np.datetime64(f"{xlim[1]}-01-01"),
107+
)
108+
if xlim is not None
109+
else None
110+
),
111+
ylim=ylim,
112+
title=title,
113+
fn=fn,
114+
)
115+
116+
92117
def plot_determination_coefficient_scene(
93118
data: DataArray, title: str | None = None, fn: str | None = None
94119
) -> Figure:
@@ -241,6 +266,44 @@ def plot_rmse_time_series(
241266
)
242267

243268

269+
def plot_rmsle_scene(
270+
data: DataArray, title: str | None = None, fn: str | None = None
271+
) -> Figure:
272+
return ScenePlot().plot(
273+
data,
274+
title=title,
275+
fn=fn,
276+
cbar_label="RMSLE",
277+
vmin=0.0,
278+
vmax=1.0,
279+
xlocs=(1.0, 2.5, 4.0, 5.5, 7.0, 8.5, 10.0),
280+
)
281+
282+
283+
def plot_rmsle_time_series(
284+
data: DataArray,
285+
title: str | None = None,
286+
fn: str | None = None,
287+
xlim: tuple[int, int] | None = None,
288+
ylim: tuple[Any, Any] = (0.0, 1.0),
289+
) -> Figure:
290+
return TimeSeriesPlot().plot(
291+
data,
292+
ylabel="RMSLE",
293+
xlim=(
294+
(
295+
np.datetime64(f"{xlim[0]}-01-01"),
296+
np.datetime64(f"{xlim[1]}-01-01"),
297+
)
298+
if xlim is not None
299+
else None
300+
),
301+
ylim=ylim,
302+
title=title,
303+
fn=fn,
304+
)
305+
306+
244307
def plot_wrmsse_scene(
245308
data: DataArray, title: str | None = None, fn: str | None = None
246309
) -> Figure:
@@ -286,7 +349,7 @@ def plot_value_density(
286349
) -> Figure:
287350
return DensityPlot().plot(
288351
data,
289-
xlabel=r"reference chlorophyll concentration (mg m$^{-3}$)",
352+
xlabel=r"observed chlorophyll concentration (mg m$^{-3}$)",
290353
ylabel=r"forecast (mg m$^{-3}$)",
291354
title=title,
292355
fn=fn,
@@ -304,7 +367,7 @@ def plot_value_scatter(
304367
) -> Figure:
305368
return ScatterPlot().plot(
306369
data,
307-
xlabel=r"reference chlorophyll concentration (mg m$^{-3}$)",
370+
xlabel=r"observed chlorophyll concentration (mg m$^{-3}$)",
308371
ylabel=r"forecast (mg m$^{-3}$)",
309372
xlim=(-0.50, 30.5),
310373
ylim=(-0.50, 30.5),
@@ -320,7 +383,7 @@ def plot_error_density(
320383
) -> Figure:
321384
return DensityPlot().plot(
322385
data,
323-
xlabel=r"reference chlorophyll concentration (mg m$^{-3}$)",
386+
xlabel=r"observed chlorophyll concentration (mg m$^{-3}$)",
324387
ylabel=r"forecast error (mg m$^{-3}$)",
325388
title=title,
326389
fn=fn,
@@ -338,7 +401,7 @@ def plot_error_scatter(
338401
) -> Figure:
339402
return ScatterPlot().plot(
340403
data,
341-
xlabel=r"reference chlorophyll concentration (mg m$^{-3}$)",
404+
xlabel=r"observed chlorophyll concentration (mg m$^{-3}$)",
342405
ylabel=r"forecast error (mg m$^{-3}$)",
343406
xlim=(-0.50, 30.5),
344407
ylim=(-15.5, 15.5),
@@ -372,7 +435,7 @@ def plot_relative_error_density(
372435
) -> Figure:
373436
return DensityPlot().plot(
374437
data,
375-
xlabel=r"reference chlorophyll concentration (mg m$^{-3}$)",
438+
xlabel=r"observed chlorophyll concentration (mg m$^{-3}$)",
376439
ylabel="forecast relative error",
377440
title=title,
378441
fn=fn,
@@ -390,7 +453,7 @@ def plot_relative_error_scatter(
390453
) -> Figure:
391454
return ScatterPlot().plot(
392455
data,
393-
xlabel="reference chlorophyll concentration (mg m$^{-3}$)",
456+
xlabel="observed chlorophyll concentration (mg m$^{-3}$)",
394457
ylabel="forecast relative error",
395458
xlim=(-0.50, 30.5),
396459
ylim=(-1.55, 1.55),
@@ -446,6 +509,13 @@ def generate_figures(args, period: tuple[int, int]):
446509
"rer_mockup_hist",
447510
).clear()
448511

512+
# noinspection PyTypeChecker
513+
plot_count_time_series(
514+
Count().series(ref, pre) / 1000.0,
515+
"Mockup chlorophyll forecast",
516+
"count_mockup_series",
517+
xlim=period,
518+
).clear()
449519
plot_count_scene(
450520
Count().image(ref, pre),
451521
"Mockup chlorophyll forecast",
@@ -500,14 +570,26 @@ def generate_figures(args, period: tuple[int, int]):
500570
"rmse_mockup_image",
501571
).clear()
502572

573+
plot_rmsle_time_series(
574+
RMSLE().series(ref, pre),
575+
"Mockup chlorophyll forecast",
576+
"rmsle_mockup_series",
577+
xlim=period,
578+
).clear()
579+
plot_rmsle_scene(
580+
RMSLE().image(ref, pre),
581+
"Mockup chlorophyll forecast",
582+
"rmsle_mockup_image",
583+
).clear()
584+
503585
plot_wrmsse_time_series(
504-
WRMSSE().series(ref, pre, condition=ref > 1.0),
586+
WRMSSE().series(ref, pre),
505587
"Mockup chlorophyll forecast",
506588
"wrmsse_mockup_series",
507589
xlim=period,
508590
).clear()
509591
plot_wrmsse_scene(
510-
WRMSSE().image(ref, pre, condition=ref > 1.0),
592+
WRMSSE().image(ref, pre),
511593
"Mockup chlorophyll forecast",
512594
"wrmsse_mockup_image",
513595
).clear()

‎wqf/val/pvr.py‎

Lines changed: 20 additions & 20 deletions
Original file line numberDiff line numberDiff line change
@@ -325,29 +325,29 @@ def plot_density_diagrams(
325325

326326

327327
def plot_diagnostic_diagrams(ref: DataArray, pre: DataArray, method: str):
328-
# plot_bias_diagrams(ref, pre, method, Period(2016, 2019))
329-
# plot_bias_diagrams(ref, pre, method, Period(2020))
330-
#
331-
# plot_det_coefficient_diagrams(ref, pre, method, Period(2016, 2019))
332-
# plot_det_coefficient_diagrams(ref, pre, method, Period(2020))
333-
#
334-
# plot_mad_diagrams(ref, pre, method, Period(2016, 2019))
335-
# plot_mad_diagrams(ref, pre, method, Period(2020))
336-
#
337-
# plot_mapd_diagrams(ref, pre, method, Period(2016, 2019))
338-
# plot_mapd_diagrams(ref, pre, method, Period(2020))
339-
340-
# plot_rmse_diagrams(ref, pre, method, Period(2016, 2019))
341-
# plot_rmse_diagrams(ref, pre, method, Period(2020))
342-
343-
# plot_rmsle_diagrams(ref, pre, method, Period(2016, 2019))
344-
# plot_rmsle_diagrams(ref, pre, method, Period(2020))
345-
#
328+
plot_bias_diagrams(ref, pre, method, Period(2016, 2019))
329+
plot_bias_diagrams(ref, pre, method, Period(2020))
330+
331+
plot_det_coefficient_diagrams(ref, pre, method, Period(2016, 2019))
332+
plot_det_coefficient_diagrams(ref, pre, method, Period(2020))
333+
334+
plot_mad_diagrams(ref, pre, method, Period(2016, 2019))
335+
plot_mad_diagrams(ref, pre, method, Period(2020))
336+
337+
plot_mapd_diagrams(ref, pre, method, Period(2016, 2019))
338+
plot_mapd_diagrams(ref, pre, method, Period(2020))
339+
340+
plot_rmse_diagrams(ref, pre, method, Period(2016, 2019))
341+
plot_rmse_diagrams(ref, pre, method, Period(2020))
342+
343+
plot_rmsle_diagrams(ref, pre, method, Period(2016, 2019))
344+
plot_rmsle_diagrams(ref, pre, method, Period(2020))
345+
346346
plot_wrmsse_diagrams(ref, pre, method, Period(2016, 2019))
347347
plot_wrmsse_diagrams(ref, pre, method, Period(2020))
348348

349-
# plot_density_diagrams(ref, pre, method, Period(2016, 2019))
350-
# plot_density_diagrams(ref, pre, method, Period(2020))
349+
plot_density_diagrams(ref, pre, method, Period(2016, 2019))
350+
plot_density_diagrams(ref, pre, method, Period(2020))
351351

352352

353353
def generate_figures(args):

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