def build_xs(self, data):
if data:
if not isinstance(data, list):
data = [data]
lines = []
for d in data:
line = d.label
# print(f"label={d.label}")
param = d.ds_param_info
if param is not None:
# print(f"meta={param.meta}")
line += f" Par: {param.name}"
meta = param.meta
if meta.get("mars.type", "") == "an":
pass
else:
r = meta.get("date", 0)
h = meta.get("time", 0)
s = meta.get("step", "")
line += f" Run: {r} {h} UTC Step: +{s}h"
lines.append(line)
return mv.mtext(text_lines=lines, text_font_size=self.font_size)
return mv.mtext(text_font_size=self.font_size)
def build_stamp(self, data, member=""):
if data:
if not isinstance(data, list):
data = [data]
# exp_conf = data[0].experiment
label = data[0].label
member_txt = ""
if member:
if member == "0":
member_txt = "CF"
else:
member_txt = f"PF {member}"
return mv.mtext(
{
"text_line_1": f"""{label} {member_txt} Step: +<grib_info key='step'/>h Valid: <grib_info key='valid-date' format='%Y-%m-%d %H'/>""",
"text_font_size": self.font_size,
}
)
return mv.mtext(
{
"text_font_size": self.font_size,
}
)
def plot_obs_freq(predictor_matrix, code):
coastline = mv.mcoast(map_coastline_thickness=2,
map_boundaries="on",
map_coastline_colour="chestnut")
symbol = mv.msymb(
legend="on",
symbol_type="marker",
symbol_table_mode="on",
symbol_outline="on",
symbol_min_table=[1, 2, 5, 10, 15, 20, 25, 30],
symbol_max_table=[2, 5, 10, 15, 20, 25, 30, 100000],
symbol_colour_table=[
"RGB(0.7020,0.7020,0.7020)",
"RGB(0.4039,0.4039,0.4039)",
"blue",
"RGB(0.4980,1.0000,0.0000)",
"RGB(1.0000,0.8549,0.0000)",
"orange",
"red",
"magenta",
],
symbol_marker_table=15,
symbol_height_table=0.3,
)
legend = mv.mlegend(
legend_text_font="arial",
legend_text_font_size=0.35,
legend_entry_plot_direction="row",
legend_box_blanking="on",
legend_entry_text_width=50,
)
title = mv.mtext(
text_line_count=4,
text_line_1=
"OBS Frequency", # To sostitute with "FE" values when relevant.
text_line_2=f"WT Code = {code}",
text_line_4=" ",
text_font="arial",
text_font_size=0.4,
)
df = predictor_matrix[["LonOBS", "LatOBS", "OBS"]]
grouped_df = df.groupby(["LatOBS", "LonOBS"], as_index=False).count()
geo = mv.create_geo(len(grouped_df), "xyv")
geo = mv.set_latitudes(geo, grouped_df["LatOBS"].to_numpy(dtype=np.float))
geo = mv.set_longitudes(geo, grouped_df["LonOBS"].to_numpy(dtype=np.float))
geo = mv.set_values(geo, grouped_df["OBS"].to_numpy(dtype=np.float))
with NamedTemporaryFile(delete=False, suffix=".pdf") as pdf:
pdf_obj = mv.pdf_output(output_name=pdf.name.replace(".pdf", ""))
mv.setoutput(pdf_obj)
mv.plot(coastline, symbol, legend, title, geo)
return pdf.name
def plot_std(predictor_matrix, code):
coastline = mv.mcoast(map_coastline_thickness=2,
map_boundaries="on",
map_coastline_colour="chestnut")
symbol = mv.msymb(
legend="on",
symbol_type="marker",
symbol_table_mode="on",
symbol_outline="on",
symbol_min_table=[0, 0.0001, 0.5, 1, 2, 5],
symbol_max_table=[0.0001, 0.5, 1, 2, 5, 1000],
symbol_colour_table=[
"RGB(0.7020,0.7020,0.7020)",
"RGB(0.2973,0.2973,0.9498)",
"RGB(0.1521,0.6558,0.5970)",
"RGB(1.0000,0.6902,0.0000)",
"red",
"RGB(1.0000,0.0000,1.0000)",
],
symbol_marker_table=15,
symbol_height_table=0.3,
)
legend = mv.mlegend(
legend_text_font="arial",
legend_text_font_size=0.35,
legend_entry_plot_direction="row",
legend_box_blanking="on",
legend_entry_text_width=50,
)
error = "FER" if "FER" in predictor_matrix.columns else "FE"
title = mv.mtext(
text_line_count=4,
text_line_1=f"{error} Standard Deviation",
text_line_2=f"WT Code = {code}",
text_line_4=" ",
text_font="arial",
text_font_size=0.4,
)
df = predictor_matrix[["LonOBS", "LatOBS", error]]
grouped_df = df.groupby(["LatOBS", "LonOBS"])[error].mean().reset_index()
geo = mv.create_geo(len(grouped_df), "xyv")
geo = mv.set_latitudes(geo, grouped_df["LatOBS"].to_numpy(dtype=np.float))
geo = mv.set_longitudes(geo, grouped_df["LonOBS"].to_numpy(dtype=np.float))
geo = mv.set_values(geo, grouped_df[error].to_numpy(dtype=np.float))
with NamedTemporaryFile(delete=False, suffix=".pdf") as pdf:
pdf_obj = mv.pdf_output(output_name=pdf.name.replace(".pdf", ""))
mv.setoutput(pdf_obj)
mv.plot(coastline, symbol, legend, title, geo)
return pdf.name
def build(self, data, font_size=None):
font_size = self._make_font_size(font_size)
label = ""
if data:
if not isinstance(data, list):
data = [data]
lines = []
lines = {"text_line_count": len(data)}
for i, d_item in enumerate(data):
# print(f"d_item={d_item}")
if isinstance(d_item, tuple):
d = d_item[0]
data_id = d_item[1]
else:
d = d_item
data_id = None
param = d.ds_param_info
if param is not None:
if param.meta.get("typeOfLevel", "") == "surface":
# lines.append(self.build_surface_fc(d.experiment.label, d.param.name, condition=cond))
lines[f"text_line_{i+1}"] = self.build_surface_fc(
d.label, param.name, data_id=data_id
)
else:
# lines.append(self.build_upper_fc(d.experiment.label, d.param.name, condition=cond))
lines[f"text_line_{i+1}"] = self.build_upper_fc(
d.label, param.name, data_id=data_id
)
# print(f"line={lines}")
# return mv.mtext(text_lines=lines, text_font_size=font_size)
return mv.mtext(**lines, text_font_size=font_size)
return mv.mtext(
{
"text_line_1": f"""{label} Par: <grib_info key='shortName'/> Lev: <grib_info key='level'/> (<grib_info key='levelType'/>) Step: +<grib_info key='step'/>h Valid: <grib_info key='valid-date' format='%Y-%m-%d %H'/>""",
"text_font_size": font_size,
}
)
def plot_avg(predictor_matrix, code):
coastline = mv.mcoast(map_coastline_thickness=2,
map_boundaries="on",
map_coastline_colour="chestnut")
symbol = mv.msymb(
legend="on",
symbol_type="marker",
symbol_table_mode="on",
symbol_outline="on",
symbol_min_table=[-1, -0.25, 0.25, 2],
symbol_max_table=[-0.025, 0.25, 2, 1000],
symbol_colour_table=[
"RGB(0.0000,0.5490,0.1882)",
"black",
"RGB(1.0000,0.6902,0.0000)",
"red",
],
symbol_marker_table=15,
symbol_height_table=0.3,
)
legend = mv.mlegend(
legend_text_font="arial",
legend_text_font_size=0.35,
legend_entry_plot_direction="row",
legend_box_blanking="on",
legend_entry_text_width=50,
)
error = "FER" if "FER" in predictor_matrix.columns else "FE"
title = mv.mtext(
text_line_count=4,
text_line_1=f"{error} Mean",
text_line_2=f"WT Code = {code}",
text_line_4=" ",
text_font="arial",
text_font_size=0.4,
)
df = predictor_matrix[["LonOBS", "LatOBS", error]]
grouped_df = df.groupby(["LatOBS", "LonOBS"])[error].mean().reset_index()
geo = mv.create_geo(len(grouped_df), "xyv")
geo = mv.set_latitudes(geo, grouped_df["LatOBS"].to_numpy(dtype=np.float))
geo = mv.set_longitudes(geo, grouped_df["LonOBS"].to_numpy(dtype=np.float))
geo = mv.set_values(geo, grouped_df[error].to_numpy(dtype=np.float))
return plot_geo(geo, coastline, symbol, legend, title)
def test_definitions():
mcont_def = mv.mcont({'legend': True})
msymb_def = mv.msymb({'symbol_type': 'marker'})
mcoast_def = mv.mcoast({'map_coastline_land_shade': True})
mobs_def = mv.mobs({'obs_temperature': False})
mtext_def = mv.mtext({'text_font_size': '0.80'})
geoview_def = mv.geoview({'map_projection': 'polar_stereographic'})
ps_output_def = mv.ps_output({'output_name': 'test'})
assert mcont_def['LEGEND'] == 'ON'
assert msymb_def['SYMBOL_TYPE'] == 'MARKER'
assert mcoast_def['MAP_COASTLINE_LAND_SHADE'] == 'ON'
assert mobs_def['OBS_TEMPERATURE'] == 'OFF'
assert mtext_def['TEXT_FONT_SIZE'] == 0.8
assert geoview_def['MAP_PROJECTION'] == 'POLAR_STEREOGRAPHIC'
assert ps_output_def['OUTPUT_NAME'] == 'test'