def test_met_plot():
contour = mv.mcont({
'CONTOUR_LINE_COLOUR': 'PURPLE',
'CONTOUR_LINE_THICKNESS': 3,
'CONTOUR_HIGHLIGHT': False
})
coast = mv.mcoast({'MAP_COASTLINE_LAND_SHADE': True})
bindings.met_plot(TEST_FIELDSET, contour, coast)
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'
def test_plot_2():
output_name = file_in_testdir('test_plot_2')
png = mv.png_output(output_name=output_name)
grid_shade = {
'legend': True,
'contour': False,
'contour_highlight': True,
'contour_shade': True,
'contour_shade_technique': 'grid_shading',
'contour_shade_max_level_colour': 'olive',
'contour_shade_min_level_colour': 'blue',
'contour_shade_colour_direction': 'clockwise',
}
degraded_field = mv.read(data=TEST_FIELDSET, grid=[4, 4])
mv.plot(png, degraded_field, mv.mcont(grid_shade))
output_name_from_magics = output_name + '.1.png'
assert (os.path.isfile(output_name_from_magics))
os.remove(output_name_from_magics)
import metview as mv
# read 2m temperature
t2 = mv.read("./t2_for_UC-04.grib")
# read geopotential
z = mv.read("./z_for_UC-04.grib")
t_shade_c = mv.mcont(
legend=True,
contour_highlight=False,
contour_level_selection_type="interval",
contour_interval=10,
contour_shade=True,
contour_shade_max_level=60,
contour_shade_min_level=-60,
contour_shade_method="area_fill",
contour_shade_max_level_colour="red",
contour_shade_min_level_colour="blue",
contour_shade_colour_direction="clockwise",
)
z_isolines = mv.mcont(
legend=True,
contour_line_thickness=2,
contour_line_colour="black",
contour_highlight_colour="black",
contour_highlight_thickness=4,
contour_level_selection_type="interval",
contour_interval=5,
def plot_stamp(
*args,
an=[],
fc=[],
layout=None,
view=None,
area=None,
title_font_size=0.4,
frame=-1,
animate="auto",
diff_base=None,
):
"""
Plot ENS stamp maps
"""
# define the view
view = _make_view(view, area)
desc = []
data = {}
vd = {}
if diff_base is not None:
assert isinstance(diff_base, mv.Fieldset)
if len(args) > 0:
assert isinstance(args[0], mv.Fieldset)
layers = _make_layers(*args, form_layout=False)
assert len(layers) == 1
# prepare ens
data["ens"] = layers[0]["data"]
assert data["ens"] is not None
if diff_base is not None:
vd["ens"] = _make_visdef(data["ens"], [], style_db="diff")
else:
vd["ens"] = _make_visdef(data["ens"], layers[0]["vd"])
# prepare an and fc
d = {"an": an, "fc": fc}
for k, v in d.items():
if v:
layers = _make_layers(v, form_layout=False)
if layers:
data[k] = layers[0]["data"]
vd[k] = layers[0]["vd"]
if diff_base is not None:
vd[k] = vd["ens"]
else:
if len(vd[k]) == 0 and "ens" in vd:
vd[k] = vd["ens"]
else:
vd[k] = _make_visdef(data[k], vd[k])
# determine ens number
members = []
if "ens" in data:
members = data["ens"]._unique_metadata("number")
LOG.debug(f"members={members}")
if len(members) == 0:
raise Exceception("No ENS data found in input!")
# determine number of maps
num = len(members) + sum([1 for x in ["an", "fc"] if x in data])
# build the layout
dw = Layout().build_stamp(num, layout=layout, view=view)
if len(dw) < num + 1:
raise Exception(
f"Layout has less maps (={len(dw)}) than expected (={num})")
title = Title(font_size=title_font_size)
# ens members
for i, m in enumerate(members):
desc.append(dw[i])
d = data["ens"].select(number=m)
if diff_base is not None:
d = d - diff_base
desc.append(d)
if vd["ens"]:
desc.extend(vd["ens"])
t = title.build_stamp(d, member=str(i))
desc.append(t)
# add an and fc
n = len(members)
for t in ["an", "fc"]:
if t in data:
desc.append(dw[n])
d = data[t]
if diff_base is not None:
d = d - diff_base
desc.append(d)
if vd[t]:
desc.append(vd[t])
t = title.build_stamp(data[t], member="")
desc.append(t)
n += 1
for i in range(n, len(dw)):
desc.append(dw[i])
if len(members) > 0 and "ens" in data:
cont = mv.mcont(contour="off", contour_label="off")
dummy = d = data["ens"].select(number=members[0])
t = title.build(dummy)
desc.extend([dw[-1], t, dummy, cont])
return mv.plot(desc, animate=animate)
def make_eccharts_mcont():
return mv.mcont(contour_automatic_settings="ecmwf", legend="on")
Analyst saves his data as a GRIB file and creates a plot in PNG format.
"""
import metview as mv
mydata = mv.read('../tests/test.grib')
derived = mydata * 2 + 5
mv.write('derived_data.grib', derived)
grid_shade = mv.mcont(
legend=True,
contour=False,
contour_highlight=True,
contour_shade=True,
contour_shade_technique='grid_shading',
contour_shade_max_level_colour='red',
contour_shade_min_level_colour='blue',
contour_shade_colour_direction='clockwise',
)
# Macro-like PNG creation:
png = mv.png_output(output_width=1200, output_name='./myplot')
mv.plot(png, derived, grid_shade)
# Using a different notation:
png_output = {
'output_type': 'png',
'output_width': 1200,
'output_name': './myplot2'