#Metview Macro
# **************************** LICENSE START ***********************************
#
# Copyright 2019 ECMWF. This software is distributed under the terms
# of the Apache License version 2.0. In applying this license, ECMWF does not
# waive the privileges and immunities granted to it by virtue of its status as
# an Intergovernmental Organization or submit itself to any jurisdiction.
#
# ***************************** LICENSE END ************************************
#
# define station id
statid="95759"
# read db
db = read("wprof.odb")
# define query for u wind component
q_u="select obsvalue as val, " &
"vertco_reference_1 as p, " &
"date@hdr as date," &
"time@hdr as time" &
"where varno=3 and statid='" & statid & "'"
# define query for v wind component
q_v="select obsvalue as val, " &
"vertco_reference_1 as p, " &
"date as d," &
"time as t" &
"where varno=4 and statid='" & statid & "'"
# define query for metadata
q_meta="select DISTINCT lat@hdr as lat, lon@hdr as lon, " &
"andate, antime where statid='" & statid & "'"
# filter u
f_u = odb_filter(
odb_query : q_u,
odb_data : db
)
# filter v
f_v = odb_filter(
odb_query : q_v,
odb_data : db
)
# filter metadata
f_m = odb_filter(
odb_query : q_meta,
odb_data : db
)
# read the odb columns into vectors
u = values(f_u, "val")
d = values(f_u, "date")
t = values(f_u, "time")
p = values(f_u, "p")/100 # pressure is converted to hPa
v = values(f_v, "val")
# read values for the title
lat = values(f_m, "lat")[1]
lon = values(f_m, "lon")[1]
andate = values(f_m, "andate")[1]
antime = values(f_m, "antime")[1]
# build date list
dLst=nil
for i=1 to count(d) do
hh = t[i]/10000
mm = (t[i]-(hh*10000))/100.
dLst=dLst & [date(d[i]) + hour(hh) + minute(mm)]
end for
# define an input visualiser
vis = input_visualiser(
input_plot_type : "xy_vectors",
input_x_type : "date",
input_y_type : "number",
input_date_x_values : dLst,
input_y_values : tolist(p),
input_x_component_values : tolist(u),
input_y_component_values : tolist(v)
)
# wind plotting style
wp = mwind(
wind_thinning_factor : 1.0,
legend : "on",
wind_advanced_method : "on",
wind_advanced_colour_selection_type : "interval",
wind_advanced_colour_min_value : 1,
wind_advanced_colour_level_interval : 1,
wind_advanced_colour_max_level_colour : "RGB(1,0.05373,0.003922)",
wind_advanced_colour_min_level_colour : "RGB(0.003922,0.2031,1)",
wind_arrow_thickness : 2,
wind_arrow_unit_velocity : 10
)
# define title
title = mtext(text_font_size : 0.4,
text_line_1 : "WIND PROFILER AN date=" & andate & " time=" & antime &
" station=" & statid &
" lat=" & lat & " lon=" & lon)
# horizontal axis
h_axis = maxis(
axis_position : "left",
axis_title_text : "Time",
axis_minor_tick : "on",
axis_minor_tick_count : 5,
axis_date_type : "hours",
axis_hours_label: "on",
axis_hours_label_height: 0.4,
axis_grid: "on",
axis_grid_colour: "charcoal",
axis_grid_line_style: "dot"
)
# vertical axis
v_axis = maxis(
axis_orientation : "vertical",
axis_title_text : "Presssure (hPa)",
axis_grid: "on",
axis_grid_colour: "charcoal",
axis_grid_line_style: "dot"
)
# the view
view = cartesianview(
x_automatic : "on",
x_axis_type : "date",
#x_date_min: 2017-01-05,
#x_date_max: 2017-01-06,
y_automatic : "off",
y_min: 1000,
y_max: 400,
y_automatic_reverse : "on",
horizontal_axis : h_axis,
vertical_axis : v_axis,
subpage_background_colour: "RGB(0.95,0.95,0.95)"
)
# define the output plot file
setoutput(pdf_output(output_name : 'odb_wind_profiler'))
# generate the plot
plot(view, vis, wp, title)
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# **************************** LICENSE START ***********************************
#
# Copyright 2019 ECMWF. This software is distributed under the terms
# of the Apache License version 2.0. In applying this license, ECMWF does not
# waive the privileges and immunities granted to it by virtue of its status as
# an Intergovernmental Organization or submit itself to any jurisdiction.
#
# ***************************** LICENSE END ************************************
#
import metview as mv
from datetime import datetime
# define station id
statid = "95759"
# read db
db = mv.read("wprof.odb")
# define query for u wind component
q_u = """select obsvalue as val,
vertco_reference_1 as p,
date@hdr as date,
time@hdr as time
where varno=3 and statid='{}'""".format(statid)
# define query for v wind component
q_v = """select obsvalue as val,
vertco_reference_1 as p,
date as d,
time as t
where varno=4 and statid='{}'""".format(statid)
# define query for metadata
q_meta = """select DISTINCT lat@hdr as lat, lon@hdr as lon, andate,
antime where statid='{}'""".format(statid)
# filter u
f_u = mv.odb_filter(
odb_query = q_u,
odb_data = db
)
# filter v
f_v = mv.odb_filter(
odb_query = q_v,
odb_data = db
)
# filter metadata
f_m = mv.odb_filter(
odb_query = q_meta,
odb_data = db
)
# read the odb columns into vectors
u = mv.values(f_u, "val")
d = mv.values(f_u, "date")
t = mv.values(f_u, "time")
p = mv.values(f_u, "p") / 100 # pressure is converted to hPa
v = mv.values(f_v, "val")
# read values for the title
lat = mv.values(f_m, "lat")[0]
lon = mv.values(f_m, "lon")[0]
andate = mv.values(f_m, "andate")[0]
antime = mv.values(f_m, "antime")[0]
# build datetime list
d_lst=[]
for i,d_val in enumerate(d):
tt = str(int(t[i]))
if len(tt) == 5:
tt = '0' + tt
d_lst.append(datetime.strptime(str(int(d_val)) + tt,"%Y%m%d%H%M%S"))
# define an input visualiser
vis = mv.input_visualiser(
input_plot_type = "xy_vectors",
input_x_type = "date",
input_y_type = "number",
input_date_x_values = d_lst,
input_y_values = list(p),
input_x_component_values = list(u),
input_y_component_values = list(v)
)
# wind plotting style
wp = mv.mwind(
wind_thinning_factor = 1.0,
legend = "on",
wind_advanced_method = "on",
wind_advanced_colour_selection_type = "interval",
wind_advanced_colour_min_value = 1,
wind_advanced_colour_level_interval = 1,
wind_advanced_colour_max_level_colour = "red",
wind_advanced_colour_min_level_colour = "blue",
wind_arrow_thickness = 2,
wind_arrow_unit_velocity = 10
)
# define title
title = mv.mtext(text_font_size = 0.4,
text_line_1 = """WIND PROFILER AN date={:.0f} time={:.0f} station={} lat={:.2f} lon={:.2f}""".
format(andate, antime, statid, lat, lon)
)
# horizontal axis
h_axis = mv.maxis(
axis_position = "left",
axis_title_text = "Time",
axis_minor_tick = "on",
axis_minor_tick_count = 5,
axis_date_type = "hours",
axis_hours_label = "on",
axis_hours_label_height = 0.4,
axis_grid = "on",
axis_grid_colour = "charcoal",
axis_grid_line_style = "dot"
)
# vertical axis
v_axis = mv.maxis(
axis_orientation = "vertical",
axis_title_text = "Presssure (hPa)",
axis_grid = "on",
axis_grid_colour = "charcoal",
axis_grid_line_style = "dot"
)
# the view
view = mv.cartesianview(
x_automatic = "on",
x_axis_type = "date",
y_automatic = "off",
y_min = 1000,
y_max = 400,
y_automatic_reverse = "on",
horizontal_axis = h_axis,
vertical_axis = v_axis,
subpage_background_colour = "RGB(0.95,0.95,0.95)"
)
# define the output plot file
mv.setoutput(mv.pdf_output(output_name = 'odb_wind_profiler'))
# generate the plot
mv.plot(view, vis, wp, title)
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