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language | py |
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title | Air Report Example |
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# Metview Macro
# **************************** LICENSE START ***********************************
#
# Copyright 2016 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 ************************************
# ------------------------------------------------------------------
# Description: Demonstrates how to show observations from a geopoints
# file using symbol objects.
# ------------------------------------------------------------------
# read the input geopoints file
my_data = read("airep.geo")
# set up the data symbol and colour
my_symbol = msymb(symbol_type : "marker",
symbol_marker_index : 15,
symbol_table_mode : "advanced",
symbol_advanced_table_selection_type : "interval",
symbol_advanced_table_colour_direction : "clockwise",
symbol_advanced_table_max_level_colour : "red",
symbol_advanced_table_min_level_colour : "blue",
symbol_advanced_table_interval : 5.00,
legend : "on")
# set up the contour so that observed values are mapped into a colour list
my_contour = mcont(contour_grid_value_plot : "on",
contour_grid_value_plot_type : "both",
contour_grid_value_height : 0.30,
contour_grid_value_marker_height : 0.20,
contour_level_selection_type : "level_list",
contour_level_list : [-20,-10,-5,-2.5,-1,-0.5,0,0.5,1,2.5,5,10,20],
contour_line_colour : "grey",
contour_line_thickness : 2,
contour_highlight : "off",
contour_label : "off",
contour_grid_value_lon_frequency : 10,
contour_grid_value_lat_frequency : 10,
legend : "off")
# legend type is histogram
my_legend = mlegend(legend_text_colour : "navy",
legend_display_type : "histogram")
# set up the coastlines
my_coast = mcoast(map_coastline_land_shade : "on",
map_coastline_land_shade_colour : "cream",
map_grid : "on",
map_grid_colour : "grey")
# set up the title
my_title = mtext(text_mode : "positional",
text_font_size : 0.60,
text_justification : "left",
text_border : "off",
text_lines : ["Monitoring of AIREP data"],
text_box_x_length : 20.00,
text_box_y_length : 2.50,
text_box_x_position : 1.50,
text_box_y_position : 16.50,
text_colour : "navy")
# define the output plot file
setoutput(pdf_output(output_name : 'air_report'))
# plot the data onto the map
plot(my_coast, my_data,my_symbol,my_title,my_legend)
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Tabs Page |
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Code Block |
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language | py |
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title | Air Report Example |
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# Metview Example
# **************************** LICENSE START ***********************************
#
# Copyright 2016 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 ************************************
# ------------------------------------------------------------------
# Description: Demonstrates how to show observations from a geopoints
# file using symbol objects.
# ------------------------------------------------------------------
import metview as mv
# read the input geopoints file
my_data = mv.read("airep.geo")
# set up the data symbol and colour
my_symbol = mv.msymb(symbol_type = "marker",
symbol_marker_index = 15,
symbol_table_mode = "advanced",
symbol_advanced_table_selection_type = "interval",
symbol_advanced_table_colour_direction = "clockwise",
symbol_advanced_table_max_level_colour = "red",
symbol_advanced_table_min_level_colour = "blue",
symbol_advanced_table_interval = 5.00,
legend = "on")
# set up the contour so that observed values are mapped into a colour list
my_contour = mv.mcont(contour_grid_value_plot = "on",
contour_grid_value_plot_type = "both",
contour_grid_value_height = 0.30,
contour_grid_value_marker_height = 0.20,
contour_level_selection_type = "level_list",
contour_level_list = [-20,-10,-5,-2.5,-1,-0.5,0,0.5,1,2.5,5,10,20],
contour_line_colour = "grey",
contour_line_thickness = 2,
contour_highlight = "off",
contour_label = "off",
contour_grid_value_lon_frequency = 10,
contour_grid_value_lat_frequency = 10,
legend = "off")
# legend type is histogram
my_legend = mv.mlegend(legend_text_colour = "navy",
legend_display_type = "histogram")
# set up the coastlines
my_coast = mv.mcoast(map_coastline_land_shade = "on",
map_coastline_land_shade_colour = "cream",
map_grid = "on",
map_grid_colour = "grey")
# set up the title
my_title = mv.mtext(text_mode = "positional",
text_font_size = 0.60,
text_justification = "left",
text_border = "off",
text_lines = ["Monitoring of AIREP data"],
text_box_x_length = 20.00,
text_box_y_length = 2.50,
text_box_x_position = 1.50,
text_box_y_position = 16.50,
text_colour = "navy")
# define the output plot file
mv.setoutput(mv.pdf_output(output_name = 'air_report'))
# plot the data onto the map
mv.plot(my_coast, my_data,my_symbol,my_title,my_legend)
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