GRIB Scatterplot Example

#Metview Macro

#  **************************** LICENSE START ***********************************
# 
#  Copyright 2020 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 ************************************
# 

# get data
use_mars = 0 # 0 or 1
if use_mars then
    # retrieve data from MARS
    
    # analysis
    an = retrieve(
        type      : "an", 
        levtype   : "ml",
        levelist  : 110,
        param     : "t",
        time      : 6,
        grid      : [1,1]
    )

    # analysis increment
    an_incr = retrieve(
        type      : "4i",
        levtype   : "ml",
        levelist  : 110,
        param     : 200130,
        time      : 9,
        iteration : 3,
        grid      : [1,1]
    )
else
    # read data from GRIB file
    f = read("an_incr.grib")
    an = f[1]
    an_incr = f[2]
end if

# extract field values into vectors
v1 = values(an)
v2 = values(an_incr)

# define 2D-binning for scatterplot
b = binning(
    binning_x_count : 100,
    binning_y_count : 100
    )

# define scatterplot    
vis = input_visualiser(
    input_plot_type: "xy_binning",
    input_x_values: v1,
    input_y_values: v2,
    input_binning: b
)

# define contour shading 
cont = mcont(
    legend                         : "on",
    contour                        : "off",
    contour_level_selection_type   : "level_list",
    contour_level_list             : [1,10,50,100,200, 500,1000],
    contour_label                  : "off",
    contour_shade                  : "on",
    contour_shade_technique        : "grid_shading",
    contour_shade_max_level_colour : "red",
    contour_shade_min_level_colour : "RGB(0.6672,0.7658,0.8465)"
    )

# define axes
horizontal_axis = maxis(
    axis_position   : "left",
    axis_title_text : "Analyis [K]",
    axis_tick_interval : 5
    )

vertical_axis = maxis(
    axis_orientation : "vertical",
    axis_title_text : "Analysis increment [K]"
    )

# define view
view = cartesianview(
    x_automatic     : "on",
    y_automatic     : "on",
    horizontal_axis : horizontal_axis,
    vertical_axis   : vertical_axis
    )

# define title
txt = "Temperature Date: " & base_date(an)[1] & " Level: 110"
title = mtext(text_line_1: txt, 
            text_font_size: 0.4)
   
# define legend         
legend = mlegend(legend_text_font_size: 0.3)

# define the output plot file
setoutput(pdf_output(output_name : 'grib_scatterplot'))

# generate plot
plot(view, vis, cont, title, legend)

"""
GRIB Scatterplot
"""

#  **************************** LICENSE START ***********************************
#
#  Copyright 2020 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

# get data
use_mars = False
if use_mars:
    # retrieve data from MARS

    # analysis
    an = mv.retrieve(
        type="an", levtype="ml", levelist=110, param="t", time=6, grid=[1, 1]
    )

    # analysis increment
    an_incr = mv.retrieve(
        type="4i",
        levtype="ml",
        levelist=110,
        param=200130,
        time=9,
        iteration=3,
        grid=[1, 1],
    )
else:
    # read data from GRIB file
    f = mv.read("an_incr.grib")
    an = f[0]
    an_incr = f[1]


# extract field values into numpy arrays
v1 = mv.values(an)
v2 = mv.values(an_incr)

# define 2D-binning for scatterplot
b = mv.binning(binning_x_count=100, binning_y_count=100)

# define scatterplot
vis = mv.input_visualiser(
    input_plot_type="xy_binning", input_x_values=v1, input_y_values=v2, input_binning=b
)

# define contour shading
cont = mv.mcont(
    legend="on",
    contour="off",
    contour_level_selection_type="level_list",
    contour_level_list=[1, 10, 50, 100, 200, 500, 1000],
    contour_label="off",
    contour_shade="on",
    contour_shade_technique="grid_shading",
    contour_shade_max_level_colour="red",
    contour_shade_min_level_colour="RGB(0.6672,0.7658,0.8465)",
)

# define axes
horizontal_axis = mv.maxis(
    axis_position="left", axis_title_text="Analyis [K]", axis_tick_interval=5
)

vertical_axis = mv.maxis(
    axis_orientation="vertical", axis_title_text="Analysis increment [K]"
)

# define view
view = mv.cartesianview(
    x_automatic="on",
    y_automatic="on",
    horizontal_axis=horizontal_axis,
    vertical_axis=vertical_axis,
)

# define title
txt = "Temperature - Date: {} Level: 110".format(mv.base_date(an))
title = mv.mtext(text_line_1=txt, text_font_size=0.4)

# define legend
legend = mv.mlegend(legend_text_font_size=0.3)

# define the output plot file
mv.setoutput(mv.pdf_output(output_name="grib_scatterplot"))

# generate plot
mv.plot(view, vis, cont, title, legend)