#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 ************************************
# 

# getting data
use_mars = 0  # 0 or 1

# getting forecast data from MARS
if use_mars = 1 then
    prec = retrieve(
        type    : "fc",
        levtype : "sfc",
        param   : "tp",
        date    : 20190809,
        time    : 0,
        step    : [0,12,24,36,48],
        area    : [12,110,40,148],
        grid    : [0.1,0.1]
    )
# read data from file
else
    prec =read("lekima_prec.grib")
end if

# de-accumulate precipitation by subtracting consecutive steps.
# The result is accumulated precipitation for 12 h intervals
num = count(prec)
prec = prec[2,num] - prec[1,num-1]

# define contour_shading. To enable the m->mm units conversion 
# for contouring we need to enable "grib_scaling_of_derived_fields"
# since prec is now regarded as derived (we performed a grid operation 
# on it) by Metview
prec_shade = mcont(
    contour_automatic_setting      : "style_name",
    contour_style_name             : "sh_blured_f1t100lst",
    legend                         : "on",
    grib_scaling_of_derived_fields : "on"
    )

# define coastlines
coastlines = mcoast(
    map_coastline_colour            : "charcoal",
    map_coastline_thickness         : 2,
    map_coastline_land_shade        : "on",
    map_coastline_land_shade_colour : "RGB(0.5569,0.5569,0.5569)",
    map_coastline_sea_shade         : "on",
    map_coastline_sea_shade_colour  : "RGB(0.8941,0.8941,0.8941)"
    )

# define geographical view
view = geoview(
    map_area_definition : "corners",
    area                : [12,110,40,148],
    coastlines          : coastlines
    )

# create a 2x2 plot layout with the defined geoview
dw = plot_superpage(pages: mvl_regular_layout(view,2,2,1,1,[5,100,15,100]))

# define title
title = mtext(text_line_1: "Param: <grib_info key='shortName'/> [12h] Run: <grib_info key='base-date' format='%Y%m%d %HUTC'/> Step: <grib_info key='step'/>h",
              text_font_size: 0.4)
# define legend
legend = mlegend(legend_text_font_size: 0.3)

# define output
setoutput(pdf_output(output_name : 'deaccumulate_precip_fc'))

# generate plot
for i=1 to 4 do 
    plot(dw[i], prec[i], prec_shade, legend, title)
end for

"""
De-accumulate Precipitation Forecast
======================================
"""

#  **************************** 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

# getting data
use_mars = False

# getting forecast data from MARS
if use_mars:
    prec = mv.retrieve(
        type="fc",
        levtype="sfc",
        param="tp",
        date=20190809,
        time=0,
        step=[0, 12, 24, 36, 48],
        area=[12, 110, 40, 148],
        grid=[0.1, 0.1],
    )
# read data from file
else:
    prec = mv.read("lekima_prec.grib")

# de-accumulate precipitation by subtracting consecutive steps.
# The result is accumulated precipitation for 12 h intervals
num = len(prec)
prec = prec[1:num] - prec[0 : num - 1]

# define contour_shading. To enable the m->mm units conversion
# for contouring we need to enable "grib_scaling_of_derived_fields"
# since prec is now regarded as derived (we performed a grid operation
# on it) by Metview
prec_shade = mv.mcont(
    contour_automatic_setting="style_name",
    contour_style_name="sh_blured_f1t100lst",
    legend="on",
    grib_scaling_of_derived_fields="on",
)

# define coastlines
coastlines = mv.mcoast(
    map_coastline_colour="charcoal",
    map_coastline_thickness=2,
    map_coastline_land_shade="on",
    map_coastline_land_shade_colour="RGB(0.5569,0.5569,0.5569)",
    map_coastline_sea_shade="on",
    map_coastline_sea_shade_colour="RGB(0.8941,0.8941,0.8941)",
)

# define geographical view
view = mv.geoview(
    map_area_definition="corners", area=[12, 110, 40, 148], coastlines=coastlines
)

# create a 2x2 plot layout with the defined geoview
dw = mv.plot_superpage(pages=mv.mvl_regular_layout(view, 2, 2, 1, 1, [5, 100, 15, 100]))

# define title
title = mv.mtext(
    text_line_1="Param: <grib_info key='shortName'/> [12h] Run: <grib_info key='base-date' format='%Y%m%d %HUTC'/> Step: +<grib_info key='step'/>h",
    text_font_size=0.4,
)

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

# define output
mv.setoutput(mv.pdf_output(output_name="deaccumulate_precip_fc"))

# generate plot
mv.plot(
    dw[0], prec[0], prec_shade, legend, title,
    dw[1], prec[1], prec_shade, legend, title,
    dw[2], prec[2], prec_shade, legend, title, 
    dw[3], prec[3], prec_shade, legend, title,
)