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Objectives

  • Set-up a cylindrical projection over the United States.
  • Apply land-shading on the coastlines.
  • Load a grib file containing Mean-Sea level Presssure and visualise it using black isolines.
  • Load a grib file containing Precipitation  and visualise it using shading technique.
  • Add a legend.
  • Add a text.
  • Draw the position of New-York City
  • Draw a line to materialise the Xsection we are going to visualise in a next tutorial

You will need to download

 

 

Setting of the geographical area

The Geographical area we want to work with today is defined by its lower-left corner [20oN, 110oE] and its upper-right corner [70oN, 30oE].

Have a look at the  subpage documentation to learn how to setup a projection .

Parameters to check

 

 

subpage_lower_left_longitude

subpage_lower_left_latitude
subpage_upper_right_longitude
subpage_upper_right_latitude
Python - Setting a projection 
from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "map_step1",
                output_name_first_page_number = "off"
        )
#settings of the geographical area 
area = mmap(subpage_map_projection="cylindrical",
        subpage_lower_left_longitude=-110.,
        subpage_lower_left_latitude=20.,
        subpage_upper_right_longitude=-30.,
        subpage_upper_right_latitude=70.,
    )    
#Using a default coastlines to see the result
plot(output, area, mcoast())

Setting the coastlines

Until now you have used the mcoast to add coastlines to your plot. The mcoast object comes with a lot of parameters to allow you to style your coastlines layer.

The full list of parameters can be found in the Coastlines documentation.

In this first exercise, we will like to see:

  • The land coloured in cream.
  • The coastlines in grey.
  • The grid as a grey dash line.

Parameters to check

 

 

map_coastline_land_shade

map_coastline_land_shade_colour
map_coastline_colour
map_grid_colour
map_grid_line_style
Python - Coastlines 
from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "map_step2",
                output_name_first_page_number = "off"
        )
#settings of the geographical area 
area = mmap(subpage_map_projection="cylindrical",
        subpage_lower_left_longitude=-110.,
        subpage_lower_left_latitude=20.,
        subpage_upper_right_longitude=-30.,
        subpage_upper_right_latitude=70.,
    )     
 #settings of the caostlines
coast = mcoast(map_coastline_land_shade = "on",
      map_coastline_land_shade_colour = "cream",
      map_grid_line_style = "dash",
      map_grid_colour = "grey",
      map_label = "on",
      map_coastline_colour = "grey")
plot(output, area, coast)

 

 

 

Visualising the Mean Sea Level Pressure field

The visualisation of any data in Magics is done by combining 2 kind of objects. One, the Data Action,  is used to define the data and explain to Magics how to interpret it, the other one is called Visual Action and will define the type of visualisation and its attributes.

In this example our data are in a grib file msl.grib. The Data Action to be used is mgrib in is documented in Grib Input Documentation.

The Visualisation we want to apply is a basic contouring, using black for the lines and an interval of 5 hPa, between isolines. We also want to add a automatic legend, with our own text "Mean Sea Level Pressure". Follow the link to access the Contouring Documentation.

Parameters to check

 

 

mgrib action to load the data

grib_input_file_name
mcont action to define a contouring
contour_line_colour
contour_line_thickness
contour_highlight_colour
contour_highlight_thickness
contour_hilo
contour_level_selection_type
contour_interval
legend
contour_legend_text
Python - Coastlines 
from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "map_step3",
                output_name_first_page_number = "off"
        )
#settings of the geographical area 
area = mmap(subpage_map_projection="cylindrical",
        subpage_lower_left_longitude=-110.,
        subpage_lower_left_latitude=20.,
        subpage_upper_right_longitude=-30.,
        subpage_upper_right_latitude=70.,
    )     
 #settings of the caostlines
coast = mcoast(map_coastline_land_shade = "on",
      map_coastline_land_shade_colour = "cream",
      map_grid_line_style = "dash",
      map_grid_colour = "grey",
      map_label = "on",
      map_coastline_colour = "grey")
#Loading the msl Grib data
msl = mgrib(grib_input_file_name="msl.grib")
#Defining the controur
contour = mcont(contour_highlight_colour= "black",
                contour_highlight_thickness= 4,
                contour_hilo= "off",
                contour_interval= 5.,
                contour_label= "on",
                contour_label_frequency= 2,
                contour_label_height= 0.4,
                contour_level_selection_type= "interval",
                contour_line_colour= "black",
                contour_line_thickness= 2, 
                legend='on',
                contour_legend_text= "Mean Sea Level Pressure",
            )
plot(output, area, coast)

 

 

 

Adding a text

Magics allows the user to add of or several lines of text. The position of the text is by default above the plot, but some parameters aloow it to be moved around.

A basic html formatting can be used for colour, style, and font size.

The mtext object has to be inserted in the plot command to see the text on the result.

 

Python - Title 
from Magics.macro import *

#settings of the png output 
output = output(
			output_formats = ['png'],
  			output_name = "coast",
    		output_name_first_page_number = "off"
    )
##settings of the coastlines attributes 
coast = mcoast(
  map_coastline_land_shade = "on",
  map_coastline_land_shade_colour = "cream",
  map_grid_line_style = "dash",
  map_grid_colour = "brown",
  map_label_colour = "brown",
  map_coastline_colour = "brown"
)
##settings of the text (notice the Html formatting)
title = mtext(
  text_lines = ["Hello World!", " <b>This is my first plot</b> !"],
  text_font_size = "0.7",
  text_colour = "charcoal"
  )
#The plot command will now use the coast and title objects
plot(output, coast, title)

 

 

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