First step

In order to be able to create and use Magics objects, the Magics python package has to be imported. 

Any Magics plot will be triggered using the plot command.

A basic plot  could be a geographical map, using the default projection, and the default attributes of coastlines.

Magics will instantiate the default driver.

...

Setting of the geographical area

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

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

Have a look at the  PNG output documentation  to see which parameters are available to set-up a PNG output.

To create a PNG output Magics, you have to create an output object and to insert at the first position in the plot command

...

from Magics.macro import *

#setting the

 output 
output = output(

    
                output_formats = ['png'],
               

 output_name = "

map_step2",
                

output_name_first_page_number = "off"
        )

Setting the coastlines

The object mcoast allows the parametrisation of the coastlines.

Have a look at the  Coastlines documentation  to see which parameters are available.

To configure the look of your coastlines you have to create a mcoast object with the parameters you want.

#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 mcont, using black for the lines. We want an interval of 5 hPa between isolines. We also want to add an automatic legend, with our own text "Mean Sea Level Pressure". Follow the link to access the Contouring DocumentationThe mcoast object has to be inserted in the plot command.

from Magics.macro import *

#settings of#setting the png output 
output = output(
			    
                output_formats = ['png'],
                			output_name = "coastmap_step3",
               		 output_name_first_page_number = "off"
        )
##settings#settings of the coastlinesgeographical attributesarea 
coastarea = mcoast(
  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 = "browngrey",
      map_label_colour = "brownon",
       map_coastline_colour = "brown"
)

#The plot command will now use the coast object
plot(output, coastgrey")
#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, msl, contour)

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.

Visualising the precipitation field

The goal of this exercise is to discover a bit more the diverse styles of visualisation offered by the mcont object.

We are pre-processed a GRIB field containing the precipitation accumulated in the last 6 hours of the valid time. We want to disable the automatic scaling appled by Magics and use our own scaling factor, in this case 1000.

Here we will work with shading, and we will use a different technique to setup the levels we want to contour.

We want to use the following list of levels for contouring [0.5, 2., 4., 10., 25., 50., 100., 250.]

and the following list of colours ["cyan", "greenish_blue", "blue", "bluish_purple", "magenta", "orange", "red", "charcoal"]

#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "map_step4",
                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")
#definition of the input data
precip = mgrib(grib_input_file_name="precip.grib", 
    grib_automatic_scaling='off', 
    grib_scaling_factor=1000.)
shading = mcont( contour_highlight= "off",
    contour_hilo= "off",
    contour_label="off",
    contour_level_list=[0.5, 2., 4., 10., 25., 50., 100., 250.],
    contour_level_selection_type= "level_list",
    contour_shade= "on",
    contour_shade_method= "area_fill",
    contour_shade_colour_method= "list",
    contour_shade_colour_list= ["cyan", "greenish_blue", "blue", "bluish_purple", "magenta", "orange", "red", "charcoal"],
    legend="on")
    
plot(output, area, coast, precip, shading)

Overlaying the 2 layers and playing with legend

Here, we want to demonstrate the plot command.

The actions added to the plot command will be executed sequentially, and their result will be displayed from the background to the foreground .

Then, try to put the shaded layer (precipitation) behind the contoured layer (msl)

and try to improve the legend to make it look continuous, by checking the Legend Documentation.

from Magics.macro import *

#setting the

 output 
output = output(

    
                output_formats = ['png'],
                

output_name = "

map_step5",
        

        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")
#definition of the input data
precip = mgrib(grib_input_file_name="precip.grib", 
    grib_automatic_scaling='off', 
    grib_scaling_factor=1000.)
#definition of shading
shading = mcont( contour_highlight= "off",
    contour_hilo= "off",
    contour_label="off",
    contour_level_list=[0.5, 2., 4., 10., 25., 50., 100., 250.],
    contour_level_selection_type= "level_list",
    contour_shade= "on",
    contour_shade_method= "area_fill",
    contour_shade_colour_method= "list",
    contour_shade_colour_list= ["cyan", "greenish_blue", "blue", "bluish_purple", "magenta", "orange", "red", "charcoal"],
    legend="on")
#definition of msl
msl = mgrib(grib_input_file_name="msl.grib")
#Definition of the black contouring
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_legend_text= "Mean Sea Level Pressure",
                contour_level_selection_type= "interval",
                contour_line_colour= "black",
                contour_line_thickness= 2,
                legend='on'
            )
#Definition of the legend
legend = mlegend(legend='on', 
            legend_display_type='continuous', 
            legend_text_colour='charcoal', 
            legend_text_font_size=0.4,
            )    
plot(output, area, coast, precip, shading, msl, contour, legend)

Adding the position of New York City

To demonstrate the use of symbols plotting, we are going to add a big red dot where New York City is.We will the add the text NYC in black on top of the dot.

The position of New York is [41^oN, 74^oW], we can give this position to Magics using the minput object, documented in Input Data Page.

The symbol is performed using the msymb object. You can find the full options in the Symbol Documentation.

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "map_step6",
                output_name_first_page_number = "off"
        )

             
#---------------------------------------
# definition of the previsous layers 
# ...
# ...
#---------------------------------------
#definition of New-York city
new_york = minput(
            input_x_values    =    [-74.],
            input_y_values    =    [41.]
            )
#definition of the symbol
point = msymb(
            symbol_type    =    "both",
            symbol_text_list    =    ["NYC"],
            symbol_marker_index    =    28,
            symbol_colour    =    "red",
            symbol_height    =    0.5,
            symbol_

text_font_size = 

0.40,
            symbol_text_font_colour = "black",
            symbol_text_position = "top",
            symbol_text_font_style = "bold ", 
            )
plot(output, area, coast, precip, shading, msl, contour, new_york, point, legend)

Adding a line to show our next Cross-section

In the next exercise, we will display a Cross-section of the Vorticity across the Storm.

We want to show this line of our plot as a black thick line.

The stating point is [50^oN, 90^oW], the end point is  [30^oN, 60^oW] : it can be passed to Magics using the minput object, documented in Input Data Page.

To draw the line we will use the mgraph object. All the parameters are available in the Graph Plotting Documentation.

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "map_step7",
                output_name_first_page_number = "off"
        )

             
#---------------------------------------
# definition of the previous layers 
# ...
# ...
#---------------------------------------
#definition of the Xsection Line
xsection = minput(
            input_x_values    =    [-90., -60.],
            input_y_values    =    [50., 30.]
            )
#definition of the graph
line = mgraph( 
            graph_line_colour    =    "black",
            graph_line_thickness    =    4
            )
plot(output, area, coast, precip, shading, msl, contour, new_york, point, xsection, line, legend)

Adding a title

We have now a very nice plot... let's add a title at the top.

Text box can be embedded everywhere on a plot, but the default position will be a title at the top of the plot, above an potential legend.

The text facility is documented in the Text Plotting Page.

Section

Column width 50% Info title Parameters to check     Useful Text parameters text_lines text_font_size text_colour text_font_style     Code Block theme Confluence language python title Python - Adding a text collapse true from Magics.macro import * #setting the output output = output( output_formats = ['png'], output_name = "map_step8", output_name_first_page_number = "off" ) #--------------------------------------- # definition of the previous layers # ... # ... #--------------------------------------- #definition of the text title = mtext(text_lines=['Sandy', '30th of October 2012'], text_font_size = 0.8, text_colour= "charcoal", text_font_style='bold', ) plot(output, area, coast, precip, shading, msl, contour, new_york, point, xsection, line, legend, title) Column width 200px  Image Added   Image Removed

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