Vertical Profile and time series

Setting of the geographical area

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

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

Useful subpage parameters

subpage_lower_left_longitude

subpage_lower_left_latitude

subpage_upper_right_longitude

subpage_upper_right_latitude

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.

Useful Coastlines parameters

map_coastline_land_shade

map_coastline_land_shade_colour

map_coastline_colour

map_grid_colour

map_grid_line_style

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.

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

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, msl, contour)

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 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"]

mgrib action to load the data

grib_input_file_name

grib_automatic_scaling

grib_scaling_factor

mcont action to define a contouring

contour_level_selection_type

contour_level_list

contour_shade

contour_shade_method

contour_shade_colour_method

contour_level_selection_type

contour_shade_colour_list

legend

#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.

Useful legend parameters

legend

legend_display_type

legend_text_colour

legend_text_font_size

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^oE], 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.

Useful input parameters

input_x_values

input_y_values

Useful Symbol parameters

symbol_colour

symbol_marker_index

symbol_height

symbol_type

symbol_text_list

symbol_text_font_size

symbol_text_font_colour

symbol_text_font_style

symbol_text_position

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^oE], the end point is  [30^oN, 60^oE] : 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.

Useful input parameters

input_x_values

input_y_values

Useful Graph parameters

graph_line

graph_line_colour

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 = [-74.], input_y_values = [41.] ) #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.

Useful Text parameters

text_lines

text_font_size

text_colour

text_font_style

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)

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