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Section

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Panel

Objectives

Set-up a cartesian projection for the Cross section
Configure the axis
Load a Netcdf netCDF file, and understand the information needed by Magics.
Apply a shading
Position the legend box
Add a text.

You will need to download

The Xsection Netcdf netCDF Data
and later ... the full solution

Setting of the

...

cartesian projection

We want to show our Cross section in the following cartesian system:

The vertical coordinate system is a logarithmic axis from 1000 hPa to 200 hPa.
The horizontal coordinate system is a geoline axis from [50^oN, 90^oW] to [30^oN, 60^oW]

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

We just have to add 2 axis (1 vertical, 1 horizontal ) to materialise it on the plot. For backward compatibility, we have only one maxis object, the orientation is defined using the parameter axis_orientation.

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Info

title	Parameters to check

lowerleftupperright

Useful subpage parameters
subpage_lower_left_longitudemap_projection
subpage_x_axis_type
subpage_y_axis_type
subpage_	x_	min_latitude
subpage_	x_	min_longitude
subpage_upperx_rightmax_latitude
subpage_x_max_longitude
subpage_y_min
subpage_y_max

Confluence

Code Block

theme

language	python
theme	Confluence
title	Python - Setting a projection
collapse	true

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "mapxsect_step1",
                output_name_first_page_number = "off"
        )
#settings# ofSetting the geographicalcartesian area view
areaprojection = mmap(
        subpage_map_projection="cylindrical"'cartesian',
        subpage_lowerx_leftaxis_longitude=-110.type='geoline',
        subpage_lowery_leftaxis_latitude=20.type='logarithmic',
        subpage_upperx_rightmin_longitudelatitude=-3050.,
        subpage_upperx_rightmax_latitude=7030.,
    )    
#Using a default coastlines to see the result
plot(output, area, mcoast())

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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.

...

width	50%

...

title	Parameters to check

Useful Coastlines parameters
map_coastline_land_shade
map_coastline_land_shade_colour
map_coastline_colour
map_grid_colour
map_grid_line_style

subpage_x_min_longitude=-90.,
        subpage_x_max_longitude=-60.,
        subpage_y_min=1020.,
        subpage_y_max=200.,
        )
# Vertical axis
vertical = maxis(
        axis_orientation='vertical',
        )
# Horizontal axis
horizontal = maxis(
        axis_orientation='horizontal',
        )
        
plot(output, projection, horizontal, vertical)

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Adjusting the axis

By specialising the axis, you can improve your axis visualisation.

Have a look at the Axis Documentation to browse the possibilities.

Now, try to improve the readability of the line by specialising the horizontal axis.

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Info

title	Parameters to check

Useful axis parameters
axis_type
axis_tick_label_height
axis_tick_label_colour
axis_grid
axis_title

Code Block

language	python
theme	Confluence
title	Python - adjusting the axis
collapse	true

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "xsect_step2",
                output_name_first_page_number = "off"
        )
# Setting the cartesian view
projection = mmap(
        subpage_map_projection='cartesian',
        subpage_x_axis_type='geoline',
        subpage_y_axis_type='logarithmic',
        subpage_x_min_latitude=50.,
        subpage_x_max_latitude=30.,
        subpage_x_min_longitude=-90.,
        subpage_x_max_longitude=-60.,
        subpage_y_min=1020.,
        subpage_y_max=200.,
        )
# Vertical axis
vertical = maxis(
        axis_orientation='vertical',
        axis_grid='on',
        axis_type='logarithmic',
        axis_tick_label_height=0.4,
        axis_tick_label_colour='charcoal',
        axis_grid_colour='charcoal',
        axis_grid_line_style='dash',
        axis_title='on',
        axis_title_text='Pressure',
        axis_title_height=0.6,
        )
# Horizontal axis
horizontal = maxis(
        axis_orientation='horizontal',
        axis_type='geoline',
        axis_tick_label_height=0.4,
        axis_tick_label_colour='charcoal',
        axis_grid='on',
        axis_grid_colour='charcoal',
        axis_grid_thickness=1,
        axis_grid_line_style='dash',
        )
plot(output, projection, horizontal, vertical)

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Image Added

Loading the netCDF data

In this exercise, we want to visualise a matrix stored in a netCDF file. netCDF is a very generic format, and can contain a lot of data. We will need to set up some information in order to explain to Magics which variable to plot, and how to interpret it.

The mnetcdf data action comes with a parameter list that can be found in the netCDF Input Page.

But first, let's see what is inside our netCDF Data

Code Block

title	ncdump section.nc

netCDF section {
dimensions:
        levels = 85 ;
        longitude = 144 ;
        latitude = 144 ;
        p15220121030000000000001_1 = 2 ;
        p15220121030000000000001_2 = 144 ;
        orography_x_values = 144 ;
        orography_y1_values = 144 ;
        orography_y2_values = 144 ;
variables:
        double levels(levels) ;
        double longitude(longitude) ;
        double latitude(latitude) ;
        double p13820121030000000000001(levels, longitude) ;

We want to display the variable p13820121030000000000001, and inform Magics that the dimensions of the matrix are described in the 2 variables levels and longitude.

The range of the vorticity values is quite small, then we would like to apply a scaling factor of 100000.

We will then just apply a basic contouring.

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Info

title	Parameters to check

Useful netCDF parameters
netcdf_filename
netcdf_value_variable
netcdf_field_scaling_factor
netcdf_y_variable
netcdf_x_variable
netcdf_x_auxiliary_variable

Code Block

language	python
theme	Confluence
title	Python - Loading a Netcdf
collapse	true

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "xsect_step3",
                output_name_first_page_number = "off"
        )
# Setting the cartesian view
projection = mmap(
        subpage_map_projection='cartesian',
        subpage_x_axis_type='geoline',
        subpage_y_axis_type='logarithmic',
        subpage_x_min_latitude=50.,
        subpage_x_max_latitude=30.,
        subpage_x_min_longitude=-90.,
        subpage_x_max_longitude=-60.,
        subpage_y_min=1020.,
        subpage_y_max=200.,
        )
# Vertical axis
vertical = maxis(
        axis_orientation='vertical',
        axis_grid='on',
        axis_type='logarithmic',
        axis_tick_label_height=0.4,
        axis_tick_label_colour='charcoal',
        axis_grid_colour='charcoal',
        axis_grid_thickness=1,
        axis_grid_reference_line_style='solid',
        axis_grid_reference_thickness=1,
        axis_grid_line_style='dash',
        axis_title='on',
        axis_title_text='Pressure',
        axis_title_height=0.6,
        )
# Horizontal axis
horizontal = maxis(
        axis_orientation='horizontal',
        axis_type='geoline',
        axis_tick_label_height=0.4,
        axis_tick_label_colour='charcoal',
        axis_grid='on',
        axis_grid_colour='charcoal',
        axis_grid_thickness=1,
        axis_grid_line_style='dash',
        )
# Definition of the netCDF data and interpretation
data = mnetcdf(netcdf_filename = "section.nc",
      netcdf_value_variable = "p13820121030000000000001",
      netcdf_field_scaling_factor = 100000.,
      netcdf_y_variable = "levels",
      netcdf_x_variable = "longitude",
      netcdf_x_auxiliary_variable = "latitude"
    )
contour = mcont()
plot(output, projection, horizontal, vertical, data, contour)

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Creating a nice shading

Now, we just create a nice polygon shading.

The list of levels we want to use is : [-200., -100., -75., -50., -30., -20., -15., -13., -11., -9., -7., -5., -3., -1., 1., 3., 5., 7., 9., 11., 13., 15., 20., 30., 50., 75., 100., 200].

and the list of colours is : ["rgb(0,0,0.3)", "rgb(0,0,0.5)", "rgb(0,0,0.7)", "rgb(0,0,0.9)", "rgb(0,0.15,1)", "rgb(0,0.3,1)", "rgb(0,0.45,1)", "rgb(0,0.6,1)", "rgb(0,0.75,1)", "rgb(0,0.85,1)", "rgb(0.2,0.95,1)", "rgb(0.45,1,1)", "rgb(0.75,1,1)", "none", "rgb(1,1,0)","rgb(1,0.9,0)", "rgb(1,0.8,0)", "rgb(1,0.7,0)", "rgb(1,0.6,0)", "rgb(1,0.5,0)", "rgb(1,0.4,0)", "rgb(1,0.3,0)", "rgb(1,0.15,0)", "rgb(0.9,0,0)", "rgb(0.7,0,0)", "rgb(0.5,0,0)", "rgb(0.3,0,0)"],

Do not forget to turn the legend on ...

You could quickly check Contour Documentation

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Info

title	Parameters to check

Useful contour parameters
contour_level_selection_type
contour_level_list
contour_shade
contour_shade_method
contour_shade_colour_method
contour_shade_colour_list
legend

Code Block

language	python
theme	Confluence
title	Python - Using a shading
collapse	true

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "xsect_step3",
                output_name_first_page_number = "off"
        )
# Setting the cartesian view
projection = mmap(
        subpage_map_projection='cartesian',
        subpage_x_axis_type='geoline',
        subpage_y_axis_type='logarithmic',
        subpage_x_min_latitude=50.,
        subpage_x_max_latitude=30.,
        subpage_x_min_longitude=-90.,
        subpage_x_max_longitude=-60.,
        subpage_y_min=1020.,
        subpage_y_max=200.,
        )
# Vertical axis
vertical = maxis(
        axis_orientation='vertical',
        axis_grid='on',
        axis_type='logarithmic',
        axis_tick_label_height=0.4,
        axis_tick_label_colour='charcoal',
        axis_grid_colour='charcoal',
        axis_grid_thickness=1,
        axis_grid_reference_line_style='solid',
        axis_grid_reference_thickness=1,
        axis_grid_line_style='dash',
        axis_title='on',
        axis_title_text='Pressure',
        axis_title_height=0.6,

Code Block

theme	Confluence
language	python
title	Python - Coastlines
collapse	true

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)

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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.

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Info

title	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

Code Block

theme	Confluence
language	python
title	Python - Msl Visualisation
collapse	true

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"# Horizontal axis
horizontal = maxis(
        axis_orientation='horizontal',
        subpage_lower_left_longitude=-110.axis_type='geoline',
        subpageaxis_lowertick_leftlabel_latitudeheight=200.4,
        subpageaxis_uppertick_rightlabel_longitude=-30.colour='charcoal',
        subpage_upper_right_latitude=70.axis_grid='on',
    )     
 #settings of the caostlines
coast = mcoast(map_coastline_land_shade = "on"axis_grid_colour='charcoal',
      map  axis_coastline_land_shade_colour = "cream"grid_thickness=1,
       map axis_grid_line_style = "'dash"',
      map_grid_colour = "grey",
      map_label)
# Definition of the netCDF data and interpretation
data = mnetcdf(netcdf_filename = "onsection.nc",
      mapnetcdf_coastlinevalue_colourvariable = "greyp13820121030000000000001"),
#Loading the msl Grib data
msl = mgrib(gribnetcdf_inputfield_filescaling_name="msl.grib")
#Defining the controur
contour = mcont(contour_highlight_colour= "blackfactor = 100000.,
      netcdf_y_variable = "levels",
      netcdf_x_variable = "longitude",
        contour_highlight_thickness= 4,netcdf_x_auxiliary_variable = "latitude"
    )
contour =     mcont(contour_highlight= "off",
      contour_hilo= "off",
    contour_label= "off",
       legend='on',
    contour_level_interval= 5list= [-200., -100.,
 -75., -50., -30., -20., 
        -15., -13.,  contour_label= "on",
       -11., -9., -7., -5., -3., -1., 1., 3., 5., 
         contour_label_frequency= 2,
            7., 9., 11., 13., 15., 20., 30., 50., 75., 100., 200],
    contour_labellevel_selection_heighttype= 0.4"level_list",
           contour_shade= "on",
     contour_levelshade_selectioncolour_type= "interval",list= ["rgb(0,0,0.3)", "rgb(0,0,0.5)", 
        "rgb(0,0,0.7)", "rgb(0,0,0.9)", "rgb(0,0.15,1)", 
      contour_line_colour= "black",  "rgb(0,0.3,1)", "rgb(0,0.45,1)", "rgb(0,0.6,1)", 
        "rgb(0,0.75,1)",        contour_line_thickness= 2"rgb(0,0.85,1)", "rgb(0.2,0.95,1)", 
                legend='on',
   "rgb(0.45,1,1)", "rgb(0.75,1,1)", "none", "rgb(1,1,0)", 
             contour_legend_text= "Mean Sea Level Pressure",
            )
plot(output, area, coast, msl, contour)

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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"]

...

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...

title	Parameters to check

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

"rgb(1,0.9,0)", "rgb(1,0.8,0)", "rgb(1,0.7,0)", 
        "rgb(1,0.6,0)", "rgb(1,0.5,0)", "rgb(1,0.4,0)", 
        "rgb(1,0.3,0)", "rgb(1,0.15,0)", "rgb(0.9,0,0)", 
        "rgb(0.7,0,0)", "rgb(0.5,0,0)", "rgb(0.3,0,0)"],
    contour_shade_colour_method= "list",
    contour_shade_method= "area_fill")
plot(output, projection, horizontal, vertical, data, contour)

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Image Added

Position the legend

By default, the legend is is positioned at the top of the plot. In this exercise we want to put see our legend on a column mode on the right of the plot.

The Information about the positional mode can be found in the Legend Documentation

Section

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Info

title	Parameters to check

Useful legend parameters
legend
legend_display_type
legend_box_mode
legend_box_x_position
legend_box_y_position
legend_box_x_length
legend_box_y_length
legend_box_blanking
legend_border

Code Block

language	python
theme	Confluence
title	Python - Position the legend
collapse	true

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "xsect_step5",
                output_name_first_page_number = "off"
        )
# Setting the cartesian view
projection = mmap(
        subpage_map_projection='cartesian',
        subpage_x_axis_type='geoline',
        subpage_y_axis_type='logarithmic',
        subpage_x_min_latitude=50.,
        subpage_x_max_latitude=30.,
        subpage_x_min_longitude=-90.,
        subpage_x_max_longitude=-60.,
        subpage_y_min=1020.,
        subpage_y_max=200.,
        )
# Vertical axis
vertical = maxis(
        axis_orientation='vertical',
        axis_grid='on',
        axis_type='logarithmic',
        axis_tick_label_height=0.4,
        axis_tick_label_colour='charcoal',
        axis_grid_colour='charcoal',
        axis_grid_thickness=1,
        axis_grid_reference_line_style='solid',
        axis_grid_reference_thickness=1,
        axis_grid_line_style='dash',
        axis_title='on',
        axis_title_text='Pressure'

Code Block

theme	Confluence
language	python
title	Python - Use of Shading
collapse	true

#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)

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Image Removed

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.

Section

Column

width	50%

Info

title	Parameters to check

Useful legend parameters
legend
legend_display_type
legend_text_colour
legend_text_font_size

Code Block

theme	Confluence
language	python
title	Python - Overlay
collapse	true

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
          axis_title_height=0.6,
      output_name = "map_step5",
     )
# Horizontal axis
horizontal = maxis(
            output_name_first_page_number = "off"axis_orientation='horizontal',
        )
#settings of the geographical area 
area = mmap(subpage_map_projection="cylindrical"axis_type='geoline',
        axis_tick_label_height=0.4,
        subpageaxis_lowertick_leftlabel_longitude=-110.colour='charcoal',
        subpage_lower_left_latitude=20.axis_grid='on',
        subpageaxis_uppergrid_right_longitude=-30.colour='charcoal',
        subpageaxis_uppergrid_right_latitude=70.thickness=1,
    )     
 #settings of the caostlines
coast = mcoast(map_coastline_land_shade = "on",
axis_grid_line_style='dash',
         map_coastline_land_shade_colour = "cream",
      map_grid_line_style)
# Definition of the netCDF data and interpretation
data = mnetcdf(netcdf_filename = "dashsection.nc",
      mapnetcdf_gridvalue_colourvariable = "greyp13820121030000000000001",
      map_labelnetcdf_field_scaling_factor = "on"100000.,
      mapnetcdf_coastliney_colourvariable = "greylevels"),
#definition of the input data
precip = mgrib(gribnetcdf_input_file_name="precip.grib", 
x_variable = "longitude",
      gribnetcdf_x_automaticauxiliary_scaling='off', variable = "latitude"
    grib_scaling_factor=1000.)
#definition of shading
shading contour = mcont( contour_highlight= "off",
    contour_hilo= "off",
    contour_label= "off",
    legend='on',
    contour_level_list= [0-200.5, 2-100., 4-75., 10-50., 25-30., 50., 100-20., 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 -15., -13., -11., -9., -7., -5., -3., -1., 1., 3., 5., 
        7., 9., 11., 13., 15., 20., 30., 50., 75., 100., 200],
    contour_level_selection_type= "level_list",
    contour_shade= "on",
    contour_shade_colour_list= ["rgb(0,0,0.3)", "rgb(0,0,0.5)", 
        "rgb(0,0,0.7)",  contour_highlight_thickness= 4,"rgb(0,0,0.9)", "rgb(0,0.15,1)", 
                contour_hilo= "off","rgb(0,0.3,1)", "rgb(0,0.45,1)", "rgb(0,0.6,1)", 
                contour_interval= 5.,"rgb(0,0.75,1)", "rgb(0,0.85,1)", "rgb(0.2,0.95,1)", 
                contour_label= "on",
                contour_label_frequency= 2,"rgb(0.45,1,1)", "rgb(0.75,1,1)", "none", "rgb(1,1,0)", 
        "rgb(1,0.9,0)", "rgb(1,0.8,0)", "rgb(1,0.7,0)", 
     contour_label_height= 0.4,
       "rgb(1,0.6,0)", "rgb(1,0.5,0)", "rgb(1,0.4,0)", 
            contour_legend_text= "Mean Sea Level Pressure","rgb(1,0.3,0)", "rgb(1,0.15,0)", "rgb(0.9,0,0)", 
                contour_level_selection_type= "interval""rgb(0.7,0,0)", "rgb(0.5,0,0)", "rgb(0.3,0,0)"],
                contour_lineshade_colour_method= "blacklist",
                contour_lineshade_thicknessmethod= 2,
                "area_fill")
legend = mlegend(legend='on'
       ', 
     )
#Definition of the legend
legend = mlegend(legend='on', 
legend_display_type='continuous', 
    legend_text_colour='charcoal',         
    legend_text_displayfont_type='continuous'size=0.4, 
    legend_box_mode = "positional",
    legend_box_x_position = 27.00,
    legend_text_colour='charcoal', 
  box_y_position = 3.00,
    legend_box_x_length = 2.00,
    legend_textbox_fonty_sizelength =0 13.400,
    legend_box_blanking = "on",
    legend_border = )"on",
    
plotlegend_border_colour='charcoal')
 plot(output, areaprojection, coasthorizontal, precipvertical, shading, msldata, contour, legend)

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width

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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.

	200px

Image Added

add a Title

Last thing to do here .. We add a title to the top..

Here we will use a combination of User text and automatic text ( read from the netCDF global attribute title)

To get the automatic title, you have to use the following tag <magics_title/>

Check the Text Plotting Page for more information

Section

Column

width	50%

Info

title	Parameters to check

Useful input parameters
input_x_values
input_y_values
Text parameters
text_lines
Useful Symbol parameters
symbol_colour
symbol_marker_index
symbol_height
symbol_type
symbol_text_list
symbol_text_font_sizesymbol_
text_font_colour
symbol_text_font_style
symbol_text_position

code

Code Block

language	python

language


theme	Confluence	python
title	Python - Adding New-York CityPosition the legend
collapse	true

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

        output_name     
#---------------------------------------
# definition of the previsous layers 
# ...
# ...
#---------------------------------------
#definition of New-York city
new_york = minput(= "xsect_step6",
                output_name_first_page_number = "off"
        )
# Setting the  input_x_valuescartesian view
projection = mmap(
    =    [-74.]subpage_map_projection='cartesian',
            input_y_valuessubpage_x_axis_type='geoline',
    =    [41.]subpage_y_axis_type='logarithmic',
        subpage_x_min_latitude=50.,
    )
#definition of the symbol
point = msymb( subpage_x_max_latitude=30.,
        subpage_x_min_longitude=-90.,
    symbol_type    subpage_x_max_longitude=-60.,
    "both",
    subpage_y_min=1020.,
        symbolsubpage_text_listy_max=200.,
    =    ["NYC"],
   )
# Vertical axis
vertical = maxis(
         symbol_marker_indexaxis_orientation='vertical',
    =    28axis_grid='on',
        axis_type='logarithmic',
    symbol_colour    axis_tick_label_height=0.4,
    "red",
    axis_tick_label_colour='charcoal',
        symbol_heightaxis_grid_colour='charcoal',
    =    0.5axis_grid_thickness=1,
            symbol_text_font_size = 0.40axis_grid_reference_line_style='solid',
            symbol_text_font_colour = "black"axis_grid_reference_thickness=1,
            symbol_text_position = "top"axis_grid_line_style='dash',
        axis_title='on',
        symbolaxis_title_text_font_style = "bold ", 
='Pressure',
        axis_title_height=0.6,
        )
plot(output, area, coast, precip, shading, msl, contour, new_york, point, legend)

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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.

Section

Column

width	50%

Info

title	Parameters to check

Useful input parameters
input_x_values
input_y_values

Useful Graph parameters
graph_line
graph_line_colour

Code Block

theme	Confluence
language	python
title	Python - Adding a line
collapse	true

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png']# Horizontal axis
horizontal = maxis(
        axis_orientation='horizontal',
        axis_type='geoline',
        axis_tick_label_height=0.4,
        axis_tick_label_colour='charcoal',
        axis_grid='on',
        axis_grid_colour='charcoal',
        axis_grid_thickness=1,
        axis_grid_line_style='dash',
        )
# Definition of the netCDF data and interpretation
data = mnetcdf(netcdf_filename = "section.nc",
      netcdf_value_variable = "p13820121030000000000001",
      netcdf_field_scaling_factor = 100000.,
      netcdf_y_variable = "levels",
      netcdf_x_variable = "longitude",
        output_namenetcdf_x_auxiliary_variable = "map_step7latitude",
    )
contour = mcont(contour_highlight= "off",
    contour_hilo= "off",
    output_name_first_page_number contour_label= "off",
    legend='on',
    contour_level_list= [-200., -100.,  )

   -75., -50., -30., -20., 
        -15., -13., 
#-11., --------------------------------------
# definition of the previous layers 
# ...
# ...
#---------------------------------------
#definition of the Xsection Line
xsection = minput(
            input_x_values    =    [-74.],9., -7., -5., -3., -1., 1., 3., 5., 
        7., 9., 11., 13., 15., 20., 30., 50., 75., 100., 200],
    contour_level_selection_type= "level_list",
    contour_shade= "on",
    contour_shade_colour_list= ["rgb(0,0,0.3)", "rgb(0,0,0.5)", 
        "rgb(0,0,0.7)", "rgb(0,0,0.9)", "rgb(0,0.15,1)", 
            input_y_values    =    [41.]"rgb(0,0.3,1)", "rgb(0,0.45,1)", "rgb(0,0.6,1)", 
            )
#definition of the graph
line = mgraph( 
            graph_line_colour    =    "black",
  "rgb(0,0.75,1)", "rgb(0,0.85,1)", "rgb(0.2,0.95,1)", 
        "rgb(0.45,1,1)", "rgb(0.75,1,1)", "none", "rgb(1,1,0)", 
        "rgb(1,0.9,0)",  graph_line_thickness "rgb(1,0.8,0)", "rgb(1,0.7,0)", 
   =    4
     "rgb(1,0.6,0)", "rgb(1,0.5,0)", "rgb(1,0.4,0)", 
        )
plot(output, area, coast, precip, shading, msl, contour, new_york, point, xsection, line, legend)

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width	200px

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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.

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(    
"rgb(1,0.3,0)", "rgb(1,0.15,0)", "rgb(0.9,0,0)", 
        "rgb(0.7,0,0)", "rgb(0.5,0,0)", "rgb(0.3,0,0)"],
    contour_shade_colour_method= "list",
    contour_shade_method= "area_fill")
legend = mlegend(legend='on', 
    legend_display_type='continuous', 
    legend_text_colour='charcoal',         
    legend_text_font_size=0.4, 
    outputlegend_box_formatsmode = ['png']"positional",
    legend_box_x_position = 27.00,
    legend_box_y_position = 3.00,
    output_namelegend_box_x_length = "map_step8"2.00,
    legend_box_y_length       = 13.00,
     outputlegend_name_first_page_numberbox_blanking = "offon",
    legend_border = "on",
    legend_border_colour='charcoal')

title = mtext(
           
#---------------------------------------
# definition of the previous layers 
# ...
# ...
#---------------------------------------
#definition of the text
title = mtext(text_lines=['Sandy', '30th of October 2012'],
     text_lines= ['Example of Xsection to demonstrate the use of netCDF data...', 
        '<magics_title/>'],
        text_html= 'true',
        text_font_size justification= 0.8'left',
            text_font_coloursize= "charcoal"0.8,
            text_font_stylecolour= 'boldcharcoal',
        )

plot(output, areaprojection, coasthorizontal, precipvertical, shading, msldata, contour, new_york, point, xsection, line, legend, title)

Column

width	200px

Image RemovedImage Added

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Content

Space Tools

Versions Compared

Old Version 3

New Version Current

Key

Setting of the

cartesian projection

Setting the coastlines

Adjusting the axis

Loading the netCDF data

Creating a nice shading

Visualising the Mean Sea Level Pressure field

Visualising the precipitation field

Position the legend

Overlaying the 2 layers and playing with legend

Adding the position of New York City

add a Title

Adding a line to show our next Cross-section

Adding a title