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Section

Column

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Panel

Objectives

Set-up a cartesian projection for the Cross section
Configure the axis
Load a 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 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

Useful subpage parameters
subpage_map_projection
subpage_x_axis_type
subpage_y_axis_type
subpage_x_min_latitude
subpage_x_min_longitude
subpage_x_max_latitude
subpage_x_max_longitude
subpage_y_min
subpage_y_max

Code Block

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

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "xsect_step1",
                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',
        )
# 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.

Section

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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

theme	Confluence
language	python
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)

Column

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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.

Section

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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

theme	Confluence
language	python
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)

Column

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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

Section

Column

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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

theme	Confluence
language	python
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,
        )
# 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(contour_highlight= "off",
    contour_hilo= "off",
    contour_label= "off",
    legend='on',
    contour_level_list= [-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],
    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)", 
        "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)"],
    contour_shade_colour_method= "list",
    contour_shade_method= "area_fill")
plot(output, projection, horizontal, vertical, data, contour)

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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

Column

width	50%

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

theme	Confluence
language	python
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',
        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(contour_highlight= "off",
    contour_hilo= "off",
    contour_label= "off",
    legend='on',
    contour_level_list= [-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],
    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)", 
        "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)"],
    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, 
    legend_box_mode = "positional",
    legend_box_x_position = 27.00,
    legend_box_y_position = 3.00,
    legend_box_x_length = 2.00,
    legend_box_y_length = 13.00,
    legend_box_blanking = "on",
    legend_border = "on",
    legend_border_colour='charcoal')
 plot(output, projection, horizontal, vertical, data, contour, legend)

Column

width	200px

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 Text parameters
text_lines
text_font_size
text_colour
text_font_style

Code Block

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

from Magics.macro import *
#setting the output 
output = output(    
                output_formats = ['png'],
                output_name = "xsect_step6",
                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(contour_highlight= "off",
    contour_hilo= "off",
    contour_label= "off",
    legend='on',
    contour_level_list= [-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],
    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)", 
        "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)"],
    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, 
    legend_box_mode = "positional",
    legend_box_x_position = 27.00,
    legend_box_y_position = 3.00,
    legend_box_x_length = 2.00,
    legend_box_y_length = 13.00,
    legend_box_blanking = "on",
    legend_border = "on",
    legend_border_colour='charcoal')
title = mtext(
        text_lines= ['Example of Xsection to demonstrate the use of netCDF data...', 
        '<magics_title/>'],
        text_html= 'true',
        text_justification= 'left',
        text_font_size= 0.8,
        text_colour= 'charcoal',
        )

plot(output, projection, horizontal, vertical, data, contour, legend, title)

Column

width	200px

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Old Version 21

New Version 22

Key

Setting of the cartesian projection

Adjusting the axis

Loading the netCDF data

Creating a nice shading

Position the legend

add a Title