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

 

 

Setting of the cartesian projection

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

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.

 

 

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
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)

 

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.

 

 

Useful axis parameters

axis_type

axis_tick_label_height
axis_tick_label_colour
axis_grid
axis_title
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)

 

 

Loading the NetCDF data

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

To do that, the mnetcdf defines a parameter list that can be found in the  Netcdf Input Page.

Now, tet's see what is inside our Netcdf Data 

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 p1382012103000000000000, and inform Magics that the dimensions of th ematrix 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.

Useful Netcdf parameters

netcdf_filename

netcdf_value_variable
netcdf_field_scaling_factor
netcdf_y_variable
netcdf_x_variable
netcdf_x_auxiliary_variable
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)