Track object

class Track(path, skiprows=0, sep=' ', date_index=0, time_index=1, lat_index=2, lon_index=3)

Object to represent a geographical track (e.g. storm track) defined in a CSV file.

Parameters

  • path (str) – specifies the CSV file containing the track data

  • skiprows (number) – skips the given number of rows from the CSV file (must be equal to the number of header rows at the beginning of the file)

  • sep (str) – the field separator character in the CSV data. When sep is ” ” (a single whitespace) multiple whitespace separators are allowed in the CSV file.

  • date_index – the index of the date column in the CSV file

  • time_index – the index of the time column in the CSV file

  • lat_index – the index of the latitude column in the CSV file

  • lon_index – the index of the longitude column in the CSV file

Track allows for loading and plotting CSV track data in a simplified way. It can be used with plot_maps() to generate plots with pre-defined track styles.

How to use a Track?

The following CSV file is taken from the Storm track gallery example and has the following structure:

20121027 00 -76.9 27.1
20121027 12 -76.29 28.37
20121028 00 -74.64  30.2
20121028 12 -73.07 31.77
20121029 00 -70.87 33.66
...

So this data contains no header and the separator is a whitespace. Using Track we can make plot in a few lines:

import metview as mv

filename = "sandy_track.grib"
if mv.exist(filename):
    g = mv.read(filename)
else:
    g = mv.gallery.load_dataset(filename)

tr = mv.Track(path, sep=" ")
mv.plot_maps(tr, view=mv.make_geoview(style="grey_2", area="north_america"))
../_images/track_1.png

Compare this code to the one used in the gallery example to see how much we can simplify the plotting with Track.

Customising the style

The style for Track is taken from the current style configuration. The default style is a list of an mgraph() (defining the curve) and an msymb() (defining the labels), in that order. The main difficulty is that the labels must be added as a list of str to the msymb(), therefore the style is not fixed but must always be generated from the current data. Luckily Track does it automatically for you.

Custom styles can also be used when plotting tracks with plot_maps(). Due to the difficulties with the label generation the recommended way for doing it is to derive a new style by updating the default one:

import metview as mv

filename = "sandy_track.grib"
if mv.exist(filename):
    g = mv.read(filename)
else:
    g = mv.gallery.load_dataset(filename)

# create track
tr = mv.Track(path, sep=" ")

# update style
vd = tr.style().update(
    {"graph_line_colour": "blue",
    "graph_symbol_colour": "purple",
    "graph_symbol_height": 0.6}, verb="mgraph")

vd = vd.update({"symbol_advanced_table_text_font_size": 0.6}, verb="msymb")

# generate plot
mv.plot_maps(tr, vd,
            view=mv.make_geoview(style="grey_2", area="north_america"))
../_images/track_2.png

Limitations

Track offers a high-level interface and uses pre-defined settings, therefore it comes with certain limitations:

  • the date format must be yyyymmdd

  • the time format must be hh

  • the label format is hard-coded as dd/hh

  • it cannot be plotted with plot()

Note

If you would like to create a fully customised track plot from CSV data see the Storm track gallery example (it uses read_table(), input_visualiser(), mgraph() and msymb() to build the track).