visjobs 0.2

Get Latest Atmospheric Model Data | Analyse | Visualize Easily

visjobs

Visjobs offers plotting effective variables in effective way using atmospheric models.

Installation

• git clone https://github.com/donmezk/visjobs
• Clone in the same directory the code is written.

Some example about how to use Visjobs

• WE WILL BE PLOTTING THE 500MB GEOPOTENTIAL HEIGHT | MEAN SEA LEVEL PRESSURE FOR NORTH AMERICA
• importing dependencies.

from visjobs.datas import get_data
from visjobs.visualize import draw_map
import xarray as xr
import numpy as np

---

• Getting the data using pick_data function.
• Function pick_data():
  • hour=06 --> means the 06Z run of the model
  • latest=True --> means the latest output with 06Z run
  • model='GFS' --> means GFS data is choosen ['NAM' is also available]
  • hourly=False --> means GFS 3 hourly data is asked [not valid for NAM]

data = get_data.pick_data(hour='06',latest=True,model='GFS',
			  hourly=False)

• Note that data taken is xarray DataArray.

---

• In below using xarray DataArray, we are deciding the interval of desired latitude and longitude.
• Returns a dictionary.
• Function pick_area():
  • data --> Xarray data must be given
  • total_process --> means until which time step the data is asked
  • interval --> means until the asked time step, with what interval time step will go
  • init_time --> means the initial time step of the data
  • list_of_vars --> the desired variables in list [str]
  • list_of_areas --> the desired areas in list [str]
  • pr_height --> the desired pressure heights in list [int]

time, area_dict = get_data.pick_area(data, total_process=2, interval=1, init_time=0, 
				     list_of_vars=['prmslmsl','hgtprs'],pr_height=['500'],
                          	     list_of_areas=['northamerica','europe'])

• Let's say I want to plot 500mb heights and mslp for North America.
• In the upper part I got the relevant data using pick_area function.
• Now assign each single data from the whole dictionary.

press = np.divide(area_dict['northamerica'][0], 100)
heightprs = area_dict['northamerica'][1]

• Choosing the desired plot size.

from pylab import rcParams
rcParams['figure.figsize'] = 21, 24

• In below using height_pressure function we will plot 500mb Height-Pressure graphic
• Function height_pressure():
  • time --> the loop initiated from the init_time indicated above function until the 'time'
  • press --> xarray input for pressure
  • heightprs --> xarray input for height
  • pr_height --> the desired pressure height
  • place --> the area which the user wants to plot
  • save_where --> where to save the figure
  • breaking --> if True, the function will stop after one loop
  • title_on --> if True, the title must be introduced, default is False

  • ---

    • if only the title_on = True, apply inputs below
  • owner_name = the box in the upper left corner of the plot
  • plot_main_tite --> main title that is going to be plotted in string
  • tl1, tl2, tl3, tll4, tl5 --> set the title's placement [a,b] (int list)

draw_map.height_pressure(time, press, heightprs ,pr_height='500', place='northamerica',
                         save_where=r'height_prs{}.png',
			 breaking=True, title_on=True ,owner_name='Kutay DÖNMEZ',
			 plot_main_title=r'GFS 500mb Geopotential Height(m) | Presssure(mb)',
                         tl5=[0.0047, 0.97100], tl1=[0,1.032])

plot result: https://pasteboard.co/J1HhgsF.png