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Real time data processing using IMDLIB

Tutorial showcasing IMDLIB for real-time data processing.

1 min read

Contents
  1. Description
  2. Installation
  3. Usage
  4. Downloading real-time data from IMD
  5. Reading downloaded real-time dataset
Map of daily rainfall over India from IMD gridded data, plotted with IMDLIB.

Description

Tutorial showcasing IMDLIB for real-time data processing.

Installation

IMDLIB can be installed via pip, conda, or using the source file from Github. It is tested for both Windows and Linux platforms with 64 bit architecture only.

Installation using pip.

pip install imdlib

Installation using conda.

conda install -c iamsaswata imdlib

Installation from source file.

pip install git+https://github.com/iamsaswata/imdlib.git

Usage

Downloading real-time data from IMD

IMDLIB, with its v.0.1.15, now supports processing of real-time daily IMD rainfall 0.25° and temperature data 0.50°.

The steps are similar to the data downloading and opening of IMD gridded archive data.

An example is presented below.

import imdlib as imd

# Downloading daily real-time rainfall data for India
import imdlib as imd
start_dy = '2020-01-31'
end_dy = '2020-03-05'
var_type = 'rain'
file_dir='../data'
data = imd.get_real_data(var_type, start_dy, end_dy, file_dir)

The output is:

    Downloading: rain for date 2020-01-31
    Downloading: rain for date 2020-02-01
    Downloading: rain for date 2020-02-02
    Downloading: rain for date 2020-02-03
    Downloading: rain for date 2020-02-04
    Downloading: rain for date 2020-02-05
    Downloading: rain for date 2020-02-06
    Downloading: rain for date 2020-02-07
    Downloading: rain for date 2020-02-08
    Downloading: rain for date 2020-02-09
    Downloading: rain for date 2020-02-10
    Downloading: rain for date 2020-02-11
    Downloading: rain for date 2020-02-12
    Downloading: rain for date 2020-02-13
    Downloading: rain for date 2020-02-14
    Downloading: rain for date 2020-02-15
    Downloading: rain for date 2020-02-16
    Downloading: rain for date 2020-02-17
    Downloading: rain for date 2020-02-18
    Downloading: rain for date 2020-02-19
    Downloading: rain for date 2020-02-20
    Downloading: rain for date 2020-02-21
    Downloading: rain for date 2020-02-22
    Downloading: rain for date 2020-02-23
    Downloading: rain for date 2020-02-24
    Downloading: rain for date 2020-02-25
    Downloading: rain for date 2020-02-26
    Downloading: rain for date 2020-02-27
    Downloading: rain for date 2020-02-28
    Downloading: rain for date 2020-02-29
    Downloading: rain for date 2020-03-01
    Downloading: rain for date 2020-03-02
    Downloading: rain for date 2020-03-03
    Downloading: rain for date 2020-03-04
    Downloading: rain for date 2020-03-05
    Download Successful !!!

Reading downloaded real-time dataset

import imdlib as imd
start_dy = '2020-01-31'
end_dy = '2020-03-05'
var_type = 'rain'
file_dir='../data'
data = imd.open_real_data(var_type, start_dy, end_dy, file_dir)