All Projects → nasa → Mmm Py

nasa / Mmm Py

Licence: other
Marshall MRMS Mosaic Python Toolkit

Projects that are alternatives of or similar to Mmm Py

Arxiv Manatee
Arxiv Sanity with novel paper search
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Cvpr18 detect globally refine locally
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Visual Attention Model
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Bempp Cl
A fast Python based just-in-time compiling boundary element library
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Deeplearningwithpython
Machine Learning and Data Science study group starting Sep'2018
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Bottom Up Attention
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
Stars: ✭ 989 (+2572.97%)
Mutual labels:  jupyter-notebook
Fractional differencing gpu
Rapid large-scale fractional differencing with RAPIDS to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Flexx Notebooks
Jupyter notebooks with Flexx examples.
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Vespcn Tensorflow
Tensorflow implementation of VESPCN
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Stock Market Prediction Using Natural Language Processing
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Pr Net
Non-Rigid Point Set Registration Networks
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Perfect Guide About Machine Learning Study
파이썬 머신러닝 완벽 가이드를 교재로 진행한 쏘카 데이터 그룹 사내 스터디 보완 자료
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
True artificial intelligence
真AI人工智能
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Kaggle
DueApe数据科学,Kaggle代码资源分享
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Vietnamese Accent Model
A simple deep learning model to add accent to Vietnamese text.
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Depiction
interpret deep learning models in a framework-independent fashion
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Adventures In Ml Code
This repository holds all the code for the site http://www.adventuresinmachinelearning.com
Stars: ✭ 989 (+2572.97%)
Mutual labels:  jupyter-notebook
Optimal Transport
Optimal transport and generalizations
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Parsing Pdfs
Extracting tabular information from PDFs using python
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook
Deep Learning Coursera
Deep Learning Andrew Ng Coursera
Stars: ✭ 38 (+2.7%)
Mutual labels:  jupyter-notebook

MMM-Py README

The National Oceanic and Atmospheric Administration (NOAA) regularly produces national 3D radar reflectivity mosaics via its Multi-Radar/Multi-Sensor (MRMS) system. These mosaics are wonderful for storm and precipitation analysis and research, but they are distributed in odd formats that NOAA is ever changing. Sometimes you just want to read a file and make a plot!

This is what MMM-Py is for. With it, you can read any version of the MRMS radar mosaics, past or present, and you can analyze, plot, subsection, and output custom mosaics of your own, which MMM-Py can ingest later. MMM-Py is free and open source. It is capable of producing publication-ready figures and analyses, but it also can do quicklook plots so you can check out the cool storm that just happened.

For more info about the latest version of MRMS, see here.

MMM-Py Installation

MMM-Py works under Python 2.7 and 3.4-3.6 on most Mac/Linux setups. Windows installation is currently untested.

Put mmmpy.py in your PYTHONPATH.

You'll need the following Python packages. Most are easily obtained or already installed with common Python frameworks such as Anaconda: numpy, matplotlib, six, netCDF4, os, Basemap, struct, time, calendar, gzip, datetime

You may also want to install pygrib from here. This is an optional dependency.

Get MRMS-modified wgrib2 package and installation info from ftp://ftp.nssl.noaa.gov/projects/MRMS/GRIB2_DECODERS/MRMS_modified_wgrib2_v2.0.1-selectfiles.tgz

Install wgrib2 and note the path to it. Modify the BASE_PATH, TMPDIR, WGRIB2_PATH, and WGRIB2_NAME global variables in mmmpy.py as necessary. TMPDIR is where intermediate netCDFs created by wgrib2 will go.

Without wgrib2 or pygrib, MMM-Py can still read legacy MRMS binaries and netCDFs. The pygrib module will obviate the need to install wgrib2, as it enables direct ingest of the grib2 files without converting to netCDF.

Using MMM-Py

To access everything:

import mmmpy

To see MMM-Py in action, check out the IPython notebooks provided in this distribution.

This conference presentation discusses MMM-Py (among other modules).

MMM-Py was developed at the NASA Marshall Space Flight Center by Timothy Lang ([email protected])

See LICENSE file for NASA open source license information.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].