Property:LabSkill

From CSDMS

This is a property of type Text.

Showing 20 pages using this property.
L
Access data in a DataFrame  +, Create plots of data from a DataFrame  +, Load data from a CSV file using the pandas library  +,
Averaging burst data  +, Cleaning up raw data  +, Exploring potential drivers of velocity changes at our site (meteorological)  +,
Become familiar with a basic configuration of the CEM model  +, Gain hands-on experience with visualizing output in Python  +, Make small changes to key input parameters in CEM  +,
Become familiar with a basic configuration of the HydroTrend model  +, Gain hands-on experience with visualizing output in Python  +, Make small changes to key input parameters in HydroTrend  +,
Become familiar with a basic configuration of the HydroTrend model`  +, Gain hands-on experience with visualizing output in Python  +, Make small changes to key input parameters in HydroTrend  +,
Communicate between two LandLab components with inputs and outputs  +, Create plots using `matplotlib`  +, Read inputs from .csv file  +,
Create functions to generate crater topography  +, Interact with and change input parameters that describe impact cratering  +, Use LandLab model grids  +,
Create plots  +, Use Fastscape and SPACE for landscape evolution  +, Use Landlab to generate a grid  +
Data Visualization  +, Pandas Dataframes  +, Subsetting dataframes  +
Extract shorelines from satellite imagery  +, Extract wave data from wave buoy  +
Familiarize with a basic configuration of the Air Frost Number Model  +, Hands-on experience with visualizing output in Python  +, Make small changes to key input parameters  +,
Import external gridded topography and create NetworkModelGrid (NMG)  +, Learn to create arrays using different random number generators  +, Learn to execute NST forward in time and make plots to understand simulation outputs  +,
Learn how to couple two models using pymt  +, Learn how to run a standalone model in pymt  +
Learn how to use "permamodel" Python module to run Ku model  +, Learn how to use Ku model output and Landlab component to run depth-dependent diffusion model  +, Learn to load, rescale, and visualize DEM data in Python.  +
Learn how to use Landlab to construct a simple two-dimensional numerical model on a regular (raster) grid.  +, Learn to use deAlmeida Overland Flow Landlab component to create a flood sequence.  +
Learn to couple Data and Model Components for overland flow simulation.  +, Learn to use Data Components to download research datasets.  +
Learn to couple Data and Model Components for simulation  +, Learn to use Data Components to download research datasets  +
Learn to create landslide susceptibility map  +, Learn to use Data Components to download research datasets  +
Learn to get the SoilGrids map service information.  +, Learn to use Basic Model Interface to access SoilGrids data and metadata.  +, Learn to use an application programming interface (API) to access SoilGrids data.  +
Learn to set up and run the Heat model  +, Learn to set up and run the Heat model through its BMI  +, View model source code and model BMI source code  +