flowplot 0.0.15

An interactive visualisation ananlyis tool for flow and input-output-storage data

Quickstart

pip install flowplot

from flowplot import cycle
cycle(r".\user-inputs\cycles\Overall.csv", delimiter=';')

Overview

flowplot is a visualisation and analysis tool for hydrological and general flow-stock, input-output-storage data for Python 🐳

Diagrams include

• Cycle, including Circles, Bar graphs, and Line graphs
• TSCompare Time series of multiple simulations and observations, with statistics
• ExceedanceProb Exceedance probability and comparison, multiple simulations
• BoxWhisker Box-whisker plots, multiple simulations
• HeatSeason Seasonality, multiple simulations

User inputs

user-inputs folder includes:

cycles:

• associates the cycle flows as in, out, storage, and sub-flows

flow time series:

• Contains three columns for the date: YYYY, MM, DD
• Column names match those indicated in the cycles csv above
• There can be several csv files holding flow time series
• Columns hold daily values of flows, with name and unit indicated in cycle csv

Units

• standard
  • m3 (meaning m3/day)
  • m3s
    (meaning m3/second)
• with option num_cells_domain:

  • mmcell (meaning mm/day/averaged across all cells)

  • m3cell (meaning m3/day averaged across all cells)

  • m3scell (meaning m3/second averaged across all cells)

• with option cellsize_m2, assuming all cells are the same size in square metres
  • mm (meaning mm/day)

cycle(r".\user-inputs\cycles\Overall.csv", delimiter=';', cellsize_m2=1000*1000, num_cells_domain=153451)

Creates the following diagrams for a user-determined cycle:

1. Circles, showing the partitioned inputs, outputs, net storage changes, and balance, aggregated spatiotemporally;
2. Bar graphs, showing the partitioned inputs, outputs, net storage changes, and balance, aggregated spatiotemporal;
3. Line graphs, overall, showing the inputs, outputs, net storage changes, and balance through time, aggregated spatially;
4. Line graphs, partitioned, showing the partitioned flows through time, aggregated spatially.