{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Ranking\n",
"\n",
"Ranking all projects by a total score can provide a much deeper understanding of the ecosystem. While quantifying the state and health of a project remains challenging, using a multidimensional index creates a more comprehensive picture. A repository's total score is a composite index of three dimensions: **size**, **community** and **activity**. Each dimension contains several indicators, represented by an index used to rank projects relative to each other. Each dimension index is referred to as a score.\n",
"\n",
"```{figure} ../images/ranking_calc.png\n",
"---\n",
"align: center\n",
"width: 100%\n",
"---\n",
"\\- The relationship between the dimensions and indicators within the ranking. \n",
"```\n",
"\n",
"For example, the activity score ranks each project using an index composed of _Total Commits Last Year_, _Issues Closed Last Year_, _Day Until Last Issue Closed_, and _Last Release Data_, which is normalised by 1. The weighted sum of all scores (activity, community, and size) is referred to as the \"total score\". The figure above shows the relationship between the dimensions and indicators within the ranking (for implementation detail, see this [code cell](#dimensions-and-calculations).)\n",
"\n",
"Unlike [stars](./popularity.ipynb), which can provide insight into a project's overall popularity, ranking by total score unveils unpopular but otherwise strong projects. For example, larger projects like [EnergyPlus](https://github.com/NREL/EnergyPlus) suddenly rises to the top. However, as with any index, there are limitations. In this case, monolithic software developments have a higher probability of achieving a high score, meaning that projects which rely more on a modular approach (i.e., projects distributed across multiple repositories) may be significantly underrepresented.\n",
"\n",
"The ranking of the projects according to their [activity](#activity-score) rating highlights the young projects that are still developing rapidly. [DeepTreeAttention](https://github.com/weecology/DeepTreeAttention) in particular stands out here, which is mainly developed by a single person. Other young projects such as [Ozon3](https://github.com/Ozon3Org/Ozon3), [cmip6-downscaling](https://github.com/carbonplan/cmip6-downscaling) or [PowerSimulations.jl](https://github.com/NREL-SIIP/PowerSimulations.jl) show not only a very high activity but the DDS also shows a strong growth of the community of this young projects.\n",
"\n",
"The real value of such health analytics comes into play when development and community data is combined with usage data. Unfortunately, this data is currently only available to a limited extent via Python dependencies. Further work is required to extend usage metrics to include other software package managers and survey methods.\n",
"\n",
"`````{admonition} Tip\n",
":class: tip\n",
"Click the project name and go directly to the repository.\n",
"`````"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"tags": [
"remove-cell"
]
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"import plotly.io as pio\n",
"import plotly.graph_objects as go\n",
"import plotly.express as px\n",
"from opensustainTemplate import *"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"tags": [
"remove-cell"
]
},
"outputs": [],
"source": [
"df_active = pd.read_csv(\"../csv/project_analysis.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"alignmentgroup": "True",
"customdata": [
[
"A whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water usage in buildings.",
"Buildings and Heating",
"https://github.com/NREL/EnergyPlus.git"
],
[
"A cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.",
"Buildings and Heating",
"https://github.com/NREL/OpenStudio.git"
],
[
"A collaborative website for better access to data and models in the hydrologic sciences.",
"Hydrosphere",
"https://github.com/hydroshare/hydroshare.git"
],
[
"A set of toolkits that together provide a system for issuance and management of Energy Attribute Certificates.",
"Energy Distribution and Grids",
"https://github.com/energywebfoundation/origin.git"
],
[
"The Unidata network Common Data Form (netCDF) in C is an interface for scientific data access and a set of freely-distributed software libraries that provide an implementation of the interface.",
"Climate Data Processing and Access",
"https://github.com/Unidata/netcdf-c.git"
],
[
"The Predictive Ecosystem Analyzer is an integrated ecological bioinformatics toolbox.",
"Biosphere",
"https://github.com/PecanProject/pecan.git"
],
[
"A community diagnostic and performance metrics tool for routine evaluation of Earth system models in World Climate Research Programme.",
"Earth and Climate Modeling",
"https://github.com/ESMValGroup/ESMValTool.git"
],
[
"A powerful, format-agnostic, community-driven Python package for analyzing and visualizing Earth science data.",
"Hydrosphere",
"https://github.com/SciTools/iris.git"
],
[
"An open, generic, scalable and independent 'Internet of Things' platform, which enables various connected smart objects in the public space to be easily controlled and monitored.",
"Energy Distribution and Grids",
"https://github.com/OSGP/open-smart-grid-platform.git"
],
[
"Fast and friendly fluid dynamics on CPUs and GPUs.",
"Hydrosphere",
"https://github.com/CliMA/Oceananigans.jl.git"
],
[
"An online marketplace for local food. It enables a network of independent online food stores that connects farmers and food hubs with individuals and local businesses.",
"Agriculture and Nutrition",
"https://github.com/openfoodfoundation/openfoodnetwork.git"
],
[
"A state-of-the-art fully coupled model of the Earth's climate including important biogeochemical and cryospheric processes.",
"Earth and Climate Modeling",
"https://github.com/E3SM-Project/E3SM.git"
],
[
"An open source framework written in Java, that makes it easy to write complex software for power systems simulations and analysis.",
"Energy Modeling and Optimization",
"https://github.com/powsybl/powsybl-core.git"
],
[
"Aims to provide multi-scale, simulation-based, open source computational tools and models to support the design, analysis, optimization, scale-up, operation and troubleshooting of innovative, advanced energy systems.",
"Energy Modeling and Optimization",
"https://github.com/IDAES/idaes-pse.git"
],
[
"A real-time visualization of the CO2 emissions from electricity consumption.",
"Carbon Intensity and Accounting",
"https://github.com/electricitymaps/electricitymaps-contrib.git"
],
[
"A global atmosphere model targeted towards 3 km (\"cloud resolving\") resolution.",
"Atmosphere",
"https://github.com/E3SM-Project/scream.git"
],
[
"Standard Energy Efficiency Data Platform™ is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings.",
"Buildings and Heating",
"https://github.com/SEED-platform/seed.git"
],
[
"A software framework for supporting the efficient development, construction, execution, and scientific interpretation of atmospheric, oceanic, and climate system models.",
"Earth and Climate Modeling",
"https://github.com/NOAA-GFDL/FMS.git"
],
[
"Fast and flexible physics-based battery models in Python.",
"Battery",
"https://github.com/pybamm-team/PyBaMM.git"
],
[
"A simulation framework for modeling coupled flow, transport, and geomechanics in the subsurface.",
"Carbon Capture and Removal",
"https://github.com/GEOSX/GEOSX.git"
],
[
"A domain ontology of the energy-system modeling context.",
"Energy Modeling and Optimization",
"https://github.com/OpenEnergyPlatform/ontology.git"
],
[
"A state-of-the-art atmospheric modeling system designed for both meteorological research and numerical weather prediction.",
"Earth and Climate Modeling",
"https://github.com/wrf-model/WRF.git"
],
[
"Global Superstructure/Workflow currently supporting the Finite-Volume on a Cubed-Sphere Global Forecast System.",
"Earth and Climate Modeling",
"https://github.com/NOAA-EMC/global-workflow.git"
],
[
"Professional interface of the Energy Transition model.",
"Energy Distribution and Grids",
"https://github.com/quintel/etmodel.git"
],
[
"A modular open source multi-regional model incorporating the economy, the climate system and a detailed representation of the energy sector.",
"Sustainable Investment",
"https://github.com/remindmodel/remind.git"
],
[
"The Common Community Physics Package is designed to facilitate the implementation of physics innovations in state-of-the-art atmospheric models, the use of various models to develop physics, and the acceleration of transition of physics innovations to operational NOAA models.",
"Hydrosphere",
"https://github.com/NCAR/ccpp-physics.git"
],
[
"A tool to estimate energy use (kilowatt-hours) and carbon emissions (metric tons CO2e) from public cloud usage.",
"Computation and Communication",
"https://github.com/cloud-carbon-footprint/cloud-carbon-footprint.git"
],
[
"An interface to download and deploy interconnected, grid-aware energy marketplaces.",
"Energy Distribution and Grids",
"https://github.com/gridsingularity/gsy-e.git"
],
[
"Providing a structured database of claims regarding ecological state and change of state.",
"Knowledge Platforms",
"https://github.com/regen-network/regen-ledger.git"
],
[
"A library of derived climate variables, i.e. climate indicators, based on xarray.",
"Climate Data Processing and Access",
"https://github.com/Ouranosinc/xclim.git"
],
[
"Model of Agricultural Production and its Impact on the Environment.",
"Agriculture and Nutrition",
"https://github.com/magpiemodel/magpie.git"
],
[
"An open source web API, initially built to provide traveler information on urban transportation networks.",
"Mobility and Transportation",
"https://github.com/hove-io/navitia.git"
],
[
"A modular, extensible, industrial-strength and field-tested platform for use in electricity, water and other utility operations.",
"Energy Monitoring and Control",
"https://github.com/opfab/operatorfabric-core.git"
],
[
"Today the core uses are in the energy domain, where there is extensive and growing support for a wide-range of electric power system, natural gas, communications and control-schemes, transportation, buildings, and related domain tools.",
"Energy Modeling and Optimization",
"https://github.com/GMLC-TDC/HELICS.git"
],
[
"A set of documented functions for simulating the performance of photovoltaic energy systems.",
"Photovoltaics and Solar Energy",
"https://github.com/pvlib/pvlib-python.git"
],
[
"An integrated web-based workbench for taxonomists and biodiversity scientists.",
"Biosphere",
"https://github.com/SpeciesFileGroup/taxonworks.git"
],
[
"A multi-physics, multi-fidelity tool for simulating the coupled dynamic response of wind turbines and wind farms.",
"Wind Energy",
"https://github.com/OpenFAST/openfast.git"
],
[
"A collaboration server to plan atmospheric research flights.",
"Atmosphere",
"https://github.com/Open-MSS/MSS.git"
],
[
"An Open Optimisation Model of the Earth Energy System.",
"Energy Modeling and Optimization",
"https://github.com/pypsa-meets-earth/pypsa-earth.git"
],
[
"Advance understanding of human and natural influences on the environment through a comprehensive, state-of-the-science, readily accessible global model of atmospheric composition.",
"Atmosphere",
"https://github.com/geoschem/geos-chem.git"
]
],
"hovertemplate": "Project Info: %{customdata[0]}
Topic: %{customdata[1]}
Git URL: %{customdata[2]}",
"legendgroup": "",
"marker": {
"color": [
0.8557953408603687,
0.7263712214471345,
0.7481049054631002,
0.7071129707112971,
0.6754057428214731,
0.8638583638583639,
0.8355420090113967,
0.8637803590285111,
0.8535322777101096,
0.6231042271700549,
0.857922954725973,
0.8774051285699043,
0.7677584006805614,
0.7442307692307693,
0.5590631364562118,
0.8919941420551623,
0.7676632455748922,
0.8198830409356725,
0.5718423372371237,
0.5811590222466355,
0.6768342951360264,
0.6445086705202312,
0.726109556177529,
0.7006305531670967,
0.7894959762812368,
0.6904149834741095,
0.8300304878048781,
0.7478344562078922,
0.7323767935121647,
0.6206239580852584,
0.7343799058084772,
0.8587618403247632,
0.7969543147208122,
0.5661462612982744,
0.4787922358015816,
0.6788910077746809,
0.6067090803932909,
0.6028751123090745,
0.7256983240223464,
0.5625306522805297
],
"coloraxis": "coloraxis",
"pattern": {
"shape": ""
}
},
"name": "",
"offsetgroup": "",
"orientation": "h",
"showlegend": false,
"textposition": "auto",
"type": "bar",
"x": [
0.9520808888558916,
0.9302749876474734,
0.9266623375158765,
0.917478807138282,
0.9122918647154524,
0.91135762514861,
0.9081216193397452,
0.9060440117793394,
0.9052678462449796,
0.903558180640831,
0.9031389978479042,
0.9015710696303136,
0.894668800715646,
0.8933001741089533,
0.8926386426117526,
0.8917697925110843,
0.8902311541914217,
0.8898014124176061,
0.8881654214226127,
0.8849468034072782,
0.8821908566632701,
0.8798161845773581,
0.8786708625701166,
0.8770807552644713,
0.8723624708073966,
0.871005197610415,
0.8703622067495429,
0.8692646909571446,
0.8676033477395654,
0.8671492862476996,
0.8638885071808549,
0.8632663071959502,
0.8625244599568515,
0.8622209024371852,
0.8613857918858621,
0.8587289960039876,
0.8541006418791649,
0.852161054729954,
0.850750140920597,
0.8502234762509607
],
"xaxis": "x",
"y": [
"EnergyPlus",
"OpenStudio",
"HydroShare",
"origin",
"netcdf-c",
"PEcAn",
"ESMValTool",
"Iris",
"Open Smart Grid Platform",
"Oceananigans.jl",
"openfoodnetwork",
"E3SM",
"PowSyBl",
"The IDAES Toolkit",
"Electricity Maps",
"SCREAM",
"SEED",
"The Flexible Modeling System",
"PyBaMM",
"GEOSX",
"The Open Energy Ontology",
"WRF",
"global-workflow",
"ETM Pro",
"REMIND",
"ccpp-physics",
"Cloud Carbon Footprint",
"Grid Singularity Energy Exchange",
"Regen Ledger",
"xclim",
"MAgPIE",
"navitia",
"OperatorFabric",
"HELICS",
"pvlib-python",
"TaxonWorks",
"openfast",
"Mission Support System",
"PyPSA-Earth",
"GEOS-Chem"
],
"yaxis": "y"
}
],
"layout": {
"barmode": "relative",
"coloraxis": {
"colorbar": {
"orientation": "h",
"title": {
"text": "DDS"
},
"x": 0.4,
"y": -0.15
},
"colorscale": [
[
0,
"rgb(237, 239, 93)"
],
[
0.16666666666666666,
"rgb(169, 220, 103)"
],
[
0.3333333333333333,
"rgb(110, 197, 116)"
],
[
0.5,
"rgb(57, 171, 126)"
],
[
0.6666666666666666,
"rgb(13, 143, 129)"
],
[
0.8333333333333334,
"rgb(15, 114, 121)"
],
[
1,
"rgb(36, 86, 104)"
]
]
},
"height": 1000,
"hoverlabel": {
"bgcolor": "white"
},
"images": [
{
"sizex": 0.05,
"sizey": 0.05,
"source": "data:image/png;base64,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",
"x": 1,
"xanchor": "right",
"xref": "paper",
"y": 0,
"yanchor": "bottom",
"yref": "paper"
}
],
"legend": {
"tracegroupgap": 0
},
"margin": {
"b": 0,
"l": 200,
"r": 0,
"t": 40
},
"showlegend": false,
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#040404",
"family": "Open Sans",
"size": 15
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"margin": {
"b": 0
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"font": {
"color": "#040404",
"family": "Open Sans"
},
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "Top 40 total score"
},
"xaxis": {
"anchor": "y",
"domain": [
0,
1
],
"range": [
0.85,
0.96
],
"title": {
"text": "Total Score"
}
},
"yaxis": {
"anchor": "x",
"autorange": "reversed",
"domain": [
0,
1
],
"title": {}
}
}
}
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_total_score = df_active.nlargest(40, \"total_score\")\n",
"\n",
"fig = px.bar(\n",
" df_total_score,\n",
" x=df_total_score[\"total_score\"],\n",
" y=df_total_score[\"project_name\"],\n",
" orientation=\"h\",\n",
" range_x=(0.85, 0.96),\n",
" custom_data=[\"oneliner\", \"topic\", \"git_url\"],\n",
" color=df_total_score[\"development_distribution_score\"],\n",
" color_continuous_scale=color_continuous_scale,\n",
")\n",
"\n",
"fig.update_layout(\n",
" height=1000, # Added parameter\n",
" #width=600,\n",
" xaxis_title=\"Total Score\",\n",
" yaxis_title=None,\n",
" title=\"Top 40 total score\",\n",
" coloraxis_colorbar=dict(\n",
" title='DDS',\n",
" orientation='h',\n",
" y=-0.15,\n",
" x=0.4\n",
" ),\n",
" hoverlabel=dict(bgcolor=\"white\"),\n",
")\n",
"fig.update(layout_showlegend=False)\n",
"fig[\"layout\"].update(margin=dict(l=200, r=0, b=0, t=40))\n",
"\n",
"fig.add_layout_image(\n",
" dict(\n",
" source=logo_img,\n",
" xref=\"paper\",\n",
" yref=\"paper\",\n",
" x=1,\n",
" y=0,\n",
" sizex=0.05,\n",
" sizey=0.05,\n",
" xanchor=\"right\",\n",
" yanchor=\"bottom\",\n",
" )\n",
")\n",
"\n",
"fig.update_traces(\n",
" hovertemplate=\"
\".join(\n",
" [\n",
" \"Project Info: %{customdata[0]}\",\n",
" \"Topic: %{customdata[1]}\",\n",
" \"Git URL: %{customdata[2]}\",\n",
" ]\n",
" )\n",
")\n",
"fig[\"layout\"][\"yaxis\"][\"autorange\"] = \"reversed\"\n",
"config = {\n",
" 'toImageButtonOptions': {\n",
" 'format': 'svg', # one of png, svg, jpeg, webp\n",
" },\n",
" 'responsive':'true'\n",
"}\n",
"fig.show(config=config)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"```{figure} data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\n",
":figclass: caption-hack\n",
":name: total-score\n",
"\\- The 40 Projects with the highest total score\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"alignmentgroup": "True",
"customdata": [
[
"Hyperspectral Image Classification with Attention Aided CNNs.",
"Biosphere",
"https://github.com/weecology/DeepTreeAttention.git"
],
[
"A whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water usage in buildings.",
"Buildings and Heating",
"https://github.com/NREL/EnergyPlus.git"
],
[
"A cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.",
"Buildings and Heating",
"https://github.com/NREL/OpenStudio.git"
],
[
"An open-source package to easily obtain real-time, historical, or forecasted air quality data for anywhere in the world.",
"Air Quality",
"https://github.com/Ozon3Org/Ozon3.git"
],
[
"A set of toolkits that together provide a system for issuance and management of Energy Attribute Certificates.",
"Energy Distribution and Grids",
"https://github.com/energywebfoundation/origin.git"
],
[
"A Julia package for power system modeling and simulation of Power Systems operations.",
"Energy Modeling and Optimization",
"https://github.com/NREL-SIIP/PowerSimulations.jl.git"
],
[
"Climate downscaling using CMIP6 data.",
"Climate Data Processing and Access",
"https://github.com/carbonplan/cmip6-downscaling.git"
],
[
"A collaborative website for better access to data and models in the hydrologic sciences.",
"Hydrosphere",
"https://github.com/hydroshare/hydroshare.git"
],
[
"A free and open source model to compute noise maps.",
"Mobility and Transportation",
"https://github.com/Universite-Gustave-Eiffel/NoiseModelling.git"
],
[
"An integrated web-based workbench for taxonomists and biodiversity scientists.",
"Biosphere",
"https://github.com/SpeciesFileGroup/taxonworks.git"
],
[
"A library for satellite image processing providing all of the functionality necessary for retrieving, and storing EUMETSAT data.",
"Data Catalogs and Interfaces",
"https://github.com/openclimatefix/Satip.git"
],
[
"A software for ingesting, operating on and visualizing all ESA Climate Change Initiative data.",
"Climate Data Processing and Access",
"https://github.com/CCI-Tools/cate.git"
],
[
"Seeks to fill a critical need for high-quality, publicly-accessible, hourly grid emissions data that can be used for GHG accounting, policymaking, academic research, and energy attribute certificate markets.",
"Carbon Intensity and Accounting",
"https://github.com/singularity-energy/open-grid-emissions.git"
],
[
"Aims to ensure quality, transparency and reproducibility in energy system research. It is a collection of various tools and information and that help working with energy-related data.",
"Energy Modeling and Optimization",
"https://github.com/OpenEnergyPlatform/oeplatform.git"
],
[
"An online marketplace for local food. It enables a network of independent online food stores that connects farmers and food hubs with individuals and local businesses.",
"Agriculture and Nutrition",
"https://github.com/openfoodfoundation/openfoodnetwork.git"
],
[
"The open-source United States Energy Policy Simulator estimates environmental and economic impacts of hundreds of climate and energy policies.",
"Energy Modeling and Optimization",
"https://github.com/EnergyInnovation/eps-us.git"
],
[
"Fast and friendly fluid dynamics on CPUs and GPUs.",
"Hydrosphere",
"https://github.com/CliMA/Oceananigans.jl.git"
],
[
"A platform for collecting and disseminating data for the Sustainable Development Goal global indicators.",
"Sustainable Development Goals",
"https://github.com/open-sdg/open-sdg.git"
],
[
"A Python package which is used to make short term forecasts for the energy sector.",
"Energy Modeling and Optimization",
"https://github.com/OpenSTEF/openstef.git"
],
[
"A traffic simulation game exploring how small changes to roads affect cyclists, transit users, pedestrians, and drivers.",
"Mobility and Transportation",
"https://github.com/a-b-street/abstreet.git"
],
[
"The Super Resolution for Renewable Resource Data software uses generative adversarial networks to create synthetic high-resolution wind and solar spatiotemporal data from coarse low-resolution inputs.",
"Datasets on Energy Systems",
"https://github.com/NREL/sup3r.git"
],
[
"A free mapping tool to support interdisciplinary Greenland-focused research, teaching, decision making, and collaboration.",
"Cryosphere",
"https://github.com/nsidc/qgreenland.git"
],
[
"An Open Optimisation Model of the Earth Energy System.",
"Energy Modeling and Optimization",
"https://github.com/pypsa-meets-earth/pypsa-earth.git"
],
[
"A real-time visualization of the CO2 emissions from electricity consumption.",
"Carbon Intensity and Accounting",
"https://github.com/electricitymaps/electricitymaps-contrib.git"
],
[
"Predicts the spectral albedo of snow and glacier ice between 200nm to 5000nm given information about the illumination conditions, ice structure and the type and concentration particulates.",
"Cryosphere",
"https://github.com/jmcook1186/biosnicar-py.git"
],
[
"Blends structured wildlife research with artificial intelligence, citizen science, and computer vision to speed population analysis and develop new insights to help fight extinction.",
"Biosphere",
"https://github.com/WildMeOrg/Wildbook.git"
],
[
"Offers open data, visualizations and analysis to help policymakers, researchers and other stakeholders gather insights on countries' climate progress.",
"Knowledge Platforms",
"https://github.com/ClimateWatch-Vizzuality/climate-watch.git"
],
[
"An extensible EV Charge Controller with PV integration implemented in Go.",
"Mobility and Transportation",
"https://github.com/evcc-io/evcc.git"
],
[
"A package built to enable interoperability and scalability in ocean sonar data processing.",
"Water Supply and Quality",
"https://github.com/OSOceanAcoustics/echopype.git"
],
[
"Humanity's open-source CNC farming machine.",
"Agriculture and Nutrition",
"https://github.com/FarmBot/Farmbot-Web-App.git"
],
[
"A tool to estimate energy use (kilowatt-hours) and carbon emissions (metric tons CO2e) from public cloud usage.",
"Computation and Communication",
"https://github.com/cloud-carbon-footprint/cloud-carbon-footprint.git"
],
[
"A testbed platform to model sequential decision making in power systems.",
"Energy Distribution and Grids",
"https://github.com/rte-france/Grid2Op.git"
],
[
"A watershed-modeling web app for citizens, conservation practitioners, municipal decision-makers, educators, and students.",
"Water Supply and Quality",
"https://github.com/WikiWatershed/model-my-watershed.git"
],
[
"Code base for the U.S. EPA's Community Multiscale Air Quality Model.",
"Air Quality",
"https://github.com/USEPA/CMAQ.git"
],
[
"Enables users to apply machine learning techniques for classifying image time series obtained from earth observation data cubes.",
"Soil and Land",
"https://github.com/e-sensing/sits.git"
],
[
"The Unidata network Common Data Form (netCDF) in C is an interface for scientific data access and a set of freely-distributed software libraries that provide an implementation of the interface.",
"Climate Data Processing and Access",
"https://github.com/Unidata/netcdf-c.git"
],
[
"The Visualization and Analysis Platform for Ocean, Atmosphere and Solar Researchers.",
"Hydrosphere",
"https://github.com/NCAR/VAPOR.git"
],
[
"A library of derived climate variables, i.e. climate indicators, based on xarray.",
"Climate Data Processing and Access",
"https://github.com/Ouranosinc/xclim.git"
],
[
"A tool capable of modeling walking and cycling accessibility.",
"Mobility and Transportation",
"https://github.com/goat-community/goat.git"
],
[
"This package simulates the behaviors of an ensemble of phytoplankton individuals.",
"Biosphere",
"https://github.com/JuliaOcean/PlanktonIndividuals.jl.git"
]
],
"hovertemplate": "Project Info: %{customdata[0]}
Topic: %{customdata[1]}
Git URL: %{customdata[2]}",
"legendgroup": "",
"marker": {
"color": [
0.0027118644067796,
0.8557953408603687,
0.7263712214471345,
0.4560439560439561,
0.7071129707112971,
0.269703656998739,
0.6579439252336449,
0.7481049054631002,
0.5244956772334294,
0.6788910077746809,
0.659432387312187,
0.5007675775253301,
0.4658753709198813,
0.3960749330954505,
0.857922954725973,
0.4836065573770491,
0.6231042271700549,
0.2491417361451692,
0.7502673796791444,
0.0502191609267376,
0.3086003372681282,
0.1802168021680217,
0.7256983240223464,
0.5590631364562118,
0.2735042735042735,
0.7769125057260651,
0.621670592498641,
0.2349794238683127,
0.6072222222222222,
0.2469677419354838,
0.8300304878048781,
0.3474264705882353,
0.2797411647585863,
0.8136309825807543,
0.6461273666092944,
0.6754057428214731,
0.7008208321539768,
0.6206239580852584,
0.5708897270911915,
0.069129916567342
],
"coloraxis": "coloraxis",
"pattern": {
"shape": ""
}
},
"name": "",
"offsetgroup": "",
"orientation": "h",
"showlegend": false,
"textposition": "auto",
"type": "bar",
"x": [
0.882164790174002,
0.8258700102354145,
0.7863357215967246,
0.7817297850562948,
0.779682702149437,
0.7753326509723644,
0.7709825997952917,
0.7635619242579325,
0.7621545547594678,
0.7616427840327533,
0.7561412487205732,
0.7558853633572159,
0.7548618219037871,
0.7543500511770727,
0.753582395087001,
0.7534544524053224,
0.7523029682702149,
0.7510235414534289,
0.7484646878198566,
0.7452661207778914,
0.7441146366427841,
0.7432190378710338,
0.7423234390992834,
0.7418116683725691,
0.7409160696008189,
0.7389969293756397,
0.7388689866939611,
0.7384851586489253,
0.736310133060389,
0.7360542476970318,
0.735670419651996,
0.7350307062436028,
0.7342630501535313,
0.7341351074718526,
0.7318321392016377,
0.7318321392016376,
0.7314483111566018,
0.7311924257932446,
0.7302968270214943,
0.72978505629478
],
"xaxis": "x",
"y": [
"DeepTreeAttention",
"EnergyPlus",
"OpenStudio",
"Ozone",
"origin",
"PowerSimulations.jl",
"cmip6-downscaling",
"HydroShare",
"NoiseModelling",
"TaxonWorks",
"Satip",
"Cate",
"Open Grid Emissions Initiative",
"Open Energy Platform",
"openfoodnetwork",
"Energy Policy Simulator",
"Oceananigans.jl",
"open-sdg",
"OpenSTEF",
"A/B Street",
"sup3r",
"QGreenland",
"PyPSA-Earth",
"Electricity Maps",
"BioSNICAR",
"Wildbook",
"Climate Watch",
"EVCC",
"Echopype",
"Farmbot",
"Cloud Carbon Footprint",
"Grid2Op",
"Model My Watershed",
"CMAQ",
"SITS",
"netcdf-c",
"VAPOR",
"xclim",
"goat",
"PlanktonIndividuals.jl"
],
"yaxis": "y"
}
],
"layout": {
"barmode": "relative",
"coloraxis": {
"colorbar": {
"orientation": "h",
"title": {
"text": "DDS"
},
"x": 0.4,
"y": -0.15
},
"colorscale": [
[
0,
"rgb(237, 239, 93)"
],
[
0.16666666666666666,
"rgb(169, 220, 103)"
],
[
0.3333333333333333,
"rgb(110, 197, 116)"
],
[
0.5,
"rgb(57, 171, 126)"
],
[
0.6666666666666666,
"rgb(13, 143, 129)"
],
[
0.8333333333333334,
"rgb(15, 114, 121)"
],
[
1,
"rgb(36, 86, 104)"
]
]
},
"dragmode": false,
"height": 1000,
"hoverlabel": {
"bgcolor": "white"
},
"images": [
{
"sizex": 0.05,
"sizey": 0.05,
"source": "data:image/png;base64,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",
"x": 1,
"xanchor": "right",
"xref": "paper",
"y": 0,
"yanchor": "bottom",
"yref": "paper"
}
],
"legend": {
"tracegroupgap": 0
},
"margin": {
"b": 0,
"l": 200,
"r": 0,
"t": 40
},
"showlegend": false,
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#040404",
"family": "Open Sans",
"size": 15
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"margin": {
"b": 0
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"font": {
"color": "#040404",
"family": "Open Sans"
},
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "Top 40 activity score"
},
"xaxis": {
"anchor": "y",
"domain": [
0,
1
],
"range": [
0.7,
0.9
],
"title": {
"text": "Activity score"
}
},
"yaxis": {
"anchor": "x",
"autorange": "reversed",
"domain": [
0,
1
],
"title": {}
}
}
}
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_activity_score = df_active.nlargest(40, \"activity\")\n",
"\n",
"fig = px.bar(\n",
" df_activity_score,\n",
" x=df_activity_score[\"activity\"],\n",
" y=df_activity_score[\"project_name\"],\n",
" orientation=\"h\",\n",
" custom_data=[\"oneliner\", \"topic\", \"git_url\"],\n",
" color=df_activity_score[\"development_distribution_score\"],\n",
" color_continuous_scale=color_continuous_scale,\n",
" range_x=(0.7, 0.9),\n",
")\n",
"\n",
"fig.update_layout(\n",
" height=1000, # Added parameter\n",
" #width=600,\n",
" xaxis_title=\"Activity score\",\n",
" yaxis_title=None,\n",
" title=\"Top 40 activity score\",\n",
" coloraxis_colorbar=dict(\n",
" title='DDS',\n",
" orientation='h',\n",
" y=-0.15,\n",
" x=0.4\n",
" ),\n",
" hoverlabel=dict(\n",
" bgcolor=\"white\",\n",
" ),\n",
" dragmode=False,\n",
")\n",
"fig.update(layout_showlegend=False)\n",
"fig[\"layout\"].update(margin=dict(l=200, r=0, b=0, t=40))\n",
"\n",
"fig.add_layout_image(\n",
" dict(\n",
" source=logo_img,\n",
" xref=\"paper\",\n",
" yref=\"paper\",\n",
" x=1,\n",
" y=0,\n",
" sizex=0.05,\n",
" sizey=0.05,\n",
" xanchor=\"right\",\n",
" yanchor=\"bottom\",\n",
" )\n",
")\n",
"\n",
"fig.update_traces(\n",
" hovertemplate=\"
\".join(\n",
" [\n",
" \"Project Info: %{customdata[0]}\",\n",
" \"Topic: %{customdata[1]}\",\n",
" \"Git URL: %{customdata[2]}\",\n",
" ]\n",
" )\n",
")\n",
"fig[\"layout\"][\"yaxis\"][\"autorange\"] = \"reversed\"\n",
"config = {\n",
" 'toImageButtonOptions': {\n",
" 'format': 'svg', # one of png, svg, jpeg, webp\n",
" },\n",
" 'responsive':'true'\n",
"}\n",
"fig.show(config=config)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"```{figure} data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\n",
":figclass: caption-hack\n",
":name: activity-score\n",
"\\- The 40 Projects with the highest activity score\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"alignmentgroup": "True",
"customdata": [
[
"Allows applicants to demonstrate their ability to analyze and develop software that makes use of big energy production data.",
"Datasets on Energy Systems",
"https://github.com/enechange/EnergyDataSimulationChallenge.git"
],
[
"The Predictive Ecosystem Analyzer is an integrated ecological bioinformatics toolbox.",
"Biosphere",
"https://github.com/PecanProject/pecan.git"
],
[
"A community diagnostic and performance metrics tool for routine evaluation of Earth system models in World Climate Research Programme.",
"Earth and Climate Modeling",
"https://github.com/ESMValGroup/ESMValTool.git"
],
[
"An open source web API, initially built to provide traveler information on urban transportation networks.",
"Mobility and Transportation",
"https://github.com/hove-io/navitia.git"
],
[
"A global atmosphere model targeted towards 3 km (\"cloud resolving\") resolution.",
"Atmosphere",
"https://github.com/E3SM-Project/scream.git"
],
[
"A software framework for supporting the efficient development, construction, execution, and scientific interpretation of atmospheric, oceanic, and climate system models.",
"Earth and Climate Modeling",
"https://github.com/NOAA-GFDL/FMS.git"
],
[
"An open, generic, scalable and independent 'Internet of Things' platform, which enables various connected smart objects in the public space to be easily controlled and monitored.",
"Energy Distribution and Grids",
"https://github.com/OSGP/open-smart-grid-platform.git"
],
[
"A state-of-the-art fully coupled model of the Earth's climate including important biogeochemical and cryospheric processes.",
"Earth and Climate Modeling",
"https://github.com/E3SM-Project/E3SM.git"
],
[
"A powerful, format-agnostic, community-driven Python package for analyzing and visualizing Earth science data.",
"Hydrosphere",
"https://github.com/SciTools/iris.git"
],
[
"The Model for Prediction Across Scales is a collaborative project for developing atmosphere, ocean, and other earth-system simulation components for use in climate, regional climate, and weather studies.",
"Earth and Climate Modeling",
"https://github.com/MPAS-Dev/MPAS-Model.git"
],
[
"Aims to provide multi-scale, simulation-based, open source computational tools and models to support the design, analysis, optimization, scale-up, operation and troubleshooting of innovative, advanced energy systems.",
"Energy Modeling and Optimization",
"https://github.com/IDAES/idaes-pse.git"
],
[
"A web application developed by NASA EOSDIS to enable data discovery, search, comparison, visualization, and access across EOSDIS' Earth Science data holdings.",
"Data Catalogs and Interfaces",
"https://github.com/nasa/earthdata-search.git"
],
[
"A massively parallel, block-structured adaptive-mesh, incompressible flow solver for wind turbine and wind farm simulations.",
"Wind Energy",
"https://github.com/Exawind/amr-wind.git"
],
[
"An open source framework written in Java, that makes it easy to write complex software for power systems simulations and analysis.",
"Energy Modeling and Optimization",
"https://github.com/powsybl/powsybl-core.git"
],
[
"Global Superstructure/Workflow currently supporting the Finite-Volume on a Cubed-Sphere Global Forecast System.",
"Earth and Climate Modeling",
"https://github.com/NOAA-EMC/global-workflow.git"
],
[
"An interface to download and deploy interconnected, grid-aware energy marketplaces.",
"Energy Distribution and Grids",
"https://github.com/gridsingularity/gsy-e.git"
],
[
"Solver for wind farm simulations targeting exascale computational platforms.",
"Wind Energy",
"https://github.com/Exawind/nalu-wind.git"
],
[
"The Unidata network Common Data Form (netCDF) in C is an interface for scientific data access and a set of freely-distributed software libraries that provide an implementation of the interface.",
"Climate Data Processing and Access",
"https://github.com/Unidata/netcdf-c.git"
],
[
"A collaborative website for better access to data and models in the hydrologic sciences.",
"Hydrosphere",
"https://github.com/hydroshare/hydroshare.git"
],
[
"A modular open source multi-regional model incorporating the economy, the climate system and a detailed representation of the energy sector.",
"Sustainable Investment",
"https://github.com/remindmodel/remind.git"
],
[
"A state-of-the-art atmospheric modeling system designed for both meteorological research and numerical weather prediction.",
"Earth and Climate Modeling",
"https://github.com/wrf-model/WRF.git"
],
[
"A numerical representation of the ocean fluid with applications from the process scale to the planetary circulation scale.",
"Earth and Climate Modeling",
"https://github.com/NOAA-GFDL/MOM6.git"
],
[
"A whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water usage in buildings.",
"Buildings and Heating",
"https://github.com/NREL/EnergyPlus.git"
],
[
"Model of Agricultural Production and its Impact on the Environment.",
"Agriculture and Nutrition",
"https://github.com/magpiemodel/magpie.git"
],
[
"A simulation framework for modeling coupled flow, transport, and geomechanics in the subsurface.",
"Carbon Capture and Removal",
"https://github.com/GEOSX/GEOSX.git"
],
[
"A cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.",
"Buildings and Heating",
"https://github.com/NREL/OpenStudio.git"
],
[
"Groundwater Wells and Aquifers application for the Ministry of Environment in British Columbia.",
"Water Supply and Quality",
"https://github.com/bcgov/gwells.git"
],
[
"A domain ontology of the energy-system modeling context.",
"Energy Modeling and Optimization",
"https://github.com/OpenEnergyPlatform/ontology.git"
],
[
"Providing a structured database of claims regarding ecological state and change of state.",
"Knowledge Platforms",
"https://github.com/regen-network/regen-ledger.git"
],
[
"Optimization of Aerodynamic systems.",
"Wind Energy",
"https://github.com/OpenMDAO/OpenMDAO.git"
],
[
"Track emissions from Compute and recommend ways to reduce their impact on the environment.",
"Computation and Communication",
"https://github.com/mlco2/codecarbon.git"
],
[
"A set of toolkits that together provide a system for issuance and management of Energy Attribute Certificates.",
"Energy Distribution and Grids",
"https://github.com/energywebfoundation/origin.git"
],
[
"An Open Optimisation Model of the Earth Energy System.",
"Energy Modeling and Optimization",
"https://github.com/pypsa-meets-earth/pypsa-earth.git"
],
[
"Fast and friendly fluid dynamics on CPUs and GPUs.",
"Hydrosphere",
"https://github.com/CliMA/Oceananigans.jl.git"
],
[
"An open source, object-oriented, simple global climate carbon-cycle model.",
"Earth and Climate Modeling",
"https://github.com/JGCRI/hector.git"
],
[
"Framework for Optimization and Quantification of Uncertainty and Surrogates.",
"Carbon Capture and Removal",
"https://github.com/CCSI-Toolset/FOQUS.git"
],
[
"Standard Energy Efficiency Data Platform™ is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings.",
"Buildings and Heating",
"https://github.com/SEED-platform/seed.git"
],
[
"Assesses the potential risk and forecasts the impact of climate hazards on the most vulnerable communities, in order to design risk reduction activities and target disaster responses.",
"Natural Hazard and Poverty",
"https://github.com/WFP-VAM/prism-app.git"
],
[
"A community platform for Big Data geoscience.",
"Earth and Climate Modeling",
"https://github.com/pangeo-data/pangeo.git"
],
[
"The Common Community Physics Package is designed to facilitate the implementation of physics innovations in state-of-the-art atmospheric models, the use of various models to develop physics, and the acceleration of transition of physics innovations to operational NOAA models.",
"Hydrosphere",
"https://github.com/NCAR/ccpp-physics.git"
]
],
"hovertemplate": "Project Info: %{customdata[0]}
Topic: %{customdata[1]}
Git URL: %{customdata[2]}",
"legendgroup": "",
"marker": {
"color": [
0.8878737541528239,
0.8638583638583639,
0.8355420090113967,
0.8587618403247632,
0.8919941420551623,
0.8198830409356725,
0.8535322777101096,
0.8774051285699043,
0.8637803590285111,
0.810784071234232,
0.7442307692307693,
0.752362381880906,
0.7642466822794691,
0.7677584006805614,
0.726109556177529,
0.7478344562078922,
0.7882816346627277,
0.6754057428214731,
0.7481049054631002,
0.7894959762812368,
0.6445086705202312,
0.6848334709606385,
0.8557953408603687,
0.7343799058084772,
0.5811590222466355,
0.7263712214471345,
0.7089129314786193,
0.6768342951360264,
0.7323767935121647,
0.6906206252916472,
0.8112449799196787,
0.7071129707112971,
0.7256983240223464,
0.6231042271700549,
0.7503121098626717,
0.8,
0.7676632455748922,
0.6728016359918201,
0.7933884297520661,
0.6904149834741095
],
"coloraxis": "coloraxis",
"pattern": {
"shape": ""
}
},
"name": "",
"offsetgroup": "",
"orientation": "h",
"showlegend": false,
"textposition": "auto",
"type": "bar",
"x": [
0.990617536676902,
0.9831115660184238,
0.9824292050494712,
0.9749232343909928,
0.974070283179802,
0.971682019788468,
0.9711702490617538,
0.9658819515523712,
0.9626407369498464,
0.960934834527465,
0.9578642101671784,
0.953770044353463,
0.9489935175707948,
0.9433640395769364,
0.9401228249744116,
0.9377345615830772,
0.9368816103718868,
0.9338109860116002,
0.9297168201978848,
0.923063800750597,
0.9211873080859774,
0.9181166837256908,
0.9172637325145002,
0.9167519617877856,
0.9157284203343568,
0.9153872398498808,
0.9152166496076424,
0.9106107130672124,
0.9090754008870692,
0.908734220402593,
0.90532241555783,
0.9036165131354488,
0.8967929034459229,
0.8923575571477311,
0.8918457864210168,
0.8915046059365404,
0.8911634254520641,
0.8901398839986353,
0.8899692937563971,
0.8865574889116342
],
"xaxis": "x",
"y": [
"EnergyDataSimulationChallenge",
"PEcAn",
"ESMValTool",
"navitia",
"SCREAM",
"The Flexible Modeling System",
"Open Smart Grid Platform",
"E3SM",
"Iris",
"MPAS",
"The IDAES Toolkit",
"Earthdata Search",
"amr-wind",
"PowSyBl",
"global-workflow",
"Grid Singularity Energy Exchange",
"nalu-wind",
"netcdf-c",
"HydroShare",
"REMIND",
"WRF",
"MOM6",
"EnergyPlus",
"MAgPIE",
"GEOSX",
"OpenStudio",
"gwells",
"The Open Energy Ontology",
"Regen Ledger",
"OpenMDAO",
"CodeCarbon",
"origin",
"PyPSA-Earth",
"Oceananigans.jl",
"hector",
"FOQUS",
"SEED",
"PRISM",
"pangeo",
"ccpp-physics"
],
"yaxis": "y"
}
],
"layout": {
"barmode": "relative",
"coloraxis": {
"colorbar": {
"orientation": "h",
"title": {
"text": "DDS"
},
"x": 0.4,
"y": -0.15
},
"colorscale": [
[
0,
"rgb(237, 239, 93)"
],
[
0.16666666666666666,
"rgb(169, 220, 103)"
],
[
0.3333333333333333,
"rgb(110, 197, 116)"
],
[
0.5,
"rgb(57, 171, 126)"
],
[
0.6666666666666666,
"rgb(13, 143, 129)"
],
[
0.8333333333333334,
"rgb(15, 114, 121)"
],
[
1,
"rgb(36, 86, 104)"
]
]
},
"dragmode": false,
"height": 1000,
"hoverlabel": {
"bgcolor": "white"
},
"images": [
{
"sizex": 0.05,
"sizey": 0.05,
"source": "data:image/png;base64,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",
"x": 1,
"xanchor": "right",
"xref": "paper",
"y": 0,
"yanchor": "bottom",
"yref": "paper"
}
],
"legend": {
"tracegroupgap": 0
},
"margin": {
"b": 0,
"l": 30,
"r": 0,
"t": 40
},
"showlegend": false,
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#040404",
"family": "Open Sans",
"size": 15
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"margin": {
"b": 0
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"font": {
"color": "#040404",
"family": "Open Sans"
},
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "Top 40 community score"
},
"xaxis": {
"anchor": "y",
"domain": [
0,
1
],
"range": [
0.85,
1
],
"title": {
"text": "Community score"
}
},
"yaxis": {
"anchor": "x",
"autorange": "reversed",
"domain": [
0,
1
],
"title": {}
}
}
}
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_community_score = df_active.nlargest(40, \"community\")\n",
"\n",
"fig = px.bar(\n",
" df_community_score,\n",
" x=df_community_score[\"community\"],\n",
" y=df_community_score[\"project_name\"],\n",
" orientation=\"h\",\n",
" range_x=(0.85, 1),\n",
" custom_data=[\"oneliner\", \"topic\", \"git_url\"],\n",
" color=df_community_score[\"development_distribution_score\"],\n",
" color_continuous_scale=color_continuous_scale,\n",
")\n",
"\n",
"fig.update_layout(\n",
" height=1000, # Added parameter\n",
" #width=600,\n",
" xaxis_title=\"Community score\",\n",
" yaxis_title=None,\n",
" title=\"Top 40 community score\",\n",
" coloraxis_colorbar=dict(\n",
" title='DDS',\n",
" orientation='h',\n",
" y=-0.15,\n",
" x=0.4\n",
" ),\n",
" hoverlabel=dict(\n",
" bgcolor=\"white\",\n",
" ),\n",
" dragmode=False,\n",
")\n",
"fig.update(layout_showlegend=False)\n",
"fig[\"layout\"].update(margin=dict(l=200, r=0, b=0, t=40))\n",
"\n",
"fig.add_layout_image(\n",
" dict(\n",
" source=logo_img,\n",
" xref=\"paper\",\n",
" yref=\"paper\",\n",
" x=1,\n",
" y=0,\n",
" sizex=0.05,\n",
" sizey=0.05,\n",
" xanchor=\"right\",\n",
" yanchor=\"bottom\",\n",
" )\n",
")\n",
"\n",
"fig.update_traces(\n",
" hovertemplate=\"
\".join(\n",
" [\n",
" \"Project Info: %{customdata[0]}\",\n",
" \"Topic: %{customdata[1]}\",\n",
" \"Git URL: %{customdata[2]}\",\n",
" ]\n",
" )\n",
")\n",
"fig[\"layout\"].update(margin=dict(l=30, r=0, b=0, t=40))\n",
"fig[\"layout\"][\"yaxis\"][\"autorange\"] = \"reversed\"\n",
"config = {\n",
" 'toImageButtonOptions': {\n",
" 'format': 'svg', # one of png, svg, jpeg, webp\n",
" },\n",
" 'responsive':'true'\n",
"}\n",
"fig.show(config=config)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"```{figure} data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\n",
":figclass: caption-hack\n",
":name: community-score\n",
"\\- The 40 Projects with the highest community score\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"tags": [
"remove-input"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"alignmentgroup": "True",
"customdata": [
[
"An online marketplace for local food. It enables a network of independent online food stores that connects farmers and food hubs with individuals and local businesses.",
"Agriculture and Nutrition",
"https://github.com/openfoodfoundation/openfoodnetwork.git"
],
[
"A state-of-the-art fully coupled model of the Earth's climate including important biogeochemical and cryospheric processes.",
"Earth and Climate Modeling",
"https://github.com/E3SM-Project/E3SM.git"
],
[
"A whole building energy simulation program that engineers, architects, and researchers use to model both energy consumption and water usage in buildings.",
"Buildings and Heating",
"https://github.com/NREL/EnergyPlus.git"
],
[
"An online, global and near real-time forest monitoring tool.",
"Biosphere",
"https://github.com/Vizzuality/gfw.git"
],
[
"An open source web API, initially built to provide traveler information on urban transportation networks.",
"Mobility and Transportation",
"https://github.com/hove-io/navitia.git"
],
[
"An agricultural modeling framework used extensively worldwide.",
"Agriculture and Nutrition",
"https://github.com/APSIMInitiative/ApsimX.git"
],
[
"The Predictive Ecosystem Analyzer is an integrated ecological bioinformatics toolbox.",
"Biosphere",
"https://github.com/PecanProject/pecan.git"
],
[
"QGIS plugin for estimating impact from natural disasters.",
"Natural Hazard and Poverty",
"https://github.com/inasafe/inasafe.git"
],
[
"Open source and open data platform that can predict when your plantings will be ready to harvest.",
"Agriculture and Nutrition",
"https://github.com/Growstuff/growstuff.git"
],
[
"A global atmosphere model targeted towards 3 km (\"cloud resolving\") resolution.",
"Atmosphere",
"https://github.com/E3SM-Project/scream.git"
],
[
"Optimization of Aerodynamic systems.",
"Wind Energy",
"https://github.com/OpenMDAO/OpenMDAO.git"
],
[
"A collaborative website for better access to data and models in the hydrologic sciences.",
"Hydrosphere",
"https://github.com/hydroshare/hydroshare.git"
],
[
"A self-hosted platform to order meals in your neighborhood and get them delivered by bike couriers.",
"Mobility and Transportation",
"https://github.com/coopcycle/coopcycle-web.git"
],
[
"A powerful, format-agnostic, community-driven Python package for analyzing and visualizing Earth science data.",
"Hydrosphere",
"https://github.com/SciTools/iris.git"
],
[
"A cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance.",
"Buildings and Heating",
"https://github.com/NREL/OpenStudio.git"
],
[
"The Framework for Modeling Behavior, Energy, Autonomy, and Mobility in Transportation Systems.",
"Mobility and Transportation",
"https://github.com/LBNL-UCB-STI/beam.git"
],
[
"A platform that provides services for collecting and storing data from buildings and devices. It provides an environment for developing applications that interact with data.",
"Buildings and Heating",
"https://github.com/VOLTTRON/volttron.git"
],
[
"A community diagnostic and performance metrics tool for routine evaluation of Earth system models in World Climate Research Programme.",
"Earth and Climate Modeling",
"https://github.com/ESMValGroup/ESMValTool.git"
],
[
"A real-time visualization of the CO2 emissions from electricity consumption.",
"Carbon Intensity and Accounting",
"https://github.com/electricitymaps/electricitymaps-contrib.git"
],
[
"Helps you identify the plants and animals around you.",
"Biosphere",
"https://github.com/inaturalist/inaturalist.git"
],
[
"The Unidata network Common Data Form (netCDF) in C is an interface for scientific data access and a set of freely-distributed software libraries that provide an implementation of the interface.",
"Climate Data Processing and Access",
"https://github.com/Unidata/netcdf-c.git"
],
[
"A free and open source library with dynamic simulation models for building energy and control systems.",
"Buildings and Heating",
"https://github.com/lbl-srg/modelica-buildings.git"
],
[
"Standard Energy Efficiency Data Platform™ is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings.",
"Buildings and Heating",
"https://github.com/SEED-platform/seed.git"
],
[
"Groundwater Wells and Aquifers application for the Ministry of Environment in British Columbia.",
"Water Supply and Quality",
"https://github.com/bcgov/gwells.git"
],
[
"Fast and friendly fluid dynamics on CPUs and GPUs.",
"Hydrosphere",
"https://github.com/CliMA/Oceananigans.jl.git"
],
[
"A state-of-the-art atmospheric modeling system designed for both meteorological research and numerical weather prediction.",
"Earth and Climate Modeling",
"https://github.com/wrf-model/WRF.git"
],
[
"A set of toolkits that together provide a system for issuance and management of Energy Attribute Certificates.",
"Energy Distribution and Grids",
"https://github.com/energywebfoundation/origin.git"
],
[
"Makes it easy for people to design public spaces together.",
"Mobility and Transportation",
"https://github.com/streetmix/streetmix.git"
],
[
"Web application for organization of foodsaving groups worldwide.",
"Agriculture and Nutrition",
"https://github.com/karrot-dev/karrot-frontend.git"
],
[
"Fast and flexible physics-based battery models in Python.",
"Battery",
"https://github.com/pybamm-team/PyBaMM.git"
],
[
"A collection of tools in Python for reading, visualizing and performing calculations with weather data.",
"Meteorological Observation and Forecast",
"https://github.com/Unidata/MetPy.git"
],
[
"A modular, extensible, industrial-strength and field-tested platform for use in electricity, water and other utility operations.",
"Energy Monitoring and Control",
"https://github.com/opfab/operatorfabric-core.git"
],
[
"Accelerate the attainment of the sustainable development goals in low- and middle-income countries by facilitating the discovery, development, use of, and investment in digital public goods.",
"Knowledge Platforms",
"https://github.com/DPGAlliance/publicgoods-candidates.git"
],
[
"A powerful open source web application for processing, logging and visualizing energy, temperature and other environmental data.",
"Energy Monitoring and Control",
"https://github.com/emoncms/emoncms.git"
],
[
"An open, generic, scalable and independent 'Internet of Things' platform, which enables various connected smart objects in the public space to be easily controlled and monitored.",
"Energy Distribution and Grids",
"https://github.com/OSGP/open-smart-grid-platform.git"
],
[
"Humanity's open-source CNC farming machine.",
"Agriculture and Nutrition",
"https://github.com/FarmBot/Farmbot-Web-App.git"
],
[
"Professional interface of the Energy Transition model.",
"Energy Distribution and Grids",
"https://github.com/quintel/etmodel.git"
],
[
"Open Source Energy Management System.",
"Energy Monitoring and Control",
"https://github.com/OpenEMS/openems.git"
],
[
"Features hundreds of data sets all in one place on the state of the planet's resources and citizens.",
"Data Catalogs and Interfaces",
"https://github.com/resource-watch/resource-watch.git"
],
[
"Helps you to analyze the effects of building retrofits, land-use planning, district heating and cooling and renewable energy on the future costs, emissions and energy consumption of neighborhoods and districts.",
"Buildings and Heating",
"https://github.com/architecture-building-systems/CityEnergyAnalyst.git"
]
],
"hovertemplate": "Project Info: %{customdata[0]}
Topic: %{customdata[1]}
Git URL: %{customdata[2]}",
"legendgroup": "",
"marker": {
"color": [
0.857922954725973,
0.8774051285699043,
0.8557953408603687,
0.6636363636363636,
0.8587618403247632,
0.6563488670371953,
0.8638583638583639,
0.731155981015204,
0.4441517386722866,
0.8919941420551623,
0.6906206252916472,
0.7481049054631002,
0.1738342594829669,
0.8637803590285111,
0.7263712214471345,
0.8218543046357616,
0.5896830748482805,
0.8355420090113967,
0.5590631364562118,
0.2967533543150571,
0.6754057428214731,
0.3642314189189189,
0.7676632455748922,
0.7089129314786193,
0.6231042271700549,
0.6445086705202312,
0.7071129707112971,
0.4434430752253081,
0.4512901527119536,
0.5718423372371237,
0.4422496570644718,
0.7969543147208122,
0.4561806352851129,
0.7925653969710876,
0.8535322777101096,
0.2469677419354838,
0.7006305531670967,
0.3402537485582468,
0.5767607919506654,
0.7044633368756642
],
"coloraxis": "coloraxis",
"pattern": {
"shape": ""
}
},
"name": "",
"offsetgroup": "",
"orientation": "h",
"showlegend": false,
"textposition": "auto",
"type": "bar",
"x": [
0.9984646878198566,
0.9971852610030706,
0.9925793244626409,
0.9888689866939612,
0.987589559877175,
0.9832395087001023,
0.9823439099283522,
0.981064483111566,
0.9779938587512794,
0.9749232343909928,
0.9746673490276356,
0.9744114636642784,
0.9741555783009213,
0.9740276356192428,
0.973899692937564,
0.9728761514841352,
0.9695496417604912,
0.9682702149437052,
0.9646878198567042,
0.9645598771750256,
0.9631525076765608,
0.9616171954964176,
0.961489252814739,
0.9577789150460594,
0.955603889457523,
0.9553480040941658,
0.95496417604913,
0.9547082906857728,
0.9545803480040942,
0.9540685772773798,
0.9530450358239508,
0.948439099283521,
0.947799385875128,
0.9472876151484136,
0.9470317297850565,
0.9470317297850562,
0.9467758444216992,
0.946136131013306,
0.9457523029682704,
0.9456243602865916
],
"xaxis": "x",
"y": [
"openfoodnetwork",
"E3SM",
"EnergyPlus",
"Global Forest Watch",
"navitia",
"ApsimX",
"PEcAn",
"InaSAFE",
"Growstuff",
"SCREAM",
"OpenMDAO",
"HydroShare",
"CoopCycle",
"Iris",
"OpenStudio",
"BEAM",
"VOLTTRON",
"ESMValTool",
"Electricity Maps",
"iNaturalist",
"netcdf-c",
"Modelica Buildings library",
"SEED",
"gwells",
"Oceananigans.jl",
"WRF",
"origin",
"Streetmix",
"Karrot",
"PyBaMM",
"MetPy",
"OperatorFabric",
"Digital Public Goods",
"Emoncms",
"Open Smart Grid Platform",
"Farmbot",
"ETM Pro",
"OpenEMS",
"Resource Watch",
"City Energy Analyst"
],
"yaxis": "y"
}
],
"layout": {
"barmode": "relative",
"coloraxis": {
"colorbar": {
"orientation": "h",
"title": {
"text": "DDS"
},
"x": 0.4,
"y": -0.15
},
"colorscale": [
[
0,
"rgb(237, 239, 93)"
],
[
0.16666666666666666,
"rgb(169, 220, 103)"
],
[
0.3333333333333333,
"rgb(110, 197, 116)"
],
[
0.5,
"rgb(57, 171, 126)"
],
[
0.6666666666666666,
"rgb(13, 143, 129)"
],
[
0.8333333333333334,
"rgb(15, 114, 121)"
],
[
1,
"rgb(36, 86, 104)"
]
]
},
"dragmode": false,
"height": 1000,
"hoverlabel": {
"bgcolor": "white"
},
"images": [
{
"sizex": 0.05,
"sizey": 0.05,
"source": "data:image/png;base64,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",
"x": 1,
"xanchor": "right",
"xref": "paper",
"y": 0,
"yanchor": "bottom",
"yref": "paper"
}
],
"legend": {
"tracegroupgap": 0
},
"margin": {
"b": 0,
"l": 30,
"r": 0,
"t": 40
},
"showlegend": false,
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#040404",
"family": "Open Sans",
"size": 15
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"margin": {
"b": 0
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"font": {
"color": "#040404",
"family": "Open Sans"
},
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
},
"title": {
"text": "Top 40 size score"
},
"xaxis": {
"anchor": "y",
"domain": [
0,
1
],
"range": [
0.93,
1
],
"title": {
"text": "Size score"
}
},
"yaxis": {
"anchor": "x",
"autorange": "reversed",
"domain": [
0,
1
],
"title": {}
}
}
}
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_size_score = df_active.nlargest(40, \"size\")\n",
"\n",
"fig = px.bar(\n",
" df_size_score,\n",
" x=df_size_score[\"size\"],\n",
" y=df_size_score[\"project_name\"],\n",
" orientation=\"h\",\n",
" range_x=(0.93, 1),\n",
" custom_data=[\"oneliner\", \"topic\", \"git_url\"],\n",
" color=df_size_score[\"development_distribution_score\"],\n",
" color_continuous_scale=color_continuous_scale,\n",
")\n",
"\n",
"fig.update_layout(\n",
" height=1000, # Added parameter\n",
" #width=600,\n",
" xaxis_title=\"Size score\",\n",
" yaxis_title=None,\n",
" title=\"Top 40 size score\",\n",
" coloraxis_colorbar=dict(\n",
" title='DDS',\n",
" orientation='h',\n",
" y=-0.15,\n",
" x=0.4\n",
" ),\n",
" dragmode=False,\n",
" hoverlabel=dict(bgcolor=\"white\"),\n",
")\n",
"fig.update(layout_showlegend=False)\n",
"fig.add_layout_image(\n",
" dict(\n",
" source=logo_img,\n",
" xref=\"paper\",\n",
" yref=\"paper\",\n",
" x=1,\n",
" y=0,\n",
" sizex=0.05,\n",
" sizey=0.05,\n",
" xanchor=\"right\",\n",
" yanchor=\"bottom\",\n",
" )\n",
")\n",
"\n",
"fig.update_traces(\n",
" hovertemplate=\"
\".join(\n",
" [\n",
" \"Project Info: %{customdata[0]}\",\n",
" \"Topic: %{customdata[1]}\",\n",
" \"Git URL: %{customdata[2]}\",\n",
" ]\n",
" )\n",
")\n",
"fig[\"layout\"].update(margin=dict(l=30, r=0, b=0, t=40))\n",
"fig[\"layout\"][\"yaxis\"][\"autorange\"] = \"reversed\"\n",
"config = {\n",
" 'toImageButtonOptions': {\n",
" 'format': 'svg', # one of png, svg, jpeg, webp\n",
" },\n",
" 'responsive':'true'\n",
"}\n",
"fig.show(config=config)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"```{figure} data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\n",
":figclass: caption-hack\n",
":name: size-score\n",
"\n",
"\\- The 40 Projects with the highest size score\n",
"```"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Dimensions and Calculations\n",
"\n",
"```python\n",
"# Each project is ranked according to different indicators in the dimensions of community, activity and size. \n",
"# A value of 1 represents the highest rank and 0 the lowest.\n",
"# The individual values are summed up within the dimensions to create the scores for the different dimensions.\n",
"df_active[\"activity\"] = (\n",
" df_active[\"total_commits_last_year\"].rank(pct=True)\n",
" + df_active[\"issues_closed_last_year\"].rank(pct=True)\n",
" + df_active[\"days_until_last_issue_closed\"].rank(pct=True)\n",
" + df_active[\"last_released_date\"].rank(pct=True, na_option=\"top\")\n",
") / 4\n",
"\n",
"df_active[\"community\"] = (\n",
" df_active[\"contributors\"].rank(pct=True)\n",
" + df_active[\"development_distribution_score\"].rank(pct=True)\n",
" + df_active[\"reviews_per_pr\"].rank(pct=True)\n",
") / 3\n",
"\n",
"df_active[\"size\"] = (\n",
" df_active[\"total_number_of_commits\"].rank(pct=True)\n",
" + df_active[\"contributors\"].rank(pct=True)\n",
" + df_active[\"closed_issues\"].rank(pct=True)\n",
" + df_active[\"closed_pullrequests\"].rank(pct=True)\n",
") / 4\n",
"\n",
"# The scores are summed up and normalised so that 1 represents the largest total score. \n",
"df_active[\"total_score\"] = (\n",
" df_active[\"activity\"] / df_active[\"activity\"].max()\n",
" + df_active[\"community\"] / df_active[\"community\"].max()\n",
" + df_active[\"size\"] / df_active[\"size\"].max()\n",
") / 3\n",
"```"
]
}
],
"metadata": {
"celltoolbar": "Tags",
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10 (default, Nov 14 2022, 12:59:47) \n[GCC 9.4.0]"
},
"tags": "full-width",
"vscode": {
"interpreter": {
"hash": "e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a"
}
}
},
"nbformat": 4,
"nbformat_minor": 4
}