refactor+fix: tools update

* packages and dashboards now link to tools overview
* consistent capitalization of epiprocess/epipredict
* aggregate all the tooling subpages into a single .md file for simplicity and to fix the header links
* remove unused shortcode

config.toml

@@ -127,6 +127,7 @@ relativeURLs = false
     parent = "tools"
     identifier = "Packages"
     name = "Packages"
+    url = "https://delphi.cmu.edu/tools/"
     weight = 6
 [[menu.main]]
     parent = "Packages"
@@ -140,19 +141,20 @@ relativeURLs = false
     weight = 20
 [[menu.main]]
     parent = "Packages"
-    name = "EpiProcess"
+    name = "Epiprocess"
     url = "https://cmu-delphi.github.io/epiprocess/"
     weight = 7
 [[menu.main]]
     parent = "Packages"
-    name = "EpiPredict"
+    name = "Epipredict"
     url = "https://cmu-delphi.github.io/epipredict/"
     weight = 7
 # utils
 [[menu.main]]
     parent = "tools"
     identifier = "utils"
     name = "Dashboards"
+    url = "https://delphi.cmu.edu/tools/"
     weight = 9
 [[menu.main]]
     parent = "utils"

content/tools/_index.md

@@ -3,16 +3,87 @@ title: Tools Overview
 linkTitle: Tools
 layout: single
 ---
+
 ## Forecasting
 
-{{<forecasting>}}
+### [COVID Forecasting](https://covid19forecasthub.org/)
+
+We participate in weekly COVID hospital admissions forecasting at the state and national level.
+Our current system for generating forecasts can be found [here](https://github.com/cmu-delphi/covid-hosp-forecast).
+In addition to publishing the individual forecasts from the participating groups, the Reich lab makes an ensemble prediction, and hosts a [visualization of both](https://viz.covid19forecasthub.org).
+We host a comparison tool for [retrospective analysis of the forecasters](https://delphi.cmu.edu/forecast-eval/).
+
+### [Flu Forecasting (FluSight)](https://www.cdc.gov/flu/weekly/flusight/index.html)
+
+We participate in the weekly Flu forecasting hub run by the CDC during the flu season. Our current system for generating forecasts can be found [here](https://github.com/cmu-delphi/flu-hosp-forecast/).
+From these dozens of individual forecasts by various groups, the CDC publishes a weekly [ensemble prediction](https://www.cdc.gov/flu/weekly/flusight/flu-forecasts.htm).
 
 ## Packages
 
 All source code is freely available on [GitHub](https://github.com/cmu-delphi/).
 
-{{<tools>}}
+### [Epidatr](https://cmu-delphi.github.io/epidatr/)
+
+R client for our [Epidata API](https://cmu-delphi.github.io/delphi-epidata/). It allows you to cache queries locally to speed up data access and seamlessly integrate pulling from our API into your pipelines.
+
+### [Delphi Tooling Book](https://cmu-delphi.github.io/delphi-tooling-book/)
+
+An introduction to epidemiological forecasting using our tools: epiprocess and epipredict.
+
+### [Epiprocess](https://cmu-delphi.github.io/epiprocess/)
+
+A collection of data structures and methods for handling epidemiological data measured over space, time, and other potential keys like age or ethnicity.
+The major methods are:
+- Sliding functions, both for generic user-supplied function and optimized commonly used functions (e.g. rolling mean and sum). These build on tools like [slider](https://slider.r-lib.org/) by
+  - handling gaps in time
+  - automatically handling grouping of keys
+  - being version aware; this enables version-aware forecast evaluation, so that you can compare forecasters using only data that would have available at the time of forecast.
+- Growth rate estimation, as estimated using relative rates of change, linear regression, smooth splines, or polynomial trend filtering.
+- Outlier detection and correction, using rolling median or LOESS trend decomposition.
+- Signal correlation over space, time and other keys. It also supports lagged correlations, automatically handles grouping by the specified keys, and handles time gaps.
+
+Epiprocess also has methods for growth rate estimation,
+
+R client for our [Epidata API](https://cmu-delphi.github.io/delphi-epidata/). It allows you to cache queries locally to speed up data access and seamlessly integrate pulling from our API into your pipelines.
+
+### [Epipredict](https://cmu-delphi.github.io/epipredict/)
+
+A collection of data structures and methods for handling epidemiological data measured over space, time, and other potential keys like age or ethnicity.
+The major methods are:
+- Sliding functions, both for generic user-supplied function and optimized commonly used functions (e.g. rolling mean and sum). These build on tools like [slider](https://slider.r-lib.org/) by
+  - handling gaps in time
+  - automatically handling grouping of keys
+  - being version aware; this enables version-aware forecast evaluation, so that you can compare forecasters using only data that would have available at the time of forecast.
+- Growth rate estimation, as estimated using relative rates of change, linear regression, smooth splines, or polynomial trend filtering.
+- Outlier detection and correction, using rolling median or LOESS trend decomposition.
+- Signal correlation over space, time and other keys. It also supports lagged correlations, automatically handles grouping by the specified keys, and handles time gaps.
+
+Epiprocess also has methods for growth rate estimation,
+
+R client for our [Epidata API](https://cmu-delphi.github.io/delphi-epidata/). It allows you to cache queries locally to speed up data access and seamlessly integrate pulling from our API into your pipelines.
+
+### [Epidatpy](https://github.com/cmu-delphi/epidatpy) (WIP)
+
+A work in progress Python client for our [Epidata API](https://cmu-delphi.github.io/delphi-epidata/). Not yet ready for production, but let us know if you are interested, so we can prioritize it!
 
 ## Operational Systems
 
-{{<systems>}}
+### [EpiData](https://github.com/cmu-delphi/delphi-epidata)
+
+API for getting up-to-date epidemiological data (also available via a web interface through [EpiVis](https://delphi.cmu.edu/epivis/epivis.html))
+
+### [Indicator Status](https://delphi.cmu.edu/covidcast/indicator-status/)
+
+A dashboard for displaying the lags for various signals in the delphi epidata API.
+
+### [Dashboard Builder](https://delphi.cmu.edu/covidcast/dashboard)
+
+A builder that allows you to customize the [Delphi Epidata Dashboard](/covidcast/).
+
+### [COVID Forecasting Evaluation](https://delphi.cmu.edu/forecast-eval/)
+
+A forecast evaluation dashboard to compare the historical performance of the forecasts submitted to the [COVID-19 Forecast Hub](https://covid19forecasthub.org/), a collaboration between various modeling teams to produce forecasts of daily hospital admissions.
+
+### [EpiVis](https://delphi.cmu.edu/epivis/)
+
+Epidemiological time series visualizer.

content/tools/archive.md

@@ -3,7 +3,6 @@ title: Archived Tools
 layout: single
 ---
 
-
 ### [COVIDcast 1.0 ("Classic")](/covidcast/classic)
 
 A map-first single-page webapp for visualizing COVID-19 pandemic indicators.