system_cpu_core_count

Function to return the system's number of CPU cores.

An integrated set of tools to allow data users to conduct
meteorological normalisation and counterfactual modelling for air quality
data. The meteorological normalisation technique uses predictive random
forest models to remove variation of pollutant concentrations so trends and
interventions can be explored in a robust way. For examples, see
Grange et al. (2018) <doi:10.5194/acp-18-6223-2018> and
Grange and Carslaw (2019) <doi:10.1016/j.scitotenv.2018.10.344>. The random
forest models can also be used for counterfactual or business as usual (BAU)
modelling by using the models to predict, from the model's perspective, the
future. For an example, see Grange et al. (2021) <doi:10.5194/acp-2020-1171>.

Stuart K. Grange

rmweather

Tools to Conduct Meteorological Normalisation and Counterfactual
Modelling for Air Quality Data

system_cpu_core_count function

<dl><dt>logical_cores</dt>
<dd>Should logical cores be included in the core count?</dd>
<dt>max_cores</dt>
<dd>Should the return have a maximum value? This can be useful 
when there are very many cores and logic is being built.</dd></dl>

Arguments

Author

Function to return the system's number of CPU cores. — system_cpu_core_count

<dl>

<dt>logical_cores</dt>
<dd>Should logical cores be included in the core count?</dd>


<dt>max_cores</dt>
<dd>Should the return have a maximum value? This can be useful 
when there are very many cores and logic is being built.</dd>

</dl>

system_cpu_core_count: Function to return the system's number of CPU cores.

Description

Usage

Arguments

Author