Yegberink/module_geothermal

None

Overview

Latest release: None, Last update: 2026-07-17

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=Yegberink/module_geothermal

Quality control: linting: failed formatting: failed

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Conda package manager. It is recommended to install conda via Miniforge. Run

conda create -c conda-forge -c bioconda -c nodefaults --name snakemake snakemake snakedeploy

to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via

conda activate snakemake

For other installation methods, refer to the Snakemake and Snakedeploy documentation.

Step 2: Deploy workflow

With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:

mkdir -p path/to/project-workdir
cd path/to/project-workdir

In all following steps, we will assume that you are inside of that directory. Then run

snakedeploy deploy-workflow https://github.com/Yegberink/module_geothermal . --tag None

Snakedeploy will create two folders, workflow and config. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.

Step 3: Configure workflow

To configure the workflow, adapt config/config.yml to your needs following the instructions below.

Step 4: Run workflow

The deployment method is controlled using the --software-deployment-method (short --sdm) argument.

To run the workflow with automatic deployment of all required software via conda/mamba, use

snakemake --cores all --sdm conda

Snakemake will automatically detect the main Snakefile in the workflow subfolder and execute the workflow module that has been defined by the deployment in step 2.

For further options such as cluster and cloud execution, see the docs.

Step 5: Generate report

After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using

snakemake --report report.zip

Configuration

The following section is imported from the workflow’s config/README.md.

Configuration

This workflow is part of the clio project. Please consult our documentation for more details. Other useful resources are:

  • INTERFACE.yaml: user input files (placed in resources/user) and module output files (placed in results).

  • workflow/internal/config.schema.yaml: general configuration options.

  • tests/integration/: a simple example of how to use this module.

Linting and formatting

Linting results
  1Using workflow specific profile workflow/profiles/default for setting default command line arguments.
  2Lints for snakefile /tmp/tmplb1_vkgj/workflow/rules/automatic.smk:
  3    * Mixed rules and functions in same snakefile.:
  4      Small one-liner functions used only once should be defined as lambda
  5      expressions. Other functions should be collected in a common module, e.g.
  6      'rules/common.smk'. This makes the workflow steps more readable.
  7      Also see:
  8      https://snakemake.readthedocs.io/en/latest/snakefiles/modularization.html#includes
  9
 10Lints for rule build_scenario_table (line 284, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
 11    * No log directive defined:
 12      Without a log directive, all output will be printed to the terminal. In
 13      distributed environments, this means that errors are harder to discover.
 14      In local environments, output of concurrent jobs will be mixed and become
 15      unreadable.
 16      Also see:
 17      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
 18    * Specify a conda environment or container for each rule.:
 19      This way, the used software for each specific step is documented, and the
 20      workflow can be executed on any machine without prerequisites.
 21      Also see:
 22      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
 23      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
 24
 25Lints for rule build_temperature_voxel (line 297, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
 26    * No log directive defined:
 27      Without a log directive, all output will be printed to the terminal. In
 28      distributed environments, this means that errors are harder to discover.
 29      In local environments, output of concurrent jobs will be mixed and become
 30      unreadable.
 31      Also see:
 32      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
 33    * Specify a conda environment or container for each rule.:
 34      This way, the used software for each specific step is documented, and the
 35      workflow can be executed on any machine without prerequisites.
 36      Also see:
 37      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
 38      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
 39
 40Lints for rule crop_to_speed_up (line 309, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
 41    * No log directive defined:
 42      Without a log directive, all output will be printed to the terminal. In
 43      distributed environments, this means that errors are harder to discover.
 44      In local environments, output of concurrent jobs will be mixed and become
 45      unreadable.
 46      Also see:
 47      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
 48    * Specify a conda environment or container for each rule.:
 49      This way, the used software for each specific step is documented, and the
 50      workflow can be executed on any machine without prerequisites.
 51      Also see:
 52      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
 53      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
 54
 55Lints for rule calculate_LCOE (line 322, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
 56    * No log directive defined:
 57      Without a log directive, all output will be printed to the terminal. In
 58      distributed environments, this means that errors are harder to discover.
 59      In local environments, output of concurrent jobs will be mixed and become
 60      unreadable.
 61      Also see:
 62      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
 63    * Specify a conda environment or container for each rule.:
 64      This way, the used software for each specific step is documented, and the
 65      workflow can be executed on any machine without prerequisites.
 66      Also see:
 67      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
 68      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
 69
 70Lints for rule make_2d_base (line 363, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
 71    * No log directive defined:
 72      Without a log directive, all output will be printed to the terminal. In
 73      distributed environments, this means that errors are harder to discover.
 74      In local environments, output of concurrent jobs will be mixed and become
 75      unreadable.
 76      Also see:
 77      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
 78    * Specify a conda environment or container for each rule.:
 79      This way, the used software for each specific step is documented, and the
 80      workflow can be executed on any machine without prerequisites.
 81      Also see:
 82      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
 83      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
 84
 85Lints for rule make_2d_scenario (line 421, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
 86    * No log directive defined:
 87      Without a log directive, all output will be printed to the terminal. In
 88      distributed environments, this means that errors are harder to discover.
 89      In local environments, output of concurrent jobs will be mixed and become
 90      unreadable.
 91      Also see:
 92      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
 93    * Specify a conda environment or container for each rule.:
 94      This way, the used software for each specific step is documented, and the
 95      workflow can be executed on any machine without prerequisites.
 96      Also see:
 97      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
 98      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
 99
100Lints for rule aggregate_to_regions (line 461, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
101    * No log directive defined:
102      Without a log directive, all output will be printed to the terminal. In
103      distributed environments, this means that errors are harder to discover.
104      In local environments, output of concurrent jobs will be mixed and become
105      unreadable.
106      Also see:
107      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
108    * Specify a conda environment or container for each rule.:
109      This way, the used software for each specific step is documented, and the
110      workflow can be executed on any machine without prerequisites.
111      Also see:
112      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
113      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
114
115Lints for rule scenario_summary_fig (line 482, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
116    * No log directive defined:
117      Without a log directive, all output will be printed to the terminal. In
118      distributed environments, this means that errors are harder to discover.
119      In local environments, output of concurrent jobs will be mixed and become
120      unreadable.
121      Also see:
122      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
123    * Specify a conda environment or container for each rule.:
124      This way, the used software for each specific step is documented, and the
125      workflow can be executed on any machine without prerequisites.
126      Also see:
127      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
128      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
129
130Lints for rule sensitivity_boxplot_per_scenario (line 511, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
131    * No log directive defined:
132      Without a log directive, all output will be printed to the terminal. In
133      distributed environments, this means that errors are harder to discover.
134      In local environments, output of concurrent jobs will be mixed and become
135      unreadable.
136      Also see:
137      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
138    * Specify a conda environment or container for each rule.:
139      This way, the used software for each specific step is documented, and the
140      workflow can be executed on any machine without prerequisites.
141      Also see:
142      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
143      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
144
145Lints for rule sensitivity_vis (line 523, /tmp/tmplb1_vkgj/workflow/rules/automatic.smk):
146    * No log directive defined:
147      Without a log directive, all output will be printed to the terminal. In
148      distributed environments, this means that errors are harder to discover.
149      In local environments, output of concurrent jobs will be mixed and become
150      unreadable.
151      Also see:
152      https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#log-files
153    * Specify a conda environment or container for each rule.:
154      This way, the used software for each specific step is documented, and the
155      workflow can be executed on any machine without prerequisites.
156      Also see:
157      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#integrated-package-management
158      https://snakemake.readthedocs.io/en/latest/snakefiles/deployment.html#running-jobs-in-containers
Formatting results
1[DEBUG] 
2[DEBUG] 
3[DEBUG] In file "/tmp/tmplb1_vkgj/workflow/rules/automatic.smk":  Formatted content is different from original
4[DEBUG] 
5[DEBUG] In file "/tmp/tmplb1_vkgj/workflow/Snakefile":  Formatted content is different from original
6[INFO] 2 file(s) would be changed 😬
7[INFO] 1 file(s) would be left unchanged 🎉
8
9snakefmt version: 0.11.5