| Name | tilupy JSON |
| Version |
1.0.0
JSON |
| download |
| home_page | |
| Summary | Thin-layer models unified processing tool |
| upload_time | 2024-02-01 13:49:36 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
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| keywords |
thin-layer
shallow-water
display
simulation
model
processing
benchmark
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
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|
# tilupy
- [Description](#description)
- [Installation](#installation)
- [Quick start](#quick-start)
- [Prepare simulations](#prepare-simus)
- [Get simulation results](#simu-results)
- [Process simulation results in python script](#process-simus-python)
- [Process simulation results in command line](#process-simus-cmd)
- [Models references](#models-refs)
- [Shaltop](#ref-shaltop)
- [r.avaflow](#ref-ravaflow)
## Description <a name="description"></a>
`tilupy` (ThIn-Layer Unified Processing in pYthon) package is meant as a top-level tool for processing inputs and outputs of thin-layer geophysical
flow simulations on general topographies.
It contains one submodule per thin-layer model for writing and reading raw inputs and outputs of the model.
Outputs are then easily compared between different simulations / models. The models themselves are not part of this package and must
be installed separately.
Note that `tilupy` is still under development, thus only minimal documentation is available at the moment, and testing is underway.
Contributions are feedback are most welcome. Reading and writing is available for the `SHALTOP` model (most commonly used by the author) and `r.avaflow`
(only partly maintained).
## Installation <a name="installation"></a>
To install `tilupy` from GitHub or PyPi, you'll need to have `pip` installed on your computer. `tilupy`is not yet available on `conda-forge`.
It is strongly recommended to install `tilupy` in a virtual environnement dedicated to this package. This can be done with `virtualenv`
(see the documentation e.g. [here](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/)).
Create the environnement with :
```bash
python -m venv /path/to/myenv
```
and activate it, on Linux:
```bash
source /path/to/myenv/bin/activate
```
and on Windows:
```cmd.exe
\path\to\myenv\Scripts\activate
```
Alternatively, if you are more used to Anaconda :
```bash
conda create -n tilupy pip
conda activate tilupy
```
or equivalently with Mamba :
```bash
mamba create -n tilupy pip
mamba activate tilupy
```
Before installing with `pip`, make sure `pip`, `steuptools` and `wheel` are up to date
```
python -m pip install --upgrade pip setuptools wheel
```
### Latest stable realease from PyPi <a name="pypi-install"></a>
```
python -m pip install tilupy
```
### Development version on from GitHub <a name="source-install"></a>
Download the GithHub repository [here](https://github.com/marcperuz/tilupy), or clone it with
```
git clone https://github.com/marcperuz/tilupy.git
```
Open a terminal in the created folder and type:
```
python -m pip install .
```
## Quick start <a name="quick-start"></a>
We give here a simple example to prepare simulations for SHALTOP, and process the results. The corresponding scripts can be found in `examples/frankslide`
### Prepare simulations <a name="prepare-simus"></a>
Import the different required modules :
```python
import os
# Read an write rasters
import tilupy.raster
# Functions to download examples of elevation and initial mass rasters
import tilupy.download_data
#Submodule used to prepare Shaltop simulations
import tilupy.models.shaltop.initsimus as shinit
```
Define the folder where input data will be downloaded and simulations carried out :
```python
FOLDER_BASE = '/path/to/myfolder'
```
Import data from GitHub, and create subfolder for simulation results
```python
folder_data = os.path.join(FOLDER_BASE, 'rasters')
os.makedirs(folder_data, exist_ok=True)
#raster_topo and raster_mass are the paths to the topography and initial mass rasters
raster_topo = tilupy.download_data.import_frankslide_dem(folder_out=folder_data)
raster_mass = tilupy.download_data.import_frankslide_pile(folder_out=folder_data)
# Create folder for shaltop simulations
folder_simus = os.path.join(FOLDER_BASE, 'shaltop')
os.makedirs(folder_simus, exist_ok=True)
```
Convert downloaded rasters to Shaltop input file type, and store the properties of the resulting grid
```python
shinit.raster_to_shaltop_txtfile(raster_topo,
os.path.join(folder_simus, 'topography.d'))
axes_props = shinit.raster_to_shaltop_txtfile(raster_mass,
os.path.join(folder_simus, 'init_mass.d'))
```
Initiate simulations parameters. See the SHALTOP documentation for details.
```python
params = dict(nx=axes_props['nx'], ny=axes_props['ny'],
per=axes_props['nx']*axes_props['dx'],
pery=axes_props['ny']*axes_props['dy'],
tmax=100, # Simulation maximum time in seconds (not comutation time)
dt_im=10, # Time interval (s) between snapshots recordings
file_z_init = 'topography.d', # Name of topography input file
file_m_init = 'init_mass.d',# name of init mass input file
initz=0, # Topography is read from file
ipr=0, # Initial mass is read from file
hinit_vert=1, # Initial is given as vertical thicknesses and
# must be converted to thicknesses normal to topography
eps0=1e-13, #Minimum value for thicknesses and velocities
icomp=1, # choice of rheology (Coulomb with constant basal friction)
x0=1000, # Min x value (used for plots after simulation is over)
y0=2000) # Min y value (used for plots after simulation is over)
```
Finally, prepare simulations for a set of given rheological parameters (here, three basal friction coefficients)
```python
deltas = [15, 20, 25]
for delta in deltas:
params_txt = 'delta_{:05.2f}'.format(delta).replace('.', 'p')
params['folder_output'] = params_txt # Specify folder where outputs are stored
params['delta1'] = delta # Specify the friction coefficient
#Write parameter file
shinit.write_params_file(params, directory=folder_simus,
file_name=params_txt + '.txt')
#Create folder for results (not done by shlatop!)
os.makedirs(os.path.join(folder_simus, params_txt), exist_ok=True)
```
You must then run the simulations (see Shaltop documentation)
### Get simulation results <a name="simu-results"></a>
Simulation results are read from a `Results` class. Main functions are defined in the parent class `tilupy.read.Results`, and each model has its own inheretied class `tilupy.models.[model_name].read.Results`. A class instance for a given model can be initiated with
```python
res = tilupy.read.get_results([model_name], **kwargs)
```
where `kwargs must be adapted to the considered model. For instance with Shaltop and the example above, the results of the simulation with a friction angle of 25 must be initiated as :
```python
res = tilupy.read.get_results('shaltop', folder_base=folder_simus, file_params='delta_25p00.txt)
```
The topography and axes can then directly be read from `res` :
```python
x, y, z = res.x, res.y, res.z
import matplotlib.pyplot as plt
plt.imshow(z)
```
`z[i, j]` is the altitude at `flip(y[i])` and `x[j]`. Thus `z[0, 0]` corresponds to the North-West corner of the topography.
Specific simulation outputs can be extracted with
```python
h_res = res.get_output(res_name)
```
where `res_name` must chosen among
- `h` : Flow thickness in the direction perpendicular to the topography
- `hvert` : Flow thickness in the vertical direction
- `ux` and `uy` : Flow velocity in the X and Y direction (check whether it is in the cartesian reference frame or not)
- `u` : Norm of the flow velocity
- `hu` : Momentum (thickness * flow velocity)
- `hu2` : Kinetic energy (thickness * square flow velocity)
It is also possible to extract 2D spatial static characteritics of the flow by using any of the previous states with `_[operation]`, where
`[operation]` is chosen among, `max`, `mean`, `std`, `sum`, `min`, `final`, `initial`. For instance `h_max` is a 2D array with the
maximum simulated thickness at each point of the grid. `h_final` is the simulated thickness at the end of the simulation.
`tilupy` will load these characteristics directly from the simulation output when possible (e.g. Shaltop records a maximum thickness array),
or compute then from the available data. For instance, if the simulation results contains a file whith the maximum thickness, `h_max` will be
read from this file. Otherwise, `h_max` is computed from the simulation recorded temporal snapshots (which is supposedly less precise).
For instance, to load the recorded thicknesses in the current example :
```python
res_name = 'h'
h_res = res.get_output(res_name) # Thicknesses recorded at different times
# h_res.d is a 3D numpy array of dimension (len(x) x len(y) x len(h_res.t))
plt.imshow(h_res.d[:, :, -1]) # Plot final thickness.
t = h_res.t # Get times of simulation outputs.
```
And to load the maximum thickness array :
```python
res_name = 'h_max'
h_max_res = res.get_output(res_name) #h_max_res is read directly from simulation
# results when possible, and is deduced from res.get_output('h') otherwise
# h_max_res.d is a 2D numpy array of dimension (len(x) x len(y))
plt.imshow(h_max_res.d)
```
### Process simulation results in python script <a name="process-simus-python"></a>
`tilupy`can be used to plot the results as images, where the flow state (thickness, velocity, ...)
is shown with a colorscale on the underlying topography. Plots can be thouroughly customized (documentation not available yet).
For instance, the following code plots the flow thickness at each recorded time step, with a constant colorscale vraying from 0.1 to
100 m. The topography is represented as a shaded relief with thin contour lines every 10 m, and bold contour_lines every 100 m. Plots are saved
in a folder created in `folder_out`, but not displayed in the terminal (if you work in a developping environnement such as `spyder`).
```python
topo_kwargs = dict(contour_step=10, step_contour_bold=100) # give interval between thin and bold contour lines
params_files = 'delta_*.txt'
tilupy.cmd.plot_results('shaltop', 'h', params_files, folder_simus,
save=True, display_plot=False, figsize=(15/2.54, 15/2.54),
vmin=0.1, vmax=100, fmt='png',
topo_kwargs=topo_kwargs)
```
The following code acts similarly, but plots the maximum thickness instead, and used a segmented colormap given by `cmap_intervals`.
```python
tilupy.cmd.plot_results('shaltop', 'h_max', params_files, folder_simus,
save=True, display_plot=False, figsize=(15/2.54, 15/2.54),
cmap_intervals=[0.1, 5, 10, 25, 50, 100],
topo_kwargs=topo_kwargs)
```
It is also possible to save outputs back to rasters. The following code save all recorded thicknesses snapshots as tif files in a new folder
created in `folder_out`.
```python
tilupy.cmd.to_raster('shaltop', 'h_max', params_files,
folder_simus, fmt='tif')
```
### Process simulation results in command line <a name="process-simus-cmd"></a>
`tilupy` comes with command line scripts to allow for quick processing of results. They work similarly as the functions `tilupy.cmd.plot_results` and `tilupy.cmd.to_raster`,
although there are less options.
`tilupy_plot` will automatically plot and save results in a new folder `plot` located in the simulation output folder specified in the parameter file :
```
tilupy_plot [-h] [-n RES_NAME] [-p PARAM_FILES] [-f FOLDER] [--fmt FMT] [--vmin VMIN] [--vmax VMAX]
[--minval_abs MINVAL_ABS]
model
```
`RES_NAME` can be any of the strings listed in the previous section. For instance, to plot all thicknesses snaphsots from shaltop simulations in the current folder, type `tilupy_plot shaltop -n h`. If parameters files are located in `another/folder`, type, `tilupy shaltop -n h -f another/folder`. Similarly, to save thicknesses snapshots as ascii rasters, use `tilupy_to_raster shaltop -n h --fmt asc`.
```
tilupy_to_raster [-h] [-n RES_NAME] [-p PARAM_FILES] [-f FOLDER] [--fmt {tif,tiff,txt,asc,ascii}] model
```
With both commands you can use the `-h` option do print help.
## Models references <a name="models-refs"></a>
We provide here a basic descriptions of models compatible with `tilupy`. The list of references is not exhaustive.
### Shaltop <a name="ref-shaltop"></a>
`shaltop` models gravitational flow models over general topographies with small slope variation (small curvature) and friction. The equations are expressed in a horizontal/vertical reference frame and the shallow approximation is imposed in the direction normal to the slope. `shaltop` is not yet freely available. If you are interested, contact [m.peruzzetto@brgm.fr](mailto:m.peruzzetto@brgm.fr) or [mangeney@ipgp.fr](mailto:mangeney@ipgp.fr).
- Bouchut, F., Mangeney-Castelnau, A., Perthame, B., Vilotte, J.-P., 2003. A new model of Saint Venant and Savage–Hutter type for gravity driven shallow water flows. Comptes Rendus Mathématique 336, 531–536. [https://doi.org/10.1016/S1631-073X(03)00117-1](https://doi.org/10.1016/S1631-073X(03)00117-1)
- Bouchut, F., Westdickenberg, M., 2004. Gravity driven shallow water models for arbitrary topography. Communications in Mathematical Sciences 2, 359–389. [https://doi.org/10.4310/CMS.2004.v2.n3.a2](https://doi.org/10.4310/CMS.2004.v2.n3.a2)
- Mangeney-Castelnau, A., Bouchut, F., Vilotte, J.P., Lajeunesse, E., Aubertin, A., Pirulli, M., 2005. On the use of Saint Venant equations to simulate the spreading of a granular mass: numerical simulation of granular spreading. Journal of Geophysical Research: Solid Earth 110, B09103. [https://doi.org/10.1029/2004JB003161](https://doi.org/10.1029/2004JB003161)
- Mangeney, A., Bouchut, F., Thomas, N., Vilotte, J.P., Bristeau, M.O., 2007. Numerical modeling of self-channeling granular flows and of their levee-channel deposits. Journal of Geophysical Research 112, F02017. [https://doi.org/10.1029/2006JF000469](https://doi.org/10.1029/2006JF000469)
### r.avaflow <a name="ref-ravaflow"></a>
`r.avaflow represents` a GIS-supported open source software tool for the simulation of complex, cascading mass flows over arbitrary topography. It can be downloaded, along with the associated documentation, on the officiel [website](https://www.landslidemodels.org/r.avaflow/). Note that the integration of `r.avaflow` in `tilupy` is partial and potentially not adapted to new releases of `r.avaflow`.
- Mergili, M., Fischer, J.-T., Krenn, J., Pudasaini, S.P., 2017. r.avaflow v1, an advanced open source computational framework for the propagation and interaction of two-phase mass flows. Geoscientific Model Development Discussions 10, 553–569. [https://doi.org/10.5194/gmd-10-553-2017](https://doi.org/10.5194/gmd-10-553-2017)
- Pudasaini, S.P., Mergili, M., 2019. A Multi-Phase Mass Flow Model. Journal of Geophysical Research: Earth Surface 124, 2920–2942. [https://doi.org/10.1029/2019JF005204](https://doi.org/10.1029/2019JF005204)
Raw data
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"author_email": "Marc Peruzzetto <m.peruzzetto@brgm.fr>",
"download_url": "https://files.pythonhosted.org/packages/da/ed/120cf578710e936de641700a93b69a0019b62d6e3f9bc5b66a2a12f56296/tilupy-1.0.0.tar.gz",
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"description": "# tilupy\n\n- [Description](#description)\n- [Installation](#installation)\n- [Quick start](#quick-start)\n - [Prepare simulations](#prepare-simus)\n - [Get simulation results](#simu-results)\n - [Process simulation results in python script](#process-simus-python)\n - [Process simulation results in command line](#process-simus-cmd)\n- [Models references](#models-refs)\n - [Shaltop](#ref-shaltop)\n - [r.avaflow](#ref-ravaflow) \n \n\n## Description <a name=\"description\"></a>\n\n`tilupy` (ThIn-Layer Unified Processing in pYthon) package is meant as a top-level tool for processing inputs and outputs of thin-layer geophysical\nflow simulations on general topographies.\nIt contains one submodule per thin-layer model for writing and reading raw inputs and outputs of the model. \nOutputs are then easily compared between different simulations / models. The models themselves are not part of this package and must\nbe installed separately.\n\nNote that `tilupy` is still under development, thus only minimal documentation is available at the moment, and testing is underway.\nContributions are feedback are most welcome. Reading and writing is available for the `SHALTOP` model (most commonly used by the author) and `r.avaflow`\n(only partly maintained).\n\n## Installation <a name=\"installation\"></a>\n\nTo install `tilupy` from GitHub or PyPi, you'll need to have `pip` installed on your computer. `tilupy`is not yet available on `conda-forge`. \n\nIt is strongly recommended to install `tilupy` in a virtual environnement dedicated to this package. This can be done with `virtualenv`\n(see the documentation e.g. [here](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/)).\nCreate the environnement with :\n\n```bash\npython -m venv /path/to/myenv\n```\n\nand activate it, on Linux:\n\n```bash\nsource /path/to/myenv/bin/activate\n```\n\nand on Windows:\n\n```cmd.exe\n\\path\\to\\myenv\\Scripts\\activate\n```\n\nAlternatively, if you are more used to Anaconda :\n\n```bash\nconda create -n tilupy pip\nconda activate tilupy\n```\n\nor equivalently with Mamba :\n\n```bash\nmamba create -n tilupy pip\nmamba activate tilupy\n```\n\nBefore installing with `pip`, make sure `pip`, `steuptools` and `wheel` are up to date\n\n```\npython -m pip install --upgrade pip setuptools wheel\n```\n\n### Latest stable realease from PyPi <a name=\"pypi-install\"></a>\n\n```\npython -m pip install tilupy\n```\n\n### Development version on from GitHub <a name=\"source-install\"></a>\n\nDownload the GithHub repository [here](https://github.com/marcperuz/tilupy), or clone it with\n\n```\ngit clone https://github.com/marcperuz/tilupy.git\n```\n\nOpen a terminal in the created folder and type:\n\n```\npython -m pip install .\n```\n\n## Quick start <a name=\"quick-start\"></a>\n\nWe give here a simple example to prepare simulations for SHALTOP, and process the results. The corresponding scripts can be found in `examples/frankslide`\n\n### Prepare simulations <a name=\"prepare-simus\"></a>\n\nImport the different required modules :\n\n```python\nimport os\n\n# Read an write rasters\nimport tilupy.raster\n# Functions to download examples of elevation and initial mass rasters\nimport tilupy.download_data\n#Submodule used to prepare Shaltop simulations\nimport tilupy.models.shaltop.initsimus as shinit\n```\n\nDefine the folder where input data will be downloaded and simulations carried out :\n\n```python\nFOLDER_BASE = '/path/to/myfolder'\n```\n\nImport data from GitHub, and create subfolder for simulation results\n\n```python\nfolder_data = os.path.join(FOLDER_BASE, 'rasters')\nos.makedirs(folder_data, exist_ok=True)\n#raster_topo and raster_mass are the paths to the topography and initial mass rasters\nraster_topo = tilupy.download_data.import_frankslide_dem(folder_out=folder_data)\nraster_mass = tilupy.download_data.import_frankslide_pile(folder_out=folder_data)\n# Create folder for shaltop simulations\nfolder_simus = os.path.join(FOLDER_BASE, 'shaltop')\nos.makedirs(folder_simus, exist_ok=True)\n```\n\nConvert downloaded rasters to Shaltop input file type, and store the properties of the resulting grid\n\n```python\nshinit.raster_to_shaltop_txtfile(raster_topo,\n os.path.join(folder_simus, 'topography.d'))\naxes_props = shinit.raster_to_shaltop_txtfile(raster_mass,\n os.path.join(folder_simus, 'init_mass.d'))\n```\n\nInitiate simulations parameters. See the SHALTOP documentation for details.\n\n```python\nparams = dict(nx=axes_props['nx'], ny=axes_props['ny'],\n per=axes_props['nx']*axes_props['dx'],\n pery=axes_props['ny']*axes_props['dy'],\n tmax=100, # Simulation maximum time in seconds (not comutation time)\n dt_im=10, # Time interval (s) between snapshots recordings\n file_z_init = 'topography.d', # Name of topography input file\n file_m_init = 'init_mass.d',# name of init mass input file\n initz=0, # Topography is read from file\n ipr=0, # Initial mass is read from file\n hinit_vert=1, # Initial is given as vertical thicknesses and \n # must be converted to thicknesses normal to topography\n eps0=1e-13, #Minimum value for thicknesses and velocities\n icomp=1, # choice of rheology (Coulomb with constant basal friction)\n x0=1000, # Min x value (used for plots after simulation is over)\n y0=2000) # Min y value (used for plots after simulation is over)\n```\n\nFinally, prepare simulations for a set of given rheological parameters (here, three basal friction coefficients)\n\n```python\ndeltas = [15, 20, 25]\nfor delta in deltas:\n params_txt = 'delta_{:05.2f}'.format(delta).replace('.', 'p')\n params['folder_output'] = params_txt # Specify folder where outputs are stored\n params['delta1'] = delta # Specify the friction coefficient\n #Write parameter file\n shinit.write_params_file(params, directory=folder_simus,\n file_name=params_txt + '.txt')\n #Create folder for results (not done by shlatop!)\n os.makedirs(os.path.join(folder_simus, params_txt), exist_ok=True)\n```\n\nYou must then run the simulations (see Shaltop documentation)\n\n### Get simulation results <a name=\"simu-results\"></a>\n\nSimulation results are read from a `Results` class. Main functions are defined in the parent class `tilupy.read.Results`, and each model has its own inheretied class `tilupy.models.[model_name].read.Results`. A class instance for a given model can be initiated with\n\n```python\nres = tilupy.read.get_results([model_name], **kwargs)\n```\n\nwhere `kwargs must be adapted to the considered model. For instance with Shaltop and the example above, the results of the simulation with a friction angle of 25 must be initiated as :\n\n```python\nres = tilupy.read.get_results('shaltop', folder_base=folder_simus, file_params='delta_25p00.txt)\n```\n\nThe topography and axes can then directly be read from `res` :\n\n```python\nx, y, z = res.x, res.y, res.z\nimport matplotlib.pyplot as plt\nplt.imshow(z)\n```\n\n`z[i, j]` is the altitude at `flip(y[i])` and `x[j]`. Thus `z[0, 0]` corresponds to the North-West corner of the topography. \n\nSpecific simulation outputs can be extracted with \n\n```python\nh_res = res.get_output(res_name)\n```\n\nwhere `res_name` must chosen among\n\n- `h` : Flow thickness in the direction perpendicular to the topography\n- `hvert` : Flow thickness in the vertical direction\n- `ux` and `uy` : Flow velocity in the X and Y direction (check whether it is in the cartesian reference frame or not)\n- `u` : Norm of the flow velocity\n- `hu` : Momentum (thickness * flow velocity)\n- `hu2` : Kinetic energy (thickness * square flow velocity)\n\nIt is also possible to extract 2D spatial static characteritics of the flow by using any of the previous states with `_[operation]`, where\n`[operation]` is chosen among, `max`, `mean`, `std`, `sum`, `min`, `final`, `initial`. For instance `h_max` is a 2D array with the\nmaximum simulated thickness at each point of the grid. `h_final` is the simulated thickness at the end of the simulation.\n`tilupy` will load these characteristics directly from the simulation output when possible (e.g. Shaltop records a maximum thickness array),\nor compute then from the available data. For instance, if the simulation results contains a file whith the maximum thickness, `h_max` will be\nread from this file. Otherwise, `h_max` is computed from the simulation recorded temporal snapshots (which is supposedly less precise).\n\nFor instance, to load the recorded thicknesses in the current example :\n\n```python\nres_name = 'h' \nh_res = res.get_output(res_name) # Thicknesses recorded at different times\n# h_res.d is a 3D numpy array of dimension (len(x) x len(y) x len(h_res.t))\nplt.imshow(h_res.d[:, :, -1]) # Plot final thickness.\nt = h_res.t # Get times of simulation outputs.\n```\n\nAnd to load the maximum thickness array :\n\n```python\nres_name = 'h_max'\nh_max_res = res.get_output(res_name) #h_max_res is read directly from simulation\n# results when possible, and is deduced from res.get_output('h') otherwise\n# h_max_res.d is a 2D numpy array of dimension (len(x) x len(y))\nplt.imshow(h_max_res.d)\n```\n\n### Process simulation results in python script <a name=\"process-simus-python\"></a>\n\n`tilupy`can be used to plot the results as images, where the flow state (thickness, velocity, ...)\nis shown with a colorscale on the underlying topography. Plots can be thouroughly customized (documentation not available yet).\n\nFor instance, the following code plots the flow thickness at each recorded time step, with a constant colorscale vraying from 0.1 to\n100 m. The topography is represented as a shaded relief with thin contour lines every 10 m, and bold contour_lines every 100 m. Plots are saved\nin a folder created in `folder_out`, but not displayed in the terminal (if you work in a developping environnement such as `spyder`).\n\n```python\ntopo_kwargs = dict(contour_step=10, step_contour_bold=100) # give interval between thin and bold contour lines\nparams_files = 'delta_*.txt'\ntilupy.cmd.plot_results('shaltop', 'h', params_files, folder_simus,\n save=True, display_plot=False, figsize=(15/2.54, 15/2.54),\n vmin=0.1, vmax=100, fmt='png',\n topo_kwargs=topo_kwargs)\n```\n\nThe following code acts similarly, but plots the maximum thickness instead, and used a segmented colormap given by `cmap_intervals`.\n\n```python\ntilupy.cmd.plot_results('shaltop', 'h_max', params_files, folder_simus,\n save=True, display_plot=False, figsize=(15/2.54, 15/2.54),\n cmap_intervals=[0.1, 5, 10, 25, 50, 100],\n topo_kwargs=topo_kwargs)\n```\n\nIt is also possible to save outputs back to rasters. The following code save all recorded thicknesses snapshots as tif files in a new folder\ncreated in `folder_out`.\n\n```python\ntilupy.cmd.to_raster('shaltop', 'h_max', params_files,\n folder_simus, fmt='tif')\n```\n\n### Process simulation results in command line <a name=\"process-simus-cmd\"></a>\n\n`tilupy` comes with command line scripts to allow for quick processing of results. They work similarly as the functions `tilupy.cmd.plot_results` and `tilupy.cmd.to_raster`, \nalthough there are less options. \n\n`tilupy_plot` will automatically plot and save results in a new folder `plot` located in the simulation output folder specified in the parameter file :\n\n```\ntilupy_plot [-h] [-n RES_NAME] [-p PARAM_FILES] [-f FOLDER] [--fmt FMT] [--vmin VMIN] [--vmax VMAX]\n [--minval_abs MINVAL_ABS]\n model\n```\n\n`RES_NAME` can be any of the strings listed in the previous section. For instance, to plot all thicknesses snaphsots from shaltop simulations in the current folder, type `tilupy_plot shaltop -n h`. If parameters files are located in `another/folder`, type, `tilupy shaltop -n h -f another/folder`. Similarly, to save thicknesses snapshots as ascii rasters, use `tilupy_to_raster shaltop -n h --fmt asc`.\n\n```\ntilupy_to_raster [-h] [-n RES_NAME] [-p PARAM_FILES] [-f FOLDER] [--fmt {tif,tiff,txt,asc,ascii}] model\n```\n\nWith both commands you can use the `-h` option do print help.\n\n## Models references <a name=\"models-refs\"></a>\n\nWe provide here a basic descriptions of models compatible with `tilupy`. The list of references is not exhaustive. \n\n### Shaltop <a name=\"ref-shaltop\"></a>\n\n`shaltop` models gravitational flow models over general topographies with small slope variation (small curvature) and friction. The equations are expressed in a horizontal/vertical reference frame and the shallow approximation is imposed in the direction normal to the slope. `shaltop` is not yet freely available. If you are interested, contact [m.peruzzetto@brgm.fr](mailto:m.peruzzetto@brgm.fr) or [mangeney@ipgp.fr](mailto:mangeney@ipgp.fr). \n\n- Bouchut, F., Mangeney-Castelnau, A., Perthame, B., Vilotte, J.-P., 2003. A new model of Saint Venant and Savage\u2013Hutter type for gravity driven shallow water flows. Comptes Rendus Math\u00e9matique 336, 531\u2013536. [https://doi.org/10.1016/S1631-073X(03)00117-1](https://doi.org/10.1016/S1631-073X(03)00117-1)\n- Bouchut, F., Westdickenberg, M., 2004. Gravity driven shallow water models for arbitrary topography. Communications in Mathematical Sciences 2, 359\u2013389. [https://doi.org/10.4310/CMS.2004.v2.n3.a2](https://doi.org/10.4310/CMS.2004.v2.n3.a2)\n- Mangeney-Castelnau, A., Bouchut, F., Vilotte, J.P., Lajeunesse, E., Aubertin, A., Pirulli, M., 2005. On the use of Saint Venant equations to simulate the spreading of a granular mass: numerical simulation of granular spreading. Journal of Geophysical Research: Solid Earth 110, B09103. [https://doi.org/10.1029/2004JB003161](https://doi.org/10.1029/2004JB003161)\n- Mangeney, A., Bouchut, F., Thomas, N., Vilotte, J.P., Bristeau, M.O., 2007. Numerical modeling of self-channeling granular flows and of their levee-channel deposits. Journal of Geophysical Research 112, F02017. [https://doi.org/10.1029/2006JF000469](https://doi.org/10.1029/2006JF000469)\n\n\n### r.avaflow <a name=\"ref-ravaflow\"></a>\n\n`r.avaflow represents` a GIS-supported open source software tool for the simulation of complex, cascading mass flows over arbitrary topography. It can be downloaded, along with the associated documentation, on the officiel [website](https://www.landslidemodels.org/r.avaflow/). Note that the integration of `r.avaflow` in `tilupy` is partial and potentially not adapted to new releases of `r.avaflow`. \n\n- Mergili, M., Fischer, J.-T., Krenn, J., Pudasaini, S.P., 2017. r.avaflow v1, an advanced open source computational framework for the propagation and interaction of two-phase mass flows. Geoscientific Model Development Discussions 10, 553\u2013569. [https://doi.org/10.5194/gmd-10-553-2017](https://doi.org/10.5194/gmd-10-553-2017)\n- Pudasaini, S.P., Mergili, M., 2019. A Multi-Phase Mass Flow Model. Journal of Geophysical Research: Earth Surface 124, 2920\u20132942. [https://doi.org/10.1029/2019JF005204](https://doi.org/10.1029/2019JF005204)\n\n\n",
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In the event the creation of the Derivative Software required modification of the Source Code, the Licensee undertakes that: 1. the resulting Modified Software will be governed by this Agreement, 2. the Integrated Contributions in the resulting Modified Software will be clearly identified and documented, 3. the Licensee will allow effective access to the source code of the Modified Software, at a minimum during the entire period of distribution of the Derivative Software, such that such modifications may be carried over in a subsequent version of the Software; it being understood that the additional cost of purchasing the source code of the Modified Software shall not exceed the cost of transferring the data. 5.3.4 COMPATIBILITY WITH THE CeCILL LICENSE When a Modified Software contains an Integrated Contribution subject to the CeCILL license agreement, or when a Derivative Software contains a Related Module subject to the CeCILL license agreement, the provisions set forth in the third item of Article 6.4 are optional. Article 6 - INTELLECTUAL PROPERTY 6.1 OVER THE INITIAL SOFTWARE The Holder owns the economic rights over the Initial Software. Any or all use of the Initial Software is subject to compliance with the terms and conditions under which the Holder has elected to distribute its work and no one shall be entitled to modify the terms and conditions for the distribution of said Initial Software. The Holder undertakes that the Initial Software will remain ruled at least by this Agreement, for the duration set forth in Article 4.2. 6.2 OVER THE INTEGRATED CONTRIBUTIONS The Licensee who develops an Integrated Contribution is the owner of the intellectual property rights over this Contribution as defined by applicable law. 6.3 OVER THE RELATED MODULES The Licensee who develops a Related Module is the owner of the intellectual property rights over this Related Module as defined by applicable law and is free to choose the type of agreement that shall govern its distribution under the conditions defined in Article 5.3.3. 6.4 NOTICE OF RIGHTS The Licensee expressly undertakes: 1. not to remove, or modify, in any manner, the intellectual property notices attached to the Software; 2. to reproduce said notices, in an identical manner, in the copies of the Software modified or not; 3. to ensure that use of the Software, its intellectual property notices and the fact that it is governed by the Agreement is indicated in a text that is easily accessible, specifically from the interface of any Derivative Software. The Licensee undertakes not to directly or indirectly infringe the intellectual property rights of the Holder and/or Contributors on the Software and to take, where applicable, vis-\u00e0-vis its staff, any and all measures required to ensure respect of said intellectual property rights of the Holder and/or Contributors. Article 7 - RELATED SERVICES 7.1 Under no circumstances shall the Agreement oblige the Licensor to provide technical assistance or maintenance services for the Software. However, the Licensor is entitled to offer this type of services. The terms and conditions of such technical assistance, and/or such maintenance, shall be set forth in a separate instrument. Only the Licensor offering said maintenance and/or technical assistance services shall incur liability therefor. 7.2 Similarly, any Licensor is entitled to offer to its licensees, under its sole responsibility, a warranty, that shall only be binding upon itself, for the redistribution of the Software and/or the Modified Software, under terms and conditions that it is free to decide. Said warranty, and the financial terms and conditions of its application, shall be subject of a separate instrument executed between the Licensor and the Licensee. Article 8 - LIABILITY 8.1 Subject to the provisions of Article 8.2, the Licensee shall be entitled to claim compensation for any direct loss it may have suffered from the Software as a result of a fault on the part of the relevant Licensor, subject to providing evidence thereof. 8.2 The Licensor's liability is limited to the commitments made under this Agreement and shall not be incurred as a result of in particular: (i) loss due the Licensee's total or partial failure to fulfill its obligations, (ii) direct or consequential loss that is suffered by the Licensee due to the use or performance of the Software, and (iii) more generally, any consequential loss. In particular the Parties expressly agree that any or all pecuniary or business loss (i.e. loss of data, loss of profits, operating loss, loss of customers or orders, opportunity cost, any disturbance to business activities) or any or all legal proceedings instituted against the Licensee by a third party, shall constitute consequential loss and shall not provide entitlement to any or all compensation from the Licensor. Article 9 - WARRANTY 9.1 The Licensee acknowledges that the scientific and technical state-of-the-art when the Software was distributed did not enable all possible uses to be tested and verified, nor for the presence of possible defects to be detected. In this respect, the Licensee's attention has been drawn to the risks associated with loading, using, modifying and/or developing and reproducing the Software which are reserved for experienced users. The Licensee shall be responsible for verifying, by any or all means, the suitability of the product for its requirements, its good working order, and for ensuring that it shall not cause damage to either persons or properties. 9.2 The Licensor hereby represents, in good faith, that it is entitled to grant all the rights over the Software (including in particular the rights set forth in Article 5). 9.3 The Licensee acknowledges that the Software is supplied \"as is\" by the Licensor without any other express or tacit warranty, other than that provided for in Article 9.2 and, in particular, without any warranty as to its commercial value, its secured, safe, innovative or relevant nature. Specifically, the Licensor does not warrant that the Software is free from any error, that it will operate without interruption, that it will be compatible with the Licensee's own equipment and software configuration, nor that it will meet the Licensee's requirements. 9.4 The Licensor does not either expressly or tacitly warrant that the Software does not infringe any third party intellectual property right relating to a patent, software or any other property right. Therefore, the Licensor disclaims any and all liability towards the Licensee arising out of any or all proceedings for infringement that may be instituted in respect of the use, modification and redistribution of the Software. Nevertheless, should such proceedings be instituted against the Licensee, the Licensor shall provide it with technical and legal assistance for its defense. Such technical and legal assistance shall be decided on a case-by-case basis between the relevant Licensor and the Licensee pursuant to a memorandum of understanding. The Licensor disclaims any and all liability as regards the Licensee's use of the name of the Software. No warranty is given as regards the existence of prior rights over the name of the Software or as regards the existence of a trademark. Article 10 - TERMINATION 10.1 In the event of a breach by the Licensee of its obligations hereunder, the Licensor may automatically terminate this Agreement thirty (30) days after notice has been sent to the Licensee and has remained ineffective. 10.2 A Licensee whose Agreement is terminated shall no longer be authorized to use, modify or distribute the Software. However, any licenses that it may have granted prior to termination of the Agreement shall remain valid subject to their having been granted in compliance with the terms and conditions hereof. Article 11 - MISCELLANEOUS 11.1 EXCUSABLE EVENTS Neither Party shall be liable for any or all delay, or failure to perform the Agreement, that may be attributable to an event of force majeure, an act of God or an outside cause, such as defective functioning or interruptions of the electricity or telecommunications networks, network paralysis following a virus attack, intervention by government authorities, natural disasters, water damage, earthquakes, fire, explosions, strikes and labor unrest, war, etc. 11.2 Any failure by either Party, on one or more occasions, to invoke one or more of the provisions hereof, shall under no circumstances be interpreted as being a waiver by the interested Party of its right to invoke said provision(s) subsequently. 11.3 The Agreement cancels and replaces any or all previous agreements, whether written or oral, between the Parties and having the same purpose, and constitutes the entirety of the agreement between said Parties concerning said purpose. No supplement or modification to the terms and conditions hereof shall be effective as between the Parties unless it is made in writing and signed by their duly authorized representatives. 11.4 In the event that one or more of the provisions hereof were to conflict with a current or future applicable act or legislative text, said act or legislative text shall prevail, and the Parties shall make the necessary amendments so as to comply with said act or legislative text. All other provisions shall remain effective. Similarly, invalidity of a provision of the Agreement, for any reason whatsoever, shall not cause the Agreement as a whole to be invalid. 11.5 LANGUAGE The Agreement is drafted in both French and English and both versions are deemed authentic. Article 12 - NEW VERSIONS OF THE AGREEMENT 12.1 Any person is authorized to duplicate and distribute copies of this Agreement. 12.2 So as to ensure coherence, the wording of this Agreement is protected and may only be modified by the authors of the License, who reserve the right to periodically publish updates or new versions of the Agreement, each with a separate number. These subsequent versions may address new issues encountered by Free Software. 12.3 Any Software distributed under a given version of the Agreement may only be subsequently distributed under the same version of the Agreement or a subsequent version. Article 13 - GOVERNING LAW AND JURISDICTION 13.1 The Agreement is governed by French law. The Parties agree to endeavor to seek an amicable solution to any disagreements or disputes that may arise during the performance of the Agreement. 13.2 Failing an amicable solution within two (2) months as from their occurrence, and unless emergency proceedings are necessary, the disagreements or disputes shall be referred to the Paris Courts having jurisdiction, by the more diligent Party. Version 1.0 dated 2006-09-05.",
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