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rename pydepsi to depsi
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README.md

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# PyDePSI (Tentative name)
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This is repository is WIP, where we are developing a Python package for inteferometric SAR processing. The software will be inspired by the MATLAB software DePSI, but implemented in Python and include recent developments in the field.
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# DePSI
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This is the WIP repository for the Python version of DePSI *(), a Python package for inteferometric SAR processing. The software is inspired by the MATLAB version DePSI. In this repository, we implement classic DePSI algorithms and new InSAR developments in Python.
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## Installation for development
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Clone this repository and `cd` into it:
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```bash
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git clone git@github.com:MotionbyLearning/PyDePSI.git
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cd PyDePSI
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git clone git@github.com:TUDelftGeodesy/DePSI.git
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cd DePSI
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```
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Create a new conda environment (here we give an example name `pydepsi-dev`) with `mamba`.:
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Create a new conda environment (here we give an example name `depsi-dev`) with `mamba`.:
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```bash
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mamba create -c conda-forge -n pydepsi-dev python=3.12
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mamba create -c conda-forge -n depsi-dev python=3.12
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```
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Here we use Python 3.12 since we aim to support python 3.10 and above.
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Activate the environment:
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```bash
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mamba activate pydepsi-dev
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mamba activate depsi-dev
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```
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Install this package in development mode:
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pydepsi/io.py depsi/io.py

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import numpy as np
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from pydepsi.utils import _orbit_fit
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from depsi.utils import _orbit_fit
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# Define constants
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SC_N_PATTERN = r"\s+([-+]?\d+(?:\.\d+)?(?:[eE][-+]?\d+)?)"

pydepsi/slc.py depsi/slc.py

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pydepsi/utils.py depsi/utils.py

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examples/notebooks/demo_pydepsi.ipynb

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examples/scripts/README.md

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# Example script for PyDePSI
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# Example script for DePSI
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This folder contains scripts to run PyDePSI on SLURM infrastructures. One needs to modify `exec_python.slurm` to specify 1) a conda environment with PyDePSI and 2) the desired Python script. The following command can be used to execute the specified script:
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This folder contains scripts to run DePSI on SLURM infrastructures. One needs to modify `exec_python.slurm` to specify 1) a conda environment with DePSI and 2) the desired Python script. The following command can be used to execute the specified script:
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```bash
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sbatch exec_python.slurm
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## Prerequisites
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It is assumed that the user has a working conda environment with PyDePSI installed. This conda environment is required in the `exec_python.slurm` script.
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It is assumed that the user has a working conda environment with DePSI installed. This conda environment is required in the `exec_python.slurm` script.
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Some HPC system (for example SURF Spider system, see [this documentation](https://doc.spider.surfsara.nl/en/latest/Pages/software_on_spider.html)) may require the user to execute the conda environment inside a container. One can for example use the [LUMI container wrapper](https://docs.lumi-supercomputer.eu/software/installing/container-wrapper/) as a solution. The [JupyterDaskOnSLURM](https://github.com/RS-DAT/JupyterDaskOnSLURM/tree/main) tool from RS-DAT platform provides the LUMI container wrapper together with Jupyter Lab interface and Dask-Slurm cluster, see the [Container wrapper for Spider system](https://github.com/RS-DAT/JupyterDaskOnSLURM/blob/main/user-guide.md#container-wrapper-for-spider-system) section. For more information on the RS-DAT platform, please refer to the following section "PyDePSI with RS-DAT".
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Some HPC system (for example SURF Spider system, see [this documentation](https://doc.spider.surfsara.nl/en/latest/Pages/software_on_spider.html)) may require the user to execute the conda environment inside a container. One can for example use the [LUMI container wrapper](https://docs.lumi-supercomputer.eu/software/installing/container-wrapper/) as a solution. The [JupyterDaskOnSLURM](https://github.com/RS-DAT/JupyterDaskOnSLURM/tree/main) tool from RS-DAT platform provides the LUMI container wrapper together with Jupyter Lab interface and Dask-Slurm cluster, see the [Container wrapper for Spider system](https://github.com/RS-DAT/JupyterDaskOnSLURM/blob/main/user-guide.md#container-wrapper-for-spider-system) section. For more information on the RS-DAT platform, please refer to the following section "DePSI with RS-DAT".
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## PyDePSI with RS-DAT
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## DePSI with RS-DAT
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The [RS-DAT platform](https://rs-dat.github.io/RS-DAT/) developed by Netherlands eScience Center can be used to start up a Jupyter environment with Dask cluster. RS-DAT can also be used to start a Dask cluster scheduler on a HPC system, to which other Python scripts/processes can connect by providing the scheduler address. In this way, the same Dask cluster can be re-used for multiple Python script executions. This can be useful for developing and testing PyDePSI scripts.
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The [RS-DAT platform](https://rs-dat.github.io/RS-DAT/) developed by Netherlands eScience Center can be used to start up a Jupyter environment with Dask cluster. RS-DAT can also be used to start a Dask cluster scheduler on a HPC system, to which other Python scripts/processes can connect by providing the scheduler address. In this way, the same Dask cluster can be re-used for multiple Python script executions. This can be useful for developing and testing DePSI scripts.
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Please refer to the [RS-DAT JupyterDaskOnSLURM user guide](https://github.com/RS-DAT/JupyterDaskOnSLURM/blob/main/user-guide.md) for this option.

examples/scripts/script_reslc.py

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from dask_jobqueue import SLURMCluster
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import sarxarray
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from pydepsi.slc import ifg_to_slc
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from pydepsi.io import read_metadata
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from depsi.slc import ifg_to_slc
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from depsi.io import read_metadata
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# Make a logger to log the stages of processing
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logger = logging.getLogger(__name__)

pyproject.toml

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build-backend = "setuptools.build_meta"
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[project]
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name = "pydepsi"
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name = "depsi"
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version = "0.1.0"
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requires-python = ">=3.10"
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dependencies = [
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[tool.setuptools]
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packages = ["pydepsi"]
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packages = ["depsi"]
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[tool.pytest.ini_options]
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minversion = "6.0"
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[tool.coverage.run]
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branch = true
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source = ["pydepsi"]
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source = ["depsi"]
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[tool.ruff]
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lint.select = [

tests/test_io.py

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from pydepsi.io import read_metadata
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from depsi.io import read_metadata
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def test_read_metadata_lines_pixels():

tests/test_slc.py

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import numpy as np
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import xarray as xr
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from pydepsi.slc import _slc_complex_recontruct, ifg_to_slc
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from depsi.slc import _slc_complex_recontruct, ifg_to_slc
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def test__slc_complex_recontruct():

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