Pdal opals notebook #67
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…l_opals_notebook
…l_opals_notebook
…s and added test_pdal_maintain_metadata
…l_opals_notebook
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## main #67 +/- ##
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+ Coverage 85.59% 85.71% +0.11%
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Files 13 13
Lines 1090 1120 +30
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+ Hits 933 960 +27
- Misses 157 160 +3
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You somehow removed the LFS pointers and added the data files as non-LFS content. That would need to be reverted... |
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I made some comments, mostly minor. However, there is one major showstopper for tomorrow's meeting: I looked at the visualization output and I am not sure we are seeing the expected result (results too similar compared to Bernhard's presentation). I need more time to investigate that, so I would postpone the merge.
| @@ -144,3 +144,4 @@ dmypy.json | |||
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| # Cython debug symbols | |||
| cython_debug/ | |||
| adaptivefiltering/data/uls_thingstaette.las | |||
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Should be removed, this is only your local setup of where to place the file.
| "source": [ | ||
| "# Opals Example Notebook\n", | ||
| "This notebook is a short example of the Opals utilities provided by `adaptivefiltering`.\n", | ||
| "If you have not worked with `adaptivefiltering` before please have a look at the `demo.ipynb`.\n", |
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demo.ipynb does not exist anymore
| "outputs": [], | ||
| "source": [ | ||
| "dataset = adaptivefiltering.DataSet(filename=\"data/uls_thingstaette.las\")\n", | ||
| "adaptivefiltering.opals.set_opals_directory(\"/home/gwydion/SSC/Opals/opals_2.4.0\")" |
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "dataset = adaptivefiltering.DataSet(filename=\"data/uls_thingstaette.las\")\n", |
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This should not have the data/ prefix as we will not ship it in the data directory of adaptivefiltering.
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "opals_dataset_3.show_hillshade(resolution=0.5, classification=asprs[\"ground\"])" |
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Why exactly does the resolution differ on example 3?
| "source": [ | ||
| "# Pdal Example Notebook\n", | ||
| "This notebook is a short example of the Pdal utilities provided by `adaptivefiltering`.\n", | ||
| "If you have not worked with `adaptivefiltering` before please have a look at the `demo.ipynb`.\n", |
| "outputs": [], | ||
| "source": [ | ||
| "pipeline_1 = adaptivefiltering.load_filter(\"Example_filter/Example_pdal_1.json\")\n", | ||
| "pipeline_2 = adaptivefiltering.load_filter(\"Example_filter/Example_pdal_1.json\")\n", |
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This loads the same filter 3 times!
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "dataset_3.show_hillshade(resolution=0.5, classification=asprs[\"ground\"])" |
| @@ -1,4 +1,6 @@ | |||
| [pytest] | |||
| testpaths = tests jupyter | |||
| testpaths = tests jupyter | |||
| filterwarnings = | ||
| ignore::DeprecationWarning | ||
| addopts = --ignore jupyter/opals_example.ipynb |
Fixed opals to pdal conversion by introducing a class variable
spatial_ref. When creating a pdal filter this is automatically set, only when creating a opals filter an extra step is taken and the spatial reference data is extracted with a pdal reader.