 [](https://github.com/ambv/black) [](https://codecov.io/gh/ahartikainen/pyinfraformat)
# pyinfraformat
Python library for reading, writing and analyzing Finnish borehole format Infraformat (version 2.5).
Well suited for scientific and research applications.
## Installation
Latest (stable) `pyinfraformat` can be installed with pip
python -m pip install pyinfraformat
The latest (unstable) version can be installed from git with pip (needs git-tools).
python -m pip install git+https://github.com/ahartikainen/pyinfraformat
Library can be installed also by `git clone` / downloading zip.
git clone https://github.com/ahartikainen/pyinfraformat
cd pyinfraformat
python -m pip install .
To install inplace for development work, use `-e` command.
python -m pip install -e .
## Quickstart
#### Basic usage
```python
import pyinfraformat as pif
pif.set_logger_level(50) # Suppress non-critical warnings, recommended for large files
holes = pif.from_infraformat("*.tek")
holes = holes.project("TM35FIN")
bounds = holes.bounds
holes.to_infraformat("holes_tm35fin.tek")
bounds = [6672242-200 , 385795-200, 6672242 +200, 385795+200]
gtk_holes = pif.from_gtk_wfs(bounds, "TM35Fin")
print(gtk_holes) # View holes object
#Infraformat Holes -object:
# Total of 203 holes
# - PO ......... 161
# - HP ......... 13
# - PA ......... 12
# - NO ......... 2
# - NE ......... 1
# - KE ......... 5
# - KR ......... 9
html_map = gtk_holes.plot_map()
html_map.save("soundings.html")
html_map # View map in jupyter
```
```python
hole_figure = gtk_holes[10].plot()
hole_figure # View hole in jupyter
```
#### Plot histograms from laboratory tests
```python
import pandas as pd
bounds = [6672242-2000 , 385795-2000, 6672242 +2000, 385795+2000]
gtk_holes = pif.from_gtk_wfs(bounds, "TM35FIN", maxholes=25_000)
laboratory_tests = gtk_holes.filter_holes(hole_type=["NO", "NE"], start="1990-01-01")
df = laboratory_tests.get_dataframe()
df['data_Soil type'] = df['data_Soil type'].astype("string")
clay_samples = df[df['data_Soil type'].str.endswith("Sa", na=False)].reset_index()
clay_samples['data_Laboratory w'] = pd.to_numeric(clay_samples['data_Laboratory w'])
fig = clay_samples['data_Laboratory w'].plot.hist(bins='fd')
fig.set_title("Clay samples water content, %")
fig
```
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"description": " [](https://github.com/ambv/black) [](https://codecov.io/gh/ahartikainen/pyinfraformat)\n\n\n# pyinfraformat\nPython library for reading, writing and analyzing Finnish borehole format Infraformat (version 2.5). \nWell suited for scientific and research applications.\n\n## Installation\n\nLatest (stable) `pyinfraformat` can be installed with pip\n\n python -m pip install pyinfraformat\n\nThe latest (unstable) version can be installed from git with pip (needs git-tools).\n\n python -m pip install git+https://github.com/ahartikainen/pyinfraformat\n\nLibrary can be installed also by `git clone` / downloading zip.\n\n git clone https://github.com/ahartikainen/pyinfraformat\n cd pyinfraformat\n python -m pip install .\n\nTo install inplace for development work, use `-e` command.\n\n python -m pip install -e .\n\n## Quickstart\n#### Basic usage\n```python\nimport pyinfraformat as pif\npif.set_logger_level(50) # Suppress non-critical warnings, recommended for large files\nholes = pif.from_infraformat(\"*.tek\")\nholes = holes.project(\"TM35FIN\")\nbounds = holes.bounds\nholes.to_infraformat(\"holes_tm35fin.tek\")\n\nbounds = [6672242-200 , 385795-200, 6672242 +200, 385795+200]\ngtk_holes = pif.from_gtk_wfs(bounds, \"TM35Fin\")\nprint(gtk_holes) # View holes object\n#Infraformat Holes -object:\n# Total of 203 holes\n# - PO ......... 161\n# - HP ......... 13\n# - PA ......... 12\n# - NO ......... 2\n# - NE ......... 1\n# - KE ......... 5\n# - KR ......... 9\n\n\nhtml_map = gtk_holes.plot_map()\nhtml_map.save(\"soundings.html\")\nhtml_map # View map in jupyter\n```\n\n\n```python\nhole_figure = gtk_holes[10].plot()\nhole_figure # View hole in jupyter\n```\n\n\n\n#### Plot histograms from laboratory tests\n```python\nimport pandas as pd\nbounds = [6672242-2000 , 385795-2000, 6672242 +2000, 385795+2000]\ngtk_holes = pif.from_gtk_wfs(bounds, \"TM35FIN\", maxholes=25_000)\nlaboratory_tests = gtk_holes.filter_holes(hole_type=[\"NO\", \"NE\"], start=\"1990-01-01\")\ndf = laboratory_tests.get_dataframe()\ndf['data_Soil type'] = df['data_Soil type'].astype(\"string\")\nclay_samples = df[df['data_Soil type'].str.endswith(\"Sa\", na=False)].reset_index()\nclay_samples['data_Laboratory w'] = pd.to_numeric(clay_samples['data_Laboratory w'])\nfig = clay_samples['data_Laboratory w'].plot.hist(bins='fd')\nfig.set_title(\"Clay samples water content, %\")\nfig\n```\n\n",
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