diff --git a/README.md b/README.md index f553c2d..eed0ed3 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,8 @@ # pyinfraformat -Python library for Finnish Infraformat (version 2.5) +Python library for reading, writing and analyzing Finnish borehole format Infraformat (version 2.5). +Well suited for scientific and research applications. ## Installation @@ -23,3 +24,56 @@ Library can be installed also by `git clone` / downloading zip. 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 +``` +![image](https://github.com/user-attachments/assets/a463e181-4ab4-479d-94f6-edcb19c0f598) + +```python +hole_figure = gtk_holes[10].plot() +hole_figure # View hole in jupyter +``` + +![image](https://github.com/user-attachments/assets/33b9c797-b084-44b2-88c8-dadd15fc540f) + +#### 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 +``` +![image](https://github.com/user-attachments/assets/e3e6030b-ccfc-4c59-9929-40a7f9900fa4)