""" Compositage of Drillholes ========================= This example shows how to composite a collection of drillholes. """ import os import numpy as np import geoassistant import sys # Path to example data test_resources_dir = os.path.join("./resources/") collar_path = os.path.join(test_resources_dir, 'FDN-S 02-11-25_Collar.csv') survey_path = os.path.join(test_resources_dir, 'FDN-S 02-11-25_Survey.csv') geotech_log_path = os.path.join(test_resources_dir, 'logs', 'FDN-C25-239.xlsx') # geotech_log_path = os.path.join(test_resources_dir, 'logs', 'FDN-C25-317.xlsx') # %% # Step 1 - Load drillhole positional data # --------------------------------------- # The geoassistant library provides convenient methods for reading collar and survey data. # These classes allow flexible column mapping, so the CSV structure can be user-defined. # The `readCollarsCsvFile` and `readSurveysCsvFile` functions return structured collections # that will be used to build the full 3D drillhole geometry. cc = geoassistant.readCollarsCsvFile(source=collar_path, id_key="HOLEID", x_key="X", y_key="Y", z_key="Z") sc = geoassistant.readSurveysCsvFile(source=survey_path, id_key="HOLEID", dip_key="DIP", azimuth_key="AZIMUTH", depth_key="DEPTH") # %% # Step 2 - Create drillhole geometry # ---------------------------------- # Using collars and surveys, the full trajectory of each drillhole can be reconstructed. # This is done through the `createDrillholesFromCollarsAndSurveys` method. # The result is a `DrillholesCollection` object, which supports spatial queries, data linking, # visualization, and parameter operations. drillholes = geoassistant.createDrillholesFromCollarsAndSurveys(collars=cc, surveys=sc) # %% # Basic info about the drillholes can now be queried directly from the object: print(f"Number of drillholes: {len(drillholes)}") print(f"Total length: {int(drillholes.getTotalLength()):,}") # %% # See how there is no length defined? That is because geoassitant doesn't have any reference # for the length of the drillholes. This can come in various ways: # # - By manually setting the length of each drill hole # - By setting the length from a log file # - By assigning the highest "To" value from a log file # %% # Step 3 - Load geotechnical interval data # ---------------------------------------- # Until now we just have traces of drillholes defined. In order to link them with their corresponding # logs, these must be provided correctly processed. In this example, this is done by the method # `readIntervalsExcelSheet`, which needs just basic parameters of the Excel-sheet like its name and the # columns where the "drillhole ID", "from" and "to" can be found. # # Additionally, the method can also receive a `DrillholesCollection` as argument, so the read logs are # automatically linked to the drillholes instances: ic = geoassistant.readIntervalsExcelSheet(source=geotech_log_path, sheetname="GeotechLog", id_col='B', from_col="C", to_col="D", drillholes=drillholes) dc = geoassistant.readDiscontinuitiesExcelSheet(source=geotech_log_path, sheetname="Discontinuity", id_col="B", depth_col="C", drillholes=drillholes) # dc = drillholes.getLoggedDiscontinuities() dc.setParameterColumn(parameter_id="AlphaAngle", column="E") dc.setParameterColumn(parameter_id="BetaAngle", column="F") # for d in dc: # if d.getDip() is not None: # # d.setParameterValue(parameter_id="AlphaAngle", value=0.) # print(d.getDepth(), d.getDip(), d.getDipdir(), d.getParameterValue(parameter_id="AlphaAngle"), d.getParameterValue(parameter_id="BetaAngle")) # # dc.export(savepath="test2.csv") # # dh = dc[0].getDrillhole() # sys.exit() # # snet = dh.createStereonet() # snet.initiate() # snet.savePlot(savepath="./test.png", plot_style="fisher") # sys.exit() # ic += geoassistant.readIntervalsExcelSheet(source=geotech_log_path2, sheetname="GeotechLog", # id_col='B', from_col="C", to_col="D", drillholes=drillholes) # %% # Step 4 - Map parameters from the file # ------------------------------------- # The raw intervals don’t contain metadata until parameter definitions are explicitly set. # Here, we declare that column "L" from the Excel sheet corresponds to the "RQD" parameter. import time ti = time.time() ic.setParameterColumn(parameter_id="OrientationLineOffset", column="G", notify=False) ic.setParameterColumn(parameter_id="RQD", column="L", notify=False) ic.setParameterColumn(parameter_id="QBartonJr", column="Y", notify=False) ic.setParameterColumn(parameter_id="QBartonJa", column="Z", notify=False) ic.setParameterColumn(parameter_id="StrongHardness", column="N", notify=False) ic.setParameterColumn(parameter_id="WeakHardness", column="O", notify=False) ic.setParameterColumn(parameter_id="WeakLength", column="P", notify=False) ic.setParameterConstantValue(parameter_id="Groundwater", value="Completely dry", notify=False) ic.setParameterConstantValue(parameter_id="JointSpacing", value=2, notify=False) ic.setParameterColumn(parameter_id="VeinFrequency", column="AB", notify=False) ic.setParameterConstantValue(parameter_id="VeinSetsNumber", value=1, notify=False) ic.setParameterColumn(parameter_id="VeinMineral", column="AC", notify=False) ic.setParameterConstantValue(parameter_id="QBartonJn", value=15, notify=False) # ic.checkCalculations() print(f"{round(time.time()-ti, 5)} seconds.") # sys.exit() # logged_drillholes = ic.getDrillholes() # composites = logged_drillholes.composite(composite_length=1.) # # composites.export(savepath="test.csv") # print(ic[13]) # sys.exit() # %% # Step 5 - Define computed parameters # ----------------------------------- # If a parameter is derived (rather than directly mapped from a column), # it can be computed manually. In this case, we define FF = n_joints / interval_length, # and assign it to the interval object using `setParameterValues`. n_joints = ic.getColumnValues(column="V") lengths = ic.getLengths() ff = np.array(n_joints) / np.array(lengths) ic.setParameterValues(parameter_id="FF", values=ff) # %% # Note: # Not all drillholes in the project may have matching geotechnical data. # You can filter the collection to obtain only those drillholes that have a given parameter defined. # Here, we get only those with FF values. ff_drillholes = drillholes.getSubsetByParameterDefinition(parameter_id="FF") # %% # Step 6 - Visualize the data # ---------------------------- # Using the filtered collection, we can easily generate histograms or other statistical views. # In this example, we show a histogram of RQD values, but only for drillholes where FF is defined. ff_drillholes.createParameterHistogram(parameter_id="RQD")