- class watex.geology.drilling.Borehole(lat=None, lon=None, area=None, status=None, depth=None, base_depth=None, geol=None, staticlevel=None, airlift=None, holeid=None, qmax=None, **kwds)[source]#
Bases:
GeologyFocused on Wells and Borehole offered to the population. To use the data for prediction purpose, each Borehole provided must be referenced on coordinates values or provided the same as the one used on ves or erp file.
- class watex.geology.drilling.DSBorehole(hole=None, dname=None, projection='ll', utm_zone=None, datum='WGS84', epsg=None, reference_ellipsoid=23, encoding='utf-8', lonlat=None, verbose=0)[source]#
Bases:
objectClass deals with Borehole datasets.
watex.geology.drilling.DSBoreholeworks with data collected in a single borehole. For instance, it could follow the arrangement ofh502data inwatex.datasets.load_hlogs()- Parameters:
hole (str) – Name or ID of the borehole.
dname (str, optional) – Depth column name. If depth is specify an attribute depth_ should be created. Depth specification is usefull for log plotting of machine training.
utm_zone (Optional, string) – zone number and ‘S’ or ‘N’ e.g. ‘55S’. Default to the centre point of coordinates points in the survey area. It should be a string (##N or ##S) in the form of number and North or South hemisphere, 10S or 03N
projection (str, ['utm'|'dms'|'ll']) – The coordinate system in which the data points for the profile is collected. If not given, the auto-detection will be triggered and find the suitable coordinate system. However, it is recommended to provide it for consistency. Note that if x and y are composed of value less than 180 degrees for longitude and 90 degrees for latitude, it should be considered as longitude-latitude (
ll) coordinates system. If x and y are degree-minutes-second (dmsordd:mm:ss) data, they must be specify as coordinate system in order to accept the non-numerical data before transforming toll. Ifdatais passed to thefit()method anddmsis not specify, x and y values should be discarded.datum (string, default = 'WGS84') – well known datum ex. WGS84, NAD27, NAD83, etc.
epsg (Optional, int) –
- epsg number defining projection (
see http://spatialreference.org/ref/ for moreinfo)
Overrides utm_zone if both are provided.
reference_ellipsoid (int, default=23) – reference ellipsoids is derived from Peter H. Dana’s website- http://www.utexas.edu/depts/grg/gcraft/notes/datum/elist.html Department of Geography, University of Texas at Austin Internet: pdana@mail.utexas.edu . Default is
23constrained to WGS84.encoding (str, default ='utf8') – Default encoding for parsing data. Can also be [‘utf-16-be’] for reading bytes characters.
lonlat (Tuple, Optional) – longitude/latitude for borehole coordinates. The location where the borehole is performed.
verbose (int, default=0) – Output messages.
- depth_#
Depth array if dname is specified.
- Type:
Series
- data_#
Sanitized dataframe.
- Type:
Pandas DataFrame
- feature_names_in_#
Name of features that composes the dataset.
- Type:
list
Note
Each columns of the dataframe is an attribute. Note that all the non- alphabetic letters is removed and replace by ‘_’.
Examples
>>> import watex as wx >>> from watex.geology import DSBorehole >>> hdata= wx.fetch_data ('hlogs',samples = 12 ).frame >>> b = DSBorehole (hole='H502').fit(hdata) >>> b.feature_names_in_ Out[77]: ['depth_top', 'depth_bottom', 'layer_thickness', 'resistivity', 'gamma_gamma', 'natural_gamma', 'sp', 'short_distance_gamma', 'well_diameter', 'aquifer_thickness', 'hole_depth_before_pumping', 'hole_depth_after_pumping', 'hole_depth_loss', 'depth_starting_pumping', 'pumping_depth_at_the_end', 'pumping_depth', 'section_aperture', 'k', 'kp', 'r', 'rp', 'hole_id', 'strata_name', 'rock_name', 'aquifer_group', 'pumping_level'] >>> b.strata_name Out[78]: 0 topsoil 1 gravel 2 mudstone 3 siltstone 4 mudstone
176 coal 177 siltstone 178 coarse-grained sandstone 179 fine-grained sandstone 180 coarse-grained sandstone Name: strata_name, Length: 181, dtype: object
- fit(data, **fit_params)[source]#
Fit Borehole data and populate attribute data.
By default if the projection is given as latitude/longitude xlon, ylat are longitude and latitude respectively.
- Parameters:
data (pd.DataFrame or Path-like object.) – Data containing the borehole informations.
fit_params (dict,) – Keyword arguments passed to
watex.utils.to_numeric_dtypes()for data management.
- Returns:
self – Instanced object for chaining method.
- Return type:
Instanced object
- property inspect#
Inspect object whether is fitted or not
- set_depth(z0=0.0, max_depth=None, reset_depth=Ellipsis)[source]#
Set the a random depth if depth is not supplied in the Borehole data
To fetch the depth, use attribute depth_. Note that if the depth exists, calling set_depth will erase the former depth value. Use in cautioness.
- Parameters:
z0 (float, default=0.) – The surface reference. Preferably, it is set to null.
max_depth (float, default=700.) – The maximum depth. Depth size must fit the length of the data in meters. Default depth is fixed to 700 meters.
reset_depth (bool, default =False,) – An alternative way to controle whether to keep the previous and new computed depth in the borehole data. The parameter erases the previous depth if exists the borehole data. If
Truea new depth is set in replacement to the previous depth and both are kept in the data otherwise.
- Returns:
self – Instanced object for chaining method.
- Return type:
Instanced object
Examples
>>> import watex as wx >>> from watex.geology import DSBorehole >>> hdata= wx.fetch_data ('hlogs').frame >>> b = DSBorehole (hole='H502').fit(hdata) >>> b.set_depth () >>> b.depth_ Out[82]: 0 0.000000 1 3.888889 2 7.777778 3 11.666667 4 15.555556
176 684.444444 177 688.333333 178 692.222222 179 696.111111 180 700.000000 Name: depth, Length: 181, dtype: float64 >>> b.set_depth (max_depth = 900, reset_depth= True ) >>> b.depth_ Out[85]: 0 0.0 1 5.0 2 10.0 3 15.0 4 20.0
176 880.0 177 885.0 178 890.0 179 895.0 180 900.0 Name: depth, Length: 181, dtype: float64
- set_strata(add_electrical_properties=False, random_state=None, shuffle=True, reset_strata=Ellipsis, reset_electrical_properties=Ellipsis)[source]#
Generate a pseudo strata associated to each depth in the borehole data.
- Parameters:
add_electrical_properties (bool, default=False,) – Add electrical resistivty values associated to each generated stratum
random_state (int, array-like, BitGenerator, np.random.RandomState, np.random.Generator, optional) – If int, array-like, or BitGenerator, seed for random number generator. If np.random.RandomState or np.random.Generator, use as given.
shuffle (bool, default=True) – Shuffle the random generated thicknesses.
reset_strata (bool, default=False,) – generate new strata at each depth. If
Trueand the name strata is valid in the borehole data colum name. Layer names that composes each stratum should be erased.reset_electrical_properties (bool, default=False) – Erase the former electrical values and replace by new names that fit each strata.
- Returns:
self – Instanced object for chaining method.
- Return type:
Instanced object
Examples
>>> import watex as wx >>> from watex.geology import DSBorehole >>> hdata= wx.fetch_data ('hlogs', key='h803').frame >>> b = DSBorehole (hole='H803').fit(hdata) >>> b.set_strata () >>> b.strata_ Out[122]: 0 tourmalinite 1 silt 2 mud 3 volcaniclastic rock 4 ore minerals
129 sulphide-rich material 130 argillite 131 graphite 132 high-Mg basalt 133 shale Name: strata, Length: 134, dtype: object >>> b.set_strata (add_electrical_properties= True, reset_strata= True) >>> b.strata_ Out[123]: 0 phyllite 1 syenite 2 laterite 3 saprolite 4 psammopelite
129 chert 130 granulite 131 pyroclastic rock 132 lamprophyre 133 ignimbrite Name: strata, Length: 134, dtype: object
b.strata_electrical_properties_ Out[124]: 0 0.0 1 0.0 2 0.0 3 330.6 4 0.0
129 0.0 130 0.0 131 0.0 132 0.0 133 0.0 Name: strata_electrical_properties, Length: 134, dtype: float64 >>>
- set_thickness(h0=1, shuffle=True, dirichlet_dist=Ellipsis, reset_layer_thickness=Ellipsis, reset_depth=Ellipsis, **kws)[source]#
Generate a random layer thickness from borehole refering to the depth.
To fetch the thickness, use attribute layer_thickness_. Use reset_layer_thickness to set new strata thicknesses.
- Parameters:
h0 (int, default='1m') – Thickness of the first layer.
shuffle (bool, default=True) – Shuffle the random generated thicknesses.
dirichlet_dis (bool, default=False) – Draw samples from the Dirichlet distribution. A Dirichlet-distributed random variable can be seen as a multivariate generalization of a Beta distribution. The Dirichlet distribution is a conjugate prior of a multinomial distribution in Bayesian inference.
reset_layer_thickness (bool, default=False,) – Set new layer thicknesses to the existing stratum. If
Trueand the data included layer thicknesses, the latter should be dropped in replacement to the new ones. However, if False, no action is performed and both are kept in the data.reset_depth (bool, default=False) – Note that thickness generating works with the depth. So, if the reset_depth is set to
True, a new depth is computed and drop the former ones. From this new depth, the thickness generating is creating.random_state (int, array-like, BitGenerator, np.random.RandomState, np.random.Generator, optional) – If int, array-like, or BitGenerator, seed for random number generator. If np.random.RandomState or np.random.Generator, use as given.
unit (str, default='m') – The reference unit for generated layer thicknesses. Default is
meters
- Returns:
self – Instanced object for chaining method.
- Return type:
Instanced object
Examples
>>> import watex as wx >>> from watex.geology import DSBorehole >>> hdata= wx.fetch_data ('hlogs').frame >>> b = DSBorehole (hole='H502').fit(hdata) >>> b.set_thickness () >>> b.layer_thickness_ 0 5.410380 1 2.068812 2 0.398028 3 6.352873 4 6.395714
176 3.396871 177 0.012463 178 7.124004 179 7.038323 180 3.439711 Name: layer_thickness, Length: 181, dtype: float64 >>> b.set_thickness (dirichlet_dist=True, reset_layer_thickness=True
).layer_thickness_
Out[89]: 0 0.681640 1 1.986043 2 6.413090 3 5.305284 4 0.000144
176 4.119242 177 12.161252 178 1.809102 179 0.408810 180 4.281848 Name: layer_thickness, Length: 181, dtype: float64
- class watex.geology.drilling.DSBoreholes(area=None, holeid=None, lat=None, lon=None, projection='ll', utm_zone=None, datum='WGS84', epsg=None, encoding='utf-8', interp_coords=False, reference_ellipsoid=23, verbose=False)[source]#
Bases:
objectClass deals with many boreholes dataset.
DSBoreholes works with the data set composed of multiple borehole data. The data columns are the all attributes of the object and any non-alphateic character is by
_. For instance, a column namelayer thicknessshould have an attribute namedlayer_thickness. Each borehole (row) data become its own object which encompasses all columns as attributes. To have full control of how data must be retrieved,holeidparameter must be set. For instance, to retrieve the borehole with ID equals to bx02, after fitting the class with appropriate parameters, attibute hole depth ( if exist in the data) can be retrieved asself.hole.bx02.hole_depth.By default if the projection is given as latitude/longitude
- Parameters:
area (str) – Name of area where the data collection is made.
holeid (str, optional) –
- The name of column of the boreholes collections ID. Note that if
given, it must exist in the borehole datasets. Note that if hole ID is not specified, each borehole can be fetched from a attribute hole count from 0 to n_samples. For instance, the borehole number 12 can be collected using:
>>> b = DSBoreholes ().fit(<borehole_data>) >>> b.hole.hole11
where 12 is the 12em position as Python index starts with 0. However when holeid is specified, the hole attribute is replaced by each value of the hole_id column as:
>>> borehole_data['hole_id'][:3] 0 B0092 1 B0093 2 B0094 Name: hole_id, dtype: object >>> b.hole.B0092 >>> b.hole.B0094
where
B0092orB0094are the borehole in the columnshole_id. Note thathole_idcan be any other names at least it is explicitly specified as a argument of the ``holeid` parameter.lon (ArrayLike 1d /str , optional) – One dimensional arrays. xlon can be consider as the abscissa of the landmark and ylat as ordinates array. If xlon or ylat is passed as string argument, data must be passed as fit_params keyword arguments and the name of xlon and y must be a column name of the data. By default xlon and ylat are considered as longitude and latitude when
dmsorllcoordinate system is passed.lat (ArrayLike 1d /str , optional) – One dimensional arrays. xlon can be consider as the abscissa of the landmark and ylat as ordinates array. If xlon or ylat is passed as string argument, data must be passed as fit_params keyword arguments and the name of xlon and y must be a column name of the data. By default xlon and ylat are considered as longitude and latitude when
dmsorllcoordinate system is passed.utm_zone (Optional, string) – zone number and ‘S’ or ‘N’ e.g. ‘55S’. Default to the centre point of coordinates points in the survey area. It should be a string (##N or ##S) in the form of number and North or South hemisphere, 10S or 03N
projection (str, ['utm'|'dms'|'ll']) – The coordinate system in which the data points for the profile is collected. If not given, the auto-detection will be triggered and find the suitable coordinate system. However, it is recommended to provide it for consistency. Note that if x and y are composed of value less than 180 degrees for longitude and 90 degrees for latitude, it should be considered as longitude-latitude (
ll) coordinates system. If x and y are degree-minutes-second (dmsordd:mm:ss) data, they must be specify as coordinate system in order to accept the non-numerical data before transforming toll. Ifdatais passed to thefit()method anddmsis not specify, x and y values should be discarded.datum (string, default = 'WGS84') – well known datum ex. WGS84, NAD27, NAD83, etc.
epsg (Optional, int) –
- epsg number defining projection (
see http://spatialreference.org/ref/ for moreinfo)
Overrides utm_zone if both are provided.
encoding (str, default ='utf8') – Default encoding for parsing data. Can also be [‘utf-16-be’] for reading bytes characters.
interp_coords (bool, default=False) – Interpolate position coordinates.
reference_ellipsoid (int, default=23) – reference ellipsoids is derived from Peter H. Dana’s website- http://www.utexas.edu/depts/grg/gcraft/notes/datum/elist.html Department of Geography, University of Texas at Austin Internet: pdana@mail.utexas.edu . Default is
23constrained to WGS84.verbose (int, default=0) – Output messages.
- lon_, lat_
longitude/latitude of coordinates arrays.
- Type:
Arraylike,
- `hole.<holeid>.<data_column>`
Each borehole, commonly which ID correspond to each row. Each row can be fetched as ‘holeID’. If holeid is nt specified, the string literal hole+index of data composed the borehole object.
- Type:
Notes
When data is supplied and lon and lat are given by their names existing in the dataframe columns, by default, the non-numerical data are removed. However, if y and x are given in DD:MM:SS in the dataframe, the coordinate system must explicitly set to ``dms` to keep the non-numerical values in the data.
Examples
>>> import watex as wx >>> from watex.geology import DSBoreholes >>> bs_data = wx.fetch_data ('nlogs', key='hydro', samples=12 , as_frame=True ) >>> bs=DSBoreholes ().fit(bs_data) >>> bs.holeid Out[61]: 'hole' >>> # when the default object hole is set as: >>> bs.hole # outputs a Boxspace object each borehole can be retrieved >>> # as hole object count from 0. to number or rows -1. Here is an >>> example of fetching the hole 11. >>> bs.hole.hole10 Out[62]: {'hole_id': 'B0103', 'uniform_number': 1.1343e+16, 'original_number': 'Guangzhou multi-element urban geological survey drilling 19ZXXSW11', 'lon': '113:43:00.99', 'lat': '23:16:17.23', 'longitude': 113.71694166666668, 'latitude': 23.271452777777775, 'east': 2577207.0, 'north': 19778060.0, 'easting': 2577207.276, 'northing': 19778177.29, 'coordinate_system': 'Xian 90', 'elevation': 22.0, 'final_hole_depth': 60.1, 'quaternary_thickness': 45.8, 'aquifer_thickness': 18.1, 'top_section_depth': 42.0, 'bottom_section_depth': 60.1, 'groundwater_type': 'igneous rock fissure water', 'static_water_level': 2.36, 'drawdown': 28.84, 'water_inflow': 0.08, 'unit_water_inflow': 0.003, 'filter_pipe_diameter': 0.16, 'water_inflow_in_m3_d': 2.94} >>> # when we specified the hole ID to the column that compose the ID like: >>> bs=DSBoreholes (holeid ='hole_id').fit(bs_data) >>> bs.hole.B0103 Out[63]: {'hole_id': 'B0103', 'uniform_number': 1.1343e+16, 'original_number': 'Guangzhou multi-element urban geological survey drilling 19ZXXSW11', 'lon': '113:43:00.99', 'lat': '23:16:17.23', 'longitude': 113.71694166666668, 'latitude': 23.271452777777775, 'east': 2577207.0, 'north': 19778060.0, 'easting': 2577207.276, 'northing': 19778177.29, 'coordinate_system': 'Xian 90', 'elevation': 22.0, 'final_hole_depth': 60.1, 'quaternary_thickness': 45.8, 'aquifer_thickness': 18.1, 'top_section_depth': 42.0, 'bottom_section_depth': 60.1, 'groundwater_type': 'igneous rock fissure water', 'static_water_level': 2.36, 'drawdown': 28.84, 'water_inflow': 0.08, 'unit_water_inflow': 0.003, 'filter_pipe_diameter': 0.16, 'water_inflow_in_m3_d': 2.94} >>> # each columns can be fetched as >>> bs.quaternary_thickness Out[64]: 0 40.5 1 12.3 2 25.5 3 40.0 4 35.0 5 47.0 6 34.0 7 40.4 8 15.1 9 17.2 10 45.8 11 47.0 Name: quaternary_thickness, dtype: float64
- fit(data, **fit_params)[source]#
Fit Hole data set and populate attributes.
- Parameters:
data (Path-like Object or DataFrame) – Hole data.
fit_params (dict,) – Keyword arguments passed to
watex.to_numeric_dtypes()to sanitize the data.
- Returns:
self – Instanced object for chaining methods.
- Return type:
- property inspect#
Inspect object whether is fitted or not
- set_coordinates(reflong, reflat, step='5m', todms=False, r=45, **kws)[source]#
Generate longitude and latitude coordinates for boreholes.
It assumes boreholes are aligned along the same axis.
- Parameters:
reflong (float or string or list of [start, stop]) – Reference longitude in degree decimal or in DD:MM:SS for the first site considered as the origin of the landmark.
reflat (float or string or list of [start, stop]) – Reference latitude in degree decimal or in DD:MM:SS for the reference site considered as the landmark origin. If value is given in a list, it can containt the start point and the stop point.
step (float or str) – Offset or the distance of seperation between different sites in meters. If the value is given as string type, except the
km, it should be considered as amvalue. Only meters and kilometers are accepables.r (float or int) – The rotate angle in degrees. Rotate the angle features toward the direction of the projection profile. Default value use the
bearing()value in degrees.todms (bool, Default=False) – Reconvert the longitude/latitude degree decimal values into the DD:MM:SS.
kws (dict,) – Additional keywords of
makeCoords().
- Returns:
self – Instanced object for method chaining.
- Return type:
Instanced object
Examples
>>> bs_data = wx.fetch_data ('nlogs', key='ns', samples=7, as_frame=True ) >>> bs=DSBoreholes ().fit(bs_data) >>> bs.set_coordinates(reflong= 113.4, reflat=22.56, step ='10m') >>> bs.set_coordinates(reflong= 113.4, reflat=22.56, step ='10m') >>> bs.lat_ Out[71]: array([22.56 , 22.56009391, 22.56018782, 22.56028174, 22.56037565, 22.56046956, 22.56056347]) >>> bs.lon_ Out[72]: array([113.4 , 113.40007436, 113.40014871, 113.40022307, 113.40029742, 113.40037178, 113.40044614])
- class watex.geology.drilling.DSDrill(area=None, holeid=None, dname=None, projection='ll', utm_zone=None, datum='WGS84', encoding='utf-8', epsg=None, reference_ellipsoid=23, properties=None, **kwd)[source]#
Bases:
GeoBaseDrill data set class.
DSDrillreads, constructs the well/hole (drillhole:DH), geology and geochemistry samples into a data set for transforming geophysics, geology, GIS, and geochemistry data collecting in a survey area into a three dimensional representation with `Oasis montaj`_. Deal with drillhole menu of Oasis Montaj software. Build data and contruct three dimensional data with `Oasis montaj`_ in Seequent.- Parameters:
- area: str
Area where the drilling operation is performed.
- holeid: str,
the column name in the data where the well/hole ID is stored.
- dname: str, optional
Depth column name. If depth is specify an attribute depth_ should be created. Depth specification is usefull for log plotting of machine training.
- utm_zone: Optional, string
zone number and ‘S’ or ‘N’ e.g. ‘55S’. Default to the centre point of coordinates points in the survey area. It should be a string (##N or ##S) in the form of number and North or South hemisphere, 10S or 03N
- projection: str, [‘utm’|’dms’|’ll’]
The coordinate system in which the data points for the profile is collected. If not given, the auto-detection will be triggered and find the suitable coordinate system. However, it is recommended to provide it for consistency. Note that if x and y are composed of value less than 180 degrees for longitude and 90 degrees for latitude, it should be considered as longitude-latitude (
ll) coordinates system. If x and y are degree-minutes-second (dmsordd:mm:ss) data, they must be specify as coordinate system in order to accept the non-numerical data before transforming toll. Ifdatais passed to thefit()method anddmsis not specify, x and y values should be discarded.- datum: string, default = ‘WGS84’
well known datum ex. WGS84, NAD27, NAD83, etc.
- encoding: str, default =’utf8’
Default encoding for parsing data. Can also be [‘utf-16-be’] for reading bytes characters.
- epsg: Optional, int
- epsg number defining projection (
see http://spatialreference.org/ref/ for moreinfo)
Overrides utm_zone if both are provided.
- reference_ellipsoid: int, default=23
reference ellipsoids is derived from Peter H. Dana’s website- http://www.utexas.edu/depts/grg/gcraft/notes/datum/elist.html Department of Geography, University of Texas at Austin Internet: pdana@mail.utexas.edu . Default is
23constrained to WGS84.
- properties: dict,
Data column can not fit the Drilling property columns. In that case. Mapping the property names is usefull to specify the columns in the original data that fits the
DSDrillproperty codes. For instance:properties ={"hole name": 'DH_Hole', "easting": 'DH_East', "northing": 'DH_Northing' } where "hole name", "easting" and "northing" are the column names in the former data set. These names should be replaced by the "DH_Hole", "DH_East" and "DH_North" respectively. The mapping can be used to specify any other property names. Note that the valuable properties are: - "DH_Hole": Well/hole ID - "DH_East": Easting coordinates of the well/hole - "DH_North": Northing coordinates of the well/hole. - "Mask": Any comment about the well/hole ID - "DH_RH": Radius value of the well/hole ID - 'DH_From': Top(roof) of any stratum/sample or rock in the well/hole. - "DH_To" : Wall( bottom) of any stratum/sample or rock in the well/hole. - "Rock" : Rock or strata/layer in the well/hole. - "DH_Azimuth": Azimuth value in the well/hole. - 'DH_Top': Surface-level of the well/hole compared to the level of sea. - 'DH_Bottom': Maximum depth of the well/hole. - 'DH_PlanDepth': Any section performed in the well/hole can be inputed. - 'DH_Decr': Description of the well/hole. - 'Sample': Sample collected in the well/hole at different depth. - 'DH_Dip': Dip of the well/hole. - 'Elevation': Elevation of the well/hole. - 'DH_RL': Level of piezometric value if exists in the well/hole.
- verbose: int, default=0
Output messages.
- Attributes:
- depth_: Series
Depth array if dname is specified.
- data_: Pandas DataFrame
Sanitized dataframe.
- collar_:Pandas DataFrame
Collar data composed of each borehole description.
- geology_: Pandas DataFrame
Geology data that compose each geological rocks
- samples_: Pandas DataFrame
Each Geochemistry samples data compose each sample collected in the survey area.
- build_collar(*, return_data=False, compute_azimuth=Ellipsis, utm_zone=Ellipsis, **kwd)[source]#
Build manually the collar data of collected drilling area.
Collar data is composed of well/hole description and usefull informations.
:meth:`build_collar collect each drillhole informations during the drilling operations or well contructions. The total of the information will build a collar dataset which can be used to Oasis Montaj software modeling. Below is an example of collar data set construction. This is some explanation of the prompt:
well/hole ID: Is the name or ID of the rocks or strata collected in the area
coordinates (xlon, xlat): is the geographical coordinates where the drilling operation is performed. Expect projection is
ll. To enter the UTM coordinates, set the projection in the building object toutmlike:>>> DSDrill (projection='utm').build_collar (return_data =True )
radius (m): Is the radius of the hole/well
surface-level: The level of the well/hole compared to the level of the sea. By default it is set to null as the level of the sea.
depth: depth of the well/hole in meters.
dip: dip in degree of the well/hole.
elevation: elevation value of the well/hole in meters. Default is no topography i.e. equal null.
azimuth: azimuth value in degrees. If not given explicitely, it can be calculated using the utm coordinates provided that the parameter compute_azimuth is set to
Trueand utm_zone is also provided. In this case, we assume that all well/hole collected belongs to the same area. Furthermore, azimuth calculation will cancel if one of the above condition is not met and if only a single borehole is supplied.plan-depth: Is a litteral string to give at which stage a section in a borehole is performed. Note that this is optional parameter and can be skipped. It has no more influence about the collar construction.
description: Give a short description of well/hole mostly about the drilling settlment.
mask/comments: Is any comments aboud the well/hole.
- Parameters:
return_data (bool, default=False,) – Return the collar dataset rather than object (
False) after entering the appropriate argumments. Note that evenTrue, the collar data set can be retrieved via the attributecollar_.compute_azimuth (bool, default=False) – Recompute the azimuth using the UTM coordinates. Note that projection need to be turned in ‘utm’ as well as the ‘utm_zone’ needs also to be supplied.
utm_zone (str,) – zone number and ‘S’ or ‘N’ e.g. ‘55S’. Default to the centre point of coordinates points in the survey area. It should be a string (##N or ##S)in the form of number and North or South hemisphere, 10S or 03N. if
utm_zoneis already set, it is not need to reset again. Resetting new utm_zone will erase the value of the former attribute. However for azimuth calculation, utm zone cannot be None otherwise the process is aborted.
- Returns:
self, collar dataset – Return object when
return_data=Falseand DataFrame otherwise.- Return type:
DSDrillor pd.DataFrame.
Examples
>>> col_data=DSDrill (projection ='utm').build_collar (return_collar =True ) Enter the well/hole ID:DXT03 Enter DXT03 coordinates (xlon, ylat):297856 352145 Enter DXT03 radius in meters [Optional]:.25 Enter DXT03 surface-level <top> in meters[0.]: Enter DXT03 depth <bottom> in meters[700.]:120 Enter DXT03 dip in degrees [-90]: Enter DXT03 elevation in meters [0.]: Enter DXT03 azimuth [Optional]: Enter DXT03 plan-depth [Optional]:wandx01 Enter DXT03 description [Optional]:hole-test Enter valuable comments about DXT03 [Optional]:RAS Tap "exit|0" to terminate or "Enter" to continue: Enter the well/hole ID:toxg Enter TOXG coordinates (xlon, ylat):125869 235645 Enter TOXG radius in meters [Optional]:2.3 Enter TOXG surface-level <top> in meters[0.]:-10 Enter TOXG depth <bottom> in meters[700.]:135 Enter TOXG dip in degrees [-90]:-70 Enter TOXG elevation in meters [0.]:3 Enter TOXG azimuth [Optional]:2.3 Enter TOXG plan-depth [Optional]:wxzu Enter TOXG description [Optional]:None Enter valuable comments about TOXG [Optional]:RAS Tap "exit|0" to terminate or "Enter" to continue:0 >>> col_data Out[3]: DH_Hole DH_East DH_North DH_RH ... DH_Azimuth DH_PlanDepth DH_Decr Mask 0 DXT03 297856.0 352145.0 0.25 ... NaN wandx01 hole-test RAS 1 TOXG 125869.0 235645.0 2.30 ... 2.3 wxzu None RAS
- build_drillholes(kind, return_data=Ellipsis, hole_elevation=0.0, compute_azimuth=Ellipsis, utm_zone=Ellipsis)[source]#
Build drillholes [‘collar|’geology’|’samples’] mannually through the parameter kind.
All the drillholes have the common attributes such as:
DH_Hole- well/hole , rock or sample ID: Is the ID of the geochemistry samples, rocks/strata or well/holes collected in the area"DH_East"and"DH_North"- coordinates (xlon, xlat): is the geographical coordinates where the drilling operation is performed. Expect projection isll. To enter the UTM coordinates, set the projection in the building object toutmlike:>>> DSDrill (projection='utm').build_collar (return_data =True )
"DH_RH"- radius (m): Is the radius of the hole/wellMask- mask/comments: Is any comments aboud the samples/geology or well/hole.
Besides, there are some other specific attributes related to each drillhole. For instance, the following attributes are required for:
collar:
"DH_Top"- surface-level: The level of the well/hole compared to the level of the sea. By default it is set to null as the level of the sea."DH_Bottom"- depth: depth of the well/hole in meters."DH_Dip"- dip: dip in degree of the well/hole."Elevation"- elevation: elevation value of the well/hole in meters. Default is no topography i.e. equal null."DH_Azimuth"- azimuth: azimuth value in degrees. If not given explicitely, it can be calculated using the utm coordinates provided that the parameter compute_azimuth is set toTrueand utm_zone is also provided. In this case, we assume that all well/hole collected belongs to the same area. Furthermore, azimuth calculation will cancel if one of the above condition is not met and if only a single borehole is supplied."DH_PlanDepth"- plan-depth: Is a litteral string to give at which stage a section in a borehole is performed. Note that this is optional parameter and can be skipped. It has no more influence about the collar construction.DH_descr- description: Give a short description of well/hole mostly about the drilling settlment.
geology:
"DH_From"and"DH_To"is computed from the layer thicknesses i.e. the thickness of each strata in the whole. Note that when many thicknesses are supplied, it may correspond to each layer. Thus, the number of thicknesses must equal to the number of layers."Rock"- the rock/layer names. It should be equals to the number of layer thicknesses. If not the case,NAshould beused to indicate the missing layer/rock name in the geology dataset.
samples:
"DH_From"and"DH_To"- samples thickness: Ask about the thickness of the samples in the whole. Note that when many thickness are supplied, it means the same sample is collected at different depth. There are two kind of data to supply:t-value: Compose only with the layer thickness values. For instance
t= "10 20 7 58"indicates four samples with thicknesses equals to 10, 20, 7 and 58 ( meters) respectively.tb-range: compose only with thickness range at each depth. For instance
t= "0-10 10-30 40-47 101-159". Note the character used to separate thickness range is'-'. Here, the top(roof) and bottom(wall) of the sample are 0 (top) and 10 (bottom), 10 and 30, 40 and 47 , and 101 and 159 for the same sample.Note that any mixed types is not acceptable and willraises error. To verify whether the expected samples values is acceptable or not, use the following
watex.utils.geotools.get_thick_from_range()orwatex.utils.geotools.get_thick_from_values()functions."Sample"- sample name: Is the name of samples collected refereing to the different depth. In principle, the number of samples thickness must equals to the number of samples. If not the case,NAshould be used to indicate the missing samples in the geosamples dataset.
- Parameters:
kind (str) – kind of drillhole to build. It could be [‘collar|’geology’|’samples’] Until now, ‘elevation’ drillhole is not built yet.
return_data (bool, default=False,) – Return the geology dataset rather than object (
False) after entering the appropriate argumments. Note that evenTrue, the geology data set can be retrieved via the attributegeology_.hole_elevation (float, default=0,) – The elevation or the level of surface of the well/hole compared to the level of sea. Note that elevation must be negative value on the top of the air for layer/strat calculation.
compute_azimuth (bool, default=False) – Recompute the azimuth using the UTM coordinates. Note that projection need to be turned in ‘utm’ as well as the ‘utm_zone’ needs also to be supplied.
utm_zone (str,) – zone number and ‘S’ or ‘N’ e.g. ‘55S’. Default to the centre point of coordinates points in the survey area. It should be a string (##N or ##S)in the form of number and North or South hemisphere, 10S or 03N. if
utm_zoneis already set, it is not need to reset again. Resetting new utm_zone will erase the value of the former attribute. However for azimuth calculation, utm zone cannot be None otherwise the process is aborted.
- Returns:
self, collar/geology/geochemistry samples dataset – Return object when
return_data=Falseand DataFrame otherwise.- Return type:
DSDrillor pd.DataFrame.
Examples
>>> from watex.geology import DSDrill >>> DSDrill().build_drillholes ('collar', return_data=True) Enter the well/hole ID:Dh00 Enter DH00 coordinates (x/lon, y/lat):11 15 Enter DH00 radius in meters [Optional]:0.2 Enter DH00 surface-level <top> in meters[0.]: Enter DH00 depth <bottom> in meters[700.]: Enter DH00 dip in degrees [-90]: Enter DH00 elevation in meters [0.]:12 Enter DH00 azimuth [Optional]: Enter DH00 plan-depth [Optional]: Enter DH00 description [Optional]: Enter valuable comments about DH00 [Optional]:testDh Tap "exit|0" to terminate or "Enter" to continue:0 Out[16]: DH_Hole DH_East DH_North ... DH_PlanDepth DH_Decr Mask 0 DH00 1.659298e+06 715053.016841 ... NaN NaN testDh >>> DSDrill().build_drillholes('geology') Enter the well/hole ID:Geo00 Enter GEO00 coordinates (x/lon, y/lat):11 15 Enter GEO00 radius in meters [Optional]:2 Enter the GEO00 depth in meters: 60 Enter each stratum thickness of GEO00 [top-->bottom] in meters:12 Enter the layer/rock names of GEO00 [top-->bottom]:sand Enter valuable comments about GEO00 [Optional]:test-geo Tap "exit|0" to terminate or "Enter" to continue:0 Out[19]: DH_Hole DH_East DH_North DH_RH DH_From DH_To Rock Mask 0 GEO00 1.659298e+06 715053.016841 2.0 0.0 12.0 sand test-geo 1 GEO00 1.659298e+06 715053.016841 2.0 12.0 60.0 NA test-geo
- build_geology(*, return_data=False, hole_elevation=0.0, **kwd)[source]#
Build manually the geology data of collected drilling area.
build_geology()collect the rocks or strata names collected during the drilling operations or well contructions. The collection of the information will build a geology dataset which can be used to Oasis Montaj software modeling. Below is an example of geology data set construction. This is some explanation of the prompt:well/hole ID: Is the name or ID of the rocks or strata collected in the area
coordinates (xlon, xlat): is the geographical coordinates where the drilling operation is performed. Expect projection is
ll. To enter the UTM coordinates, set the projection in the building object toutmlike:>>> DSDrill (projection='utm').build_geology (return_geology =True )
radius (m): Is the radius of the hole/well
depth: depth of the well/hole in meters.
layer thickness: The thickness of each strata in the whole. Note that when many thickness are supplied, it may correspond to each layer i.e. the number of thicknesses must equal to the number of layers. If not the case,
NAshould be used to indicate the missing layer/rock name in the geology dataset.mask/comments: Is any comments aboud the well/hole.
- Parameters:
return_data (bool, default=False,) – Return the geology dataset rather than object (
False) after entering the appropriate argumments. Note that evenTrue, the geology data set can be retrieved via the attributegeology_.hole_elevation (float, default=0,) – The elevation or the level of surface of the well/hole compared to the level of sea. Note that elevation must be negative value on the top of the air for layer/strat calculation.
- Returns:
self, geology dataset – Return object when
return_geology=Falseand DataFrame otherwise.- Return type:
DSDrillor pd.DataFrame.
Examples
>>> DSDrill ().build_geology (return_geology =True ) Enter the well/hole ID:GEOK4 Enter GEOK4 coordinates (xlon, ylat):10 15 Enter GEOK4 radius in meters [Optional]:12.2 Enter the GEOK4 depth in meters: 75 Enter each stratum thickness of GEOK4 [top-->bottom] in meters:10 20 11 Enter the layer/rock names of GEOK4 [top-->bottom]:granite gneiss Enter valuable comments about GEOK4 [Optional]:building test Tap exit|0 to terminate or enter to continue:0 Out[17]: DH_Hole DH_East DH_North ... DH_To Rock Mask 0 GEOK4 1.105412e+06 500000.0 ... 10.0 granite building test 1 GEOK4 1.105412e+06 500000.0 ... 30.0 gneiss building test 2 GEOK4 1.105412e+06 500000.0 ... 41.0 NA building test 3 GEOK4 1.105412e+06 500000.0 ... 75.0 NA building test
- build_geosamples(*, return_data=False, **kwd)[source]#
Build manually the geochemistry samples of area.
build_geosamples()collect the geochemistry samples in the survey area with their geographical coordinates locations. The name as well as the sample thickness and the radium of the holes can be from the prompt. The collection of the information will build a geosamples dataset which can be used to Oasis Montaj software modeling. Below is an examples of Outputted. This is some indication of the prompts:sample ID: Is the name or ID of the samples collected in the area
coordinates (xlon, xlat): is the geographical coordinates where the sampling is performed.
The radius (m): Is the radius of the hole did for collecting the sample.
samples thickness: Ask the thickness of the samples in the whole. Note that when many thickness are supplied, it means the same sample is collected at different depth. There are two kind of data to supply:
t-value: Compose only with the layer thickness values. For instance
t= "10 20 7 58"indicates four samples with thicknesses equals to 10, 20, 7 and 58 ( meters) respectively.tb-range: compose only with thickness range at each depth. For instance
t= "0-10 10-30 40-47 101-159". Note the character used to separate thickness range is'-'. Here, the top(roof) and bottom(wall) of the sample are 0 (top) and 10 (bottom), 10 and 30, 40 and 47 , and 101 and 159 for the same sample.Note that any mixed types is not acceptable and willraises error. To verify whether the expected samples values is acceptable or not, use the following
watex.utils.geotools.get_thick_from_range()orwatex.utils.geotools.get_thick_from_values()functions.
sample name: Is the name of samples collected refereing to the different depth. In principle, the number of samples thickness must equals to the number of samples. If not the case,
NAshould be used to indicate the missing samples in the geosamples dataset.mask/comments: Is any comments aboud the sample
- Parameters:
return_data (bool, default=False,) – Return the samples dataset rather than object (
False) after prompted the appropriate argumments. Note that evenTrue, the geosample data set can be retrieved via the attributesample_.- Returns:
self, geosample dataset – Return object when
return_data=Falseand DataFrame otherwise.- Return type:
DSDrillor pd.DataFrame.
Examples
>>> dr = DSDrill ().build_geosamples (return_samples =True ) Enter the sample ID:sx02 Enter SX02 coordinates (xlat, ylon):12 15 Enter SX02 radius in meters [Optional]:2.5 Enter the sample thickness of SX02 in meters:15 15 48 23 Enter the sample names of SX02:pup sup op Enter valuable comments about SX02 [Optional]:t-value Tap "exit|0" to terminate or "Enter" to continue: Enter the sample ID:sx05 Enter SX05 coordinates (xlat, ylon):15 56 Enter SX05 radius in meters [Optional]:2.3 Enter the sample thickness of SX05 in meters:12-17 26-36 40-57 Enter the sample names of SX05:benz op Enter valuable comments about SX05 [Optional]:t-range1 Tap "exit|0" to terminate or "Enter" to continue: Enter the sample ID:sx07 Enter SX07 coordinates (xlat, ylon):10 15 Enter SX07 radius in meters [Optional]:1.25 Enter the sample thickness of SX07 in meters:56-76 Enter the sample names of SX07:gru Enter valuable comments about SX07 [Optional]:t-range2 Tap "exit|0" to terminate or "Enter" to continue:0 >>> dr Out[8]: DH_Hole DH_East DH_North DH_RH DH_From DH_To Sample Mask 0 SX02 1.326554e+06 500000.000000 2.50 0.0 15.0 pup t-value 1 SX02 1.326554e+06 500000.000000 2.50 15.0 30.0 sup t-value 2 SX02 1.326554e+06 500000.000000 2.50 30.0 78.0 op t-value 3 SX02 1.326554e+06 500000.000000 2.50 78.0 101.0 NA t-value 4 SX05 1.658569e+06 392487.772324 2.30 12.0 17.0 benz t-range1 5 SX05 1.658569e+06 392487.772324 2.30 26.0 36.0 op t-range1 6 SX05 1.658569e+06 392487.772324 2.30 40.0 57.0 NA t-range1 7 SX07 1.105412e+06 500000.000000 1.25 56.0 76.0 gru t-range2
- code = ('DH_Hole', 'DH_East', 'DH_North', 'Mask', 'DH_RH', 'DH_From', 'DH_To', 'Rock', 'DH_Azimuth', 'DH_Top', 'DH_Bottom', 'DH_PlanDepth', 'DH_Decr', 'Sample', 'DH_Dip', 'Elevation', 'DH_RL')#
- fit(data=None, **fit_params)[source]#
Fit drill data to build
- Parameters:
data (pd.DataFrame or Path-like object.) – Data containing the drilling informations.
fit_params (dict,) – Keyword arguments passed to
watex.utils.to_numeric_dtypes()for data management.
- Returns:
self – Instanced object for chaining method.
- Return type:
Instanced object
Examples
>>> from watex.geology.drilling import Drill >>> csv_data ='data/drill/nbleDH.csv' >>> xlsx_data= 'data/drill/nbleDH.xlsx' >>> dr0 = Drill().fit(csv_data) >>> dr0.data_.head(2) DH_Hole__ID_ DH_East DH_North ... DH_Top DH_Bottom DH_PlanDepth 0 S01 477205.6935 2830978.218 ... 0 968.83 NaN 1 S02 477261.7258 2830944.879 ... 0 974.8945704 NaN >>> dr1 = Drill().fit(xlsx_data) >>> dr1.data_.head(2) DH_Hole (ID) DH_East ... sample03 sample04 0 S01 477205.6935 ... pup Boudin Axis 1 S02 477261.7258 ... pup pzs
- fit_structures(kind, keep_acronyms=Ellipsis, fill_value=None, inplace=Ellipsis)[source]#
Set the geology or geochemistry samples to fit the AGSO database structures.
- Parameters:
kind (str, { "geology", "samples"}) – Kind of structure to be fitted.
keep_acronym (bool, default=False,) – Use the acronym of the structural and geological database info to replace the full geological/structural name.
fill_value (str, optional) – If None, the undetermined structured are not replaced. They are kept in the data. However, if the fill_value is provided, the missing structure from data is replaced by the fill_value.
inplace (bool, default=False) – If
True, modifies the geology or samples dataset inplace and return None
- Returns:
data – Geology or Geochemistry fitted data. Data are modified in place if
Trueand returnNone.- Return type:
pd.DataFrame
Examples
>>> from watex.geology import DSDrill >>> dr = DSDrill() >>> dr.build_drillholes (kind='geology', return_data =True ) Enter the well/hole ID:GEO02 Enter GEO02 coordinates (x/lon, y/lat):12 26 Enter GEO02 radius in meters [Optional]:3.6 Enter the GEO02 depth in meters: 26 Enter each stratum thickness of GEO02 [top-->bottom] in meters:7 Enter the layer/rock names of GEO02 [top-->bottom]:limestone Enter valuable comments about GEO02 [Optional]:test Tap "exit|0" to terminate or "Enter" to continue: Enter the well/hole ID:GEO03 Enter GEO03 coordinates (x/lon, y/lat):12 15 Enter GEO03 radius in meters [Optional]:3.10 Enter the GEO03 depth in meters: 36 Enter each stratum thickness of GEO03 [top-->bottom] in meters:12 10 Enter the layer/rock names of GEO03 [top-->bottom]:sand tuff Enter valuable comments about GEO03 [Optional]:test2 Tap "exit|0" to terminate or "Enter" to continue:0 Out[1]: DH_Hole DH_East DH_North DH_RH DH_From DH_To Rock Mask 0 GEO02 2.879133e+06 199681.925199 3.6 0.0 7.0 limestone test1 1 GEO02 2.879133e+06 199681.925199 3.6 7.0 26.0 NA test1 2 GEO03 1.660514e+06 177349.038212 3.1 0.0 12.0 sand test2 3 GEO03 1.660514e+06 177349.038212 3.1 12.0 22.0 tuff test2 4 GEO03 1.660514e+06 177349.038212 3.1 22.0 36.0 NA test2 >>> dr.fit_structures('geology') Out[2]: DH_Hole DH_East DH_North ... DH_To Rock Mask 0 GEO02 2.879133e+06 199681.925199 ... 7.0 limestone test1 1 GEO02 2.879133e+06 199681.925199 ... 26.0 carbonate iron formation test1 2 GEO03 1.660514e+06 177349.038212 ... 12.0 sandstone test2 3 GEO03 1.660514e+06 177349.038212 ... 22.0 tuff test2 4 GEO03 1.660514e+06 177349.038212 ... 36.0 carbonate iron formation test2
- get_collar(data=None, reset_collar=False, **kws)[source]#
Get or set the collar data.
- Parameters:
data (str, pd.Dataframe) – Path-like object of dataframe containing the collar data
reset_collar (bool, defult=False,) – If collar is provided, resetting the collar data will replace the previous collar data in the original data.
kws (dict,) – Keyword arguments passed to
watex.utils.coreutils._is_readable()
- Returns:
self – Object instanced for method chaining
- Return type:
Instanced object
Examples
>>> from watex.geology.drilling import DSDrill >>> xlsx_data= 'data/drill/nbleDH.xlsx' >>> dr = DSDrill().fit(xlsx_data) >>> dr2 = dr.get_collar (dr.collar_, reset_collar= True ) >>> dr2.collar_ DH_Hole (ID) DH_East DH_North ... DH_PlanDepth DH_Decr Mask 0 S01 477205.6935 2830978.218 ... NaN NaN NaN 1 S02 477261.7258 2830944.879 ... NaN NaN NaN
>>> dr.holeid # id hole is autodetected if not given 'DH_Hole (ID)' >>> # retreive the holeID S01 >>> dr.collar.S01 {'DH_Hole (ID)': 'S01', 'DH_East': 477205.6935, 'DH_North': 2830978.218, 'DH_Dip': -90.0, 'Elevation ': 0.0, 'DH_Azimuth': 0.0, 'DH_Top': 0.0, 'DH_Bottom': 968.83, 'DH_PlanDepth': nan, 'DH_Decr': nan, 'Mask ': nan}
- get_geology(data=None, reset_geology=False, **kws)[source]#
Get the geological informations that composed each drilling.
- Parameters:
data (str, dataframe) – Path like object composed of layer thickness and geology
reset_geology (bool, default=False) – If
Trueit assumes that the datakws (dict,) – Keyword arguments passed to
watex.utils.coreutils._is_readable()
- Returns:
self – Object instanced for method chaining
- Return type:
Instanced object
Examples
>>> from watex.geology.drilling import DSDrill >>> xlsx_data= 'data/drill/nbleDH.xlsx' >>> dr = DSDrill().fit(xlsx_data) >>> dr.get_geology (dr.geology_, reset_geology=True ).geology_ DH_Hole Thick01 ... Rock03 Rock04 0 S01 0.200000 ... carbonate iron formation ROCK 1 S02 174.429396 ... GRT ROCK >>> dr.holeid # id hole is autodetected if not given Out[62]: 'DH_Hole' >>> # retreive the hole ID of S01 drilling. >>> dr.geology.S01 {'DH_Hole': 'S01', 'Thick01': 0.2, 'Thick02': 98.62776918, 'Thick03': 204.7500461, 'Thick04': 420.0266651, 'Rock01': 'clast supported breccia', 'Rock02': 'sulphide-rich material', 'Rock03': 'carbonate iron formation', 'Rock04': 'ROCK'}
- get_geosamples(data=None, reset_samples=False, **kws)[source]#
Get or set the geochemistry samples data.
- Parameters:
data (str, pd.Dataframe) – Path-like object of dataframe containing the geochemistry sample data
reset_samples (bool, default=False,) – If geochemistry samples is provided, resetting the samples data will replace the previous samples data in the original data.
kws (dict,) – Keyword arguments passed to
watex.utils.coreutils._is_readable()
- Returns:
self – Object instanced for method chaining
- Return type:
Instanced object
Examples
>>> from watex.geology.drilling import DSDrill >>> xlsx_data= 'data/drill/nbleDH.xlsx' >>> dr = DSDrill().fit(xlsx_data) >>> dr.get_geosamples (dr.samples_, reset_samples= True ).samples_ DH_Hole Thick01 Thick02 ... sample02 sample03 sample04 0 S01 10.0 98.627769 ... prt pup Boudin Axis 1 S02 17.4 313.904388 ... Banding/gneissosity pup pzs >>> dr.holeid # id hole is autodetected if not given 'DH_Hole' >>> # retreive the holeID geosamples S02 >>> dr.samples.S02 {'DH_Hole': 'S02', 'Thick01': 17.4, 'Thick02': 313.9043882, 'Thick03': 400.12, 'Thick04': 515.3, 'sample01': 'pup', 'sample02': 'Banding/gneissosity', 'sample03': 'pup', 'sample04': 'pzs'}
- get_properties(kind)[source]#
Get a specific drillhole properties.
- Parameters:
kind (str, {"collar", "geology", "samples"}) – Kind of drillhole properties to fetch.
- Returns:
properties – Tuple of properties
- Return type:
Tuple
Examples
>>> from watex.geology import DSDrill >>> DSDrill ().get_properties (kind='geology') ('DH_Hole', 'DH_East', 'DH_North', 'DH_RH', 'DH_From', 'DH_To', 'Rock', 'Mask')
- property inspect#
Inspect object whether is fitted or not
- out(kind, fname=None, format='.xlsx', savepath=None, **outkws)[source]#
Export the drillhole.
- Parameters:
kind (str, {"geology", "collar", "samples", "*", "data"}) –
- Kind of data to export. If
"*", the geology, collar and samples are exported in single excel sheets or csv formats if format is set to
.xlsxor.csvrespectively.- fname: str,
Full path to filename. If fname is None, the filename used the kind name.
- Kind of data to export. If
format (str, default=".xlsx") – Extension to export the file. Note that if the filename fname includes the file extension, it should be used.
savepath (str, optional) – Path to locate the files.
Outkws (dict,) – Keywords arguments passed to other pandas exportable readable formats.
Examples
>>> from watex.geology import DSDrill >>> from watex.datasets import load_nlogs >>> ndata = load_nlogs(samples =7 , as_frame =True) >>> dr =DSDrill(projection='utm').fit(ndata) >>> dr.out( kind="data") >>> dr.out(fname = 'test_data.csv', kind ="data")
- set_drillholes(kind, properties=None, return_data=False)[source]#
Transform the data and fit to the corresponding drillholes.
kind is used to specify the type of drillhole to build. The DH_ used to prefix the drillhole properties can be omitted when specifying the properties.
- Parameters:
kind (str, {"collar", "geology", "samples"}) – Kind of drillhole to build.
properties (dict,) – A mapper that uses to replace the column names from data to the values of the drillholes. If properties is not specified drillhole data returns NaN columns.
return_data (bool, default=False) – Out the drillhole data. Otherwise returns the drillhole object
DSDrill.
- Returns:
self, data –
DSDrillObject instanced or drillholes data set rebuild. Unmatch properties names should be replaced by NaN- Return type:
Object instanced and pd.DataFrame
Examples
>>> import watex as wx >>> from watex.geology import DSDrill >>> ndata = wx.fetch_data ('nlogs', samples =12, as_frame = True ) >>> dr = DSDrill ().fit(ndata) >>> dr.data_.head(2) Out[26]: hole_id uniform_number ... filter_pipe_diameter water_inflow_in_m3_d 0 B0092 1.133960e+16 ... 0.120 15.249 1 B0093 1.133110e+16 ... 0.125 114.474 [2 rows x 25 columns] >>> # try list data column names and find the suitable columns that >>> # could fit the drillholes properies. >>> dr.data_.columns Out[27]: Index(['hole_id', 'uniform_number', 'original_number', 'lon', 'lat', 'longitude', 'latitude', 'east', 'north', 'easting', 'northing', 'coordinate_system', 'elevation', 'final_hole_depth', 'quaternary_thickness', 'aquifer_thickness', 'top_section_depth', 'bottom_section_depth', 'groundwater_type', 'static_water_level', 'drawdown', 'water_inflow', 'unit_water_inflow', 'filter_pipe_diameter', 'water_inflow_in_m3_d'], dtype='object') >>> To get properties, one needs to call get properties to have an idea >>> # before setting the columns to fit the properties as >>> DSDrill ().get_properties (kind='collar') Out[29]: ('DH_Hole', 'DH_East', 'DH_North', 'DH_RH', 'DH_Top', 'DH_Bottom', 'DH_Dip', 'Elevation', 'DH_Azimuth', 'DH_PlanDepth', 'DH_Decr', 'Mask') >>> # Then we can match each data columns to the properties as: >>> properties = {"hole_id": "DH_Hole", "easting": 'DH_East', "northing": 'DH_North', "top_section_depth": "DH_Top", "bottom_section_depth": "DH_Bottom", "final_hole_depth": 'DH_PlanDepth'} >>> dr.set_drillholes (kind='collar', properties = properties) >>> dr.collar_ Out[30]: DH_Hole DH_East DH_North ... DH_PlanDepth DH_Decr Mask 0 B0092 2509081.067 19774192.36 ... 200.14 NaN NaN 1 B0093 2576045.247 19757910.23 ... 50.00 NaN NaN 2 B0094 2579349.264 19763695.25 ... 47.00 NaN NaN 3 B0095 2568832.229 19760491.25 ... 59.40 NaN NaN 4 B0096 2566131.227 19765367.27 ... 42.00 NaN NaN 5 B0097 2568517.240 19770396.28 ... 50.70 NaN NaN 6 B0098 2583506.276 19763770.24 ... 50.00 NaN NaN 7 B0099 2576326.263 19770189.27 ... 50.00 NaN NaN 8 B0101 2567480.246 19777199.30 ... 60.00 NaN NaN 9 B0102 2583420.292 19775988.28 ... 50.00 NaN NaN 10 B0103 2577207.276 19778177.29 ... 60.10 NaN NaN 11 B0106 2519089.079 19758966.30 ... 48.10 NaN NaN [12 rows x 12 columns]