# -*- coding: utf-8 -*-
# Licence:BSD 3-Clause
# Author: LKouadio <etanoyau@gmail.com>
# Created date: Fri Apr 15 10:46:56 2022
"""
:code:`watex` property objects. It is composed of base classes that are inherited
by methods implemented throughout the package. It also inferred properties to
data objects.
.. _WATex: https://github.com/WEgeophysics/watex/
.. |ERP| replace:: Electrical resistivity profiling
.. |VES| replace:: Vertical Electrical Sounding
.. _interpol_imshow: https://matplotlib.org/stable/gallery/images_contours_and_fields/interpolation_methods.html
"""
# import warnings
from __future__ import annotations
import os
from abc import (
ABC,
abstractmethod,
)
import pandas as pd
from .decorators import refAppender
from ._docstring import refglossary
from .exceptions import (
FileHandlingError,
EDIError
)
__all__ = [
"Water",
"BasePlot",
'P',
'BagoueNotes',
"ElectricalMethods",
"IsEdi",
"Config",
"UTM_DESIGNATOR",
"_EDI",
"_ZRP_COMPS",
"_TIP_COMPS",
"Software",
"Copyright",
"References",
"Person",
]
UTM_DESIGNATOR ={
'X':[72,84],
'W':[64,72],
'V':[56,64],
'U':[48,56],
'T':[40,48],
'S':[32,40],
'R':[24,32],
'Q':[16,24],
'P':[8,16],
'N':[0,8],
'M':[-8,0],
'L':[-16, 8],
'K':[-24,-16],
'J':[-32,-24],
'H':[-40,-32],
'G':[-48,-40],
'F':[-56,-48],
'E':[-64, -56],
'D':[-72,-64],
'C':[-80,-72],
'Z':[-80,84]
}
_EDI =[
#Head=Infos-Frequency-Rhorot
# Zrot and end blocks
'>HEAD','>INFO',
#Definitions Measurments Blocks
'>=DEFINEMEAS',
'>=MTSECT',
'>FREQ ORDER=INC',
'>ZROT',
'>RHOROT',
'>!Comment',
'>FREQ',
'>HMEAS',
'>EMEAS',
#Apparents Resistivities
#and Phase Blocks
'>RHOXY','>PHSXY',
'>RHOXY.VAR','>PHSXY.VAR',
'>RHOXY.ERR','>PHSXY.ERR',
'>RHOXY.FIT','>PHSXY.FIT',
'>RHOYX','>PHSYX',
'>RHOYX.VAR','>PHSYX.VAR',
'>RHOYX.ERR','>PHSYX.ERR',
'>RHOYX.FIT','>PHSYX.FIT',
'>RHOXX','>PHSXX',
'>RHOXX.VAR','>PHSXX.VAR',
'>RHOXX.ERR','>PHSXX.ERR',
'>RHOXX.FIT','>PHSXX.FIT',
'>RHOYY','>PHSYY',
'>RHOYY.VAR','>PHSYY.VAR',
'>RHOYY.ERR','>PHSYY.ERR',
'>RHOYY.FIT','>PHSYY.FIT',
'>FRHOXY','>FPHSXY',
'>FRHOXY.VAR','>FPHSXY.VAR',
'>FRHOXY.ERR','>FPHSXY.ERR',
'>FRHOXY.FIT','>FPHSXY.FIT',
'>FRHOXX','>FPHSXX',
'>FRHOXX.VAR','>FPHSXX.VAR',
'>FRHOXX.ERR','>FPHSXX.ERR',
'>FRHOXX.FIT','>FPHSXX.FIT',
#Time series-Sepctra
#and EM/OTHERSECT
'>TSERIESSECT', '>TSERIES',
'>=SPECTRASECT', '>=EMAPSECT',
'>=OTHERSECT',
#Impedance Data Blocks
'>ZXYR','>ZXYI',
'>ZXY.VAR', '>ZXYR.VAR',
'>ZXYI.VAR', '>ZXY.COV',
'>ZYXR','>ZYXI',
'>ZYX.VAR', '>ZYXR.VAR',
'>ZYXI.VAR', '>ZYX.COV',
'>ZYYR','>ZYYI',
'>ZYY.VAR', '>ZYYR.VAR',
'>ZYYI.VAR', '>ZYY.COV',
'>ZXXR', '>ZXXI',
'>ZXXR.VAR','>ZXXI.VAR',
'>ZXX.VAR','>ZXX.COV',
'>FZXXR','>FZXXI',
'>FZXYR','>FZXYI',
#Continuous 1D inversion
'>RES1DXX', '>DEP1DXX',
'>RES1DXY', '>DEP1DXY',
'>RES1DYX', '>DEP1DYX',
'>RES1DYY', '>DEP1DYY',
'>FRES1DXX', '>FDEP1DXX',
'>FRES1DXY', '>FDEP1DXY',
# Coherency and
#Signal Data Blocks
'>COH','>EPREDCOH',
'>HPREDCOH','>SIGAMP',
'>SIGNOISE',
#Tipper Data blocks
'>TIPMAG','>TIPPHS',
'TIPMAG.ERR', '>TIPMAG.FIT',
'>TIPPHS.FIT', '>TXR.EXP',
'>TXI.EXP', '>TXVAR.EXP',
'>TYR.EXP','>TYI.EXP',
'>TYVAR.EXP',
# Strike, Skew, and
# Ellipticity Data Blocks
'>ZSTRIKE','>ZSKEW',
'>ZELLIP', '>TSTRIKE',
'>TSKEW','>TELLIP',
#Spatial filter blocks
'>FILWIDTH','>FILANGLE',
'>EQUIVLEN' , '>END'
]
#
_ZRP_COMPS =[
#z
[
['zxxr', 'zxxi', 'zxx.var'],
['zxyr', 'zxyi', 'zxy.var'],
['zyxr', 'zyxi', 'zyx.var'],
['zyyr', 'zyyi', 'zyy.var']
],
#Rho
[
['rhoxx', 'rhoxx.var','rhoxx.err', 'rhoxx.fit'],
['rhoxy','rhoxy.var','rhoxy.err', 'rhoxy.fit']
],
[
['phxx','phsxx.var', 'phsxx.err', 'phsxx.fit'],
['phxy','phsxy.var', 'phsxy.err', 'phsxy.fit']
],
# filtered
[
['frhoxx','frhoxx.var','frhoxx.err', 'frhoxx.fit'],
['frhoxy','frhoxy.var', 'frhoxy.err', 'frhoxy.fit']
],
[
['fphsxx','fphsxx.var', 'fphsxx.err', 'fphsxx.fit'],
['fphsxy','fphsxy.var', 'fphsxy.err', 'fphsxy.fit']
],
]
_TIP_COMPS =[
['txr.exp', 'txi.exp', 'txvar.exp'],
['tyr.exp', 'tyi.exp', 'tyvar.exp']
]
[docs]
@refAppender(refglossary.__doc__)
class Water (ABC):
r""" Should be a SuperClass for methods classes which deals with water
properties and components.
Instanciate the class shoud raise an error.
Water (H2O) is a polar inorganic compound that is at room temperature a
tasteless and odorless liquid, which is nearly colorless apart from an
inherent hint of blue. It is by far the most studied chemical compound
and is described as the "universal solvent"and the "solvent of life".
It is the most abundant substance on the surface of Earth and the only
common substance to exist as a solid, liquid, and gas on Earth's surface.
It is also the third most abundant molecule in the universe
(behind molecular hydrogen and carbon monoxide).
The Base class initialize arguments for different methods such as the
|ERP| and for |VES|. The `Water` should set the attributes and check
whether attributes are suitable for what the specific class expects to.
Hold some properties informations:
================= =======================================================
Property Description
================= =======================================================
state official names for the chemical compound r"$H_2O$". It
can be a matter of ``solid``, ``ice``, ``gaseous``,
``water vapor`` or ``steam``. The *default* is ``None``.
taste water from ordinary sources, including bottled mineral
water, usually has many dissolved substances, that may
give it varying tastes and odors. Humans and other
animals have developed senses that enable them to
evaluate the potability of water in order to avoid
water that is too ``salty`` or ``putrid``.
The *default* is ``potable``.
odor Pure water is usually described as tasteless and odorless,
although humans have specific sensors that can feel
the presence of water in their mouths,and frogs are known
to be able to smell it. The *default* is ``pure``.
color The color can be easily observed in a glass of tap-water
placed against a pure white background, in daylight.
The **default** is ``pure white background``.
appearance Pure water is visibly blue due to absorption of light
in the region ca. 600 nm – 800 nm. The *default* is
``visible``.
density Water differs from most liquids in that it becomes
less dense as it freezes. In 1 atm pressure, it reaches
its maximum density of ``1.000 kg/m3`` (62.43 lb/cu ft)
at 3.98 °C (39.16 °F). The *default* units and values
are ``kg/m3``and ``1.``
magnetism Water is a diamagnetic material. Though interaction
is weak, with superconducting magnets it can attain a
notable interaction. the *default* value is
:math:`-0.91 \chi m`". Note that the magnetism
succeptibily has no unit.
capacity stands for `heat capacity`. In thermodynamics, the
specific heat capacity (symbol cp) of a substance is the
heat capacity of a sample of the substance divided by
the mass of the sample. Water has a very high specific
heat capacity of 4184 J/(kg·K) at 20 °C
(4182 J/(kg·K) at 25 °C).The *default* is is ``4182 ``
vaporization stands for `heat of vaporization`. Indeed, the enthalpy
of vaporization (symbol :math:`\delta H_{vap}`), also
known as the (latent) heat of vaporization or heat of
evaporation, is the amount of energy (enthalpy) that
must be added to a liquid substance to transform a
quantity of that substance into a gas. Water has a high
heat of vaporization i.e. 40.65 kJ/mol or 2257 kJ/kg
at the normal boiling point), both of which are a
result of the extensive hydrogen bonding between its
molecules. The *default* is ``2257 kJ/kg``.
fusion stands for `enthalpy of fusion` more commonly known as
latent heat of water is 333.55 kJ/kg at 0 °C. The
*default* is ``33.55``.
miscibility Water is miscible with many liquids, including ethanol
in all proportions. Water and most oils are immiscible
usually forming layers according to increasing density
from the top. *default* is ``True``.
condensation As a gas, water vapor is completely miscible with air so
the vapor's partial pressure is 2% of atmospheric
pressure and the air is cooled from 25 °C, starting at
about 22 °C, water will start to condense, defining the
dew point, and creating fog or dew. The *default* is the
degree of condensation set to ``22°C``.
pressure stands for `vapour pressure` of water. It is the pressure
exerted by molecules of water vapor in gaseous form
i.e. whether pure or in a mixture with other gases such
as air. The vapor pressure is given as a list from the
temperature T, 0°C (0.6113kPa) to 100°C(101.3200kPa).
*default* is ``(0.611, ..., 101.32)``.
compressibility The compressibility of water is a function of pressure
and temperature. At 0 °C, at the limit of zero pressure,
the compressibility is ``5.1x10^−10 P^{a^−1}``.
The *default* value is the value at 0 °C.
triple stands for `triple point`. The temperature and pressure
at which ordinary solid, liquid, and gaseous water
coexist in equilibrium is a triple point of water. The
`triple point` are set to (.001°C,611.657 Pa) and
(100 , 101.325kPa) for feezing (0°C) and boiling point
(100°C) points. In addition, the `triple point` can be
set as ``(20. , 101.325 kPa)`` for 20°C. By *default*,
the `triple point` solid/liquid/vapour is set to
``(.001, 611.657 Pa )``.
melting stands for `melting point`. Water can remain in a fluid
state down to its homogeneous nucleation point of about
231 K (−42 °C; −44 °F). The melting point of ordinary
hexagonal ice falls slightly under moderately high
pressures, by 0.0073 °C (0.0131 °F)/atm[h] or about
``0.5 °C`` (0.90 °F)/70 atm considered as the
*default* value.
conductivity In pure water, sensitive equipment can detect a very
slight electrical conductivity of 0.05501 ± 0.0001
μS/cm at 25.00 °C. *default* is ``.05501``.
polarity An important feature of water is its polar nature. The
structure has a bent molecular geometry for the two
hydrogens from the oxygen vertex. The *default* is
``bent molecular geometry`` or ``angular or V-shaped``.
Other possibility is ``covalent bonds ``
``VSEPR theory`` for Valence Shell Electron Repulsion.
cohesion stands for the collective action of hydrogen bonds
between water molecules. The *default* is ``coherent``
for the water molecules staying close to each other.
In addition, the `cohesion` refers to the tendency of
similar or identical particles/surfaces to cling to
one another.
adhesion stands for the tendency of dissimilar particles or
surfaces to cling to one another. It can be
``chemical adhesion``, ``dispersive adhesion``,
``diffusive adhesion`` and ``disambiguation``.
The *default* is ``disambiguation``.
tension stands for the tendency of liquid surfaces at rest to
shrink into the minimum surface area possible. Water
has an unusually high surface tension of 71.99 mN/m
at 25 °C[63] which is caused by the strength of the
hydrogen bonding between water molecules. This allows
insects to walk on water. The *default* value is to
``71.99 mN/m at 25 °C``.
action stands for `Capillary action`. Water has strong cohesive
and adhesive forces, it exhibits capillary action.
Strong cohesion from hydrogen bonding and adhesion
allows trees to transport water more than 100 m upward.
So the *default* value is set to ``100.``meters.
issolvent Water is an excellent solvent due to its high dielectric
constant. Substances that mix well and dissolve in water
are known as hydrophilic ("water-loving") substances,
while those that do not mix well with water are known
as hydrophobic ("water-fearing") substances.
tunnelling stands for `quantum tunneling`. It is a quantum
mechanical phenomenon whereby a wavefunction can
propagate through a potential barrier. It can be
``monomers`` for the motions which destroy and
regenerate the weak hydrogen bond by internal rotations,
or ``hexamer`` involving the concerted breaking of two
hydrogen bond. The *default* is ``hexamer`` discovered
on 18 March 2016.
reaction stands for `acide-base reactions`. Water is
``amphoteric`` i.e. it has the ability to act as either
an acid or a base in chemical reactions.
ionization In liquid water there is some self-ionization giving
``hydronium`` ions and ``hydroxide`` ions. *default* is
``hydroxide``.
earthmass stands for the earth mass ration in "ppm" unit. Water
is the most abundant substance on Earth and also the
third most abundant molecule in the universe after the
:math:`H_2 \quad \text{and} \quad CO` . The *default*
value is ``0.23``ppm of the earth's mass.
occurence stands for the abundant molecule in the Earth. Water
represents ``97.39%`` of the global water volume of
1.38×109 km3 is found in the oceans considered as the
*default* value.
pH stands for `Potential of Hydrogens`. It also shows the
acidity in nature of water. For instance the "rain" is
generally mildly acidic, with a pH between 5.2 and 5.8
if not having any acid stronger than carbon dioxide. At
neutral pH, the concentration of the hydroxide ion
(:math:`OH^{-}`) equals that of the (solvated) hydrogen
ion(:math:`H^{+}`), with a value close to ``10^−7 mol L^−1``
at 25 °C. The *default* is ``7.`` or ``neutral`` or the
name of any substance `pH` close to.
nommenclature The accepted IUPAC name of water is ``oxidane`` or
simply ``water``. ``Oxidane`` is only intended to be
used as the name of the mononuclear parent hydride used
for naming derivatives of water by substituent
nomenclature. The *default* name is ``oxidane``.
================= =======================================================
Notes
----------
Water (chemical formula H2O) is an inorganic, transparent, tasteless,
odorless, and nearly colorless chemical substance, which is the main
constituent of Earth's hydrosphere and the fluids of all known living
organisms (in which it acts as a solvent). It is vital for all known
forms of life, even though it provides neither food, energy, nor organic
micronutrients. Its chemical formula, H2O, indicates that each of its
molecules contains one oxygen and two hydrogen atoms, connected by covalent
bonds. The hydrogen atoms are attached to the oxygen atom at an angle of
104.45°. "Water" is the name of the liquid state of H2O at standard
temperature and pressure.
"""
@abstractmethod
def __init__(self,
state: str = None,
taste: str = 'potable',
odor: int | str = 'pure',
appearance: str = 'visible',
color: str = 'pure white background',
capacity: float = 4184. ,
vaporization: float = 2257.,
fusion: float = 33.55,
density: float = 1. ,
magnetism: float = -.91,
miscibility: bool =True ,
condensation: float = 22,
pressure: tuple = (.6113, ..., 101.32),
compressibility: float =5.1e-10,
triple: tuple = (.001, 611.657 ),
conductivity: float = .05501,
melting: float = .5,
polarity: str ='bent molecular geometry ',
cohesion: str = 'coherent',
adhesion: str ='disambiguation',
tension: float = 71.99,
action: float = 1.e2 ,
issolvent: bool =True,
reaction:str = 'amphoteric', #
ionisation:str = "hydroxide",
tunneling: str = 'hexamer' ,
nommenclature: str ='oxidane',
earthmass: float =.23 ,
occurence: float = .9739,
pH: float| str = 7.,
):
self.state=state
self.taste=taste
self.odor=odor
self.appearance=appearance
self.color=color
self.capacity=capacity
self.vaporization=vaporization
self.fusion=fusion
self.density=density
self.magnetism=magnetism
self.miscibility=miscibility
self.condensation=condensation
self.pressure=pressure,
self.compressibility=compressibility
self.triple=triple
self.conductivity=conductivity
self.melting=melting
self.polarity=polarity
self.cohesion=cohesion
self.adhesion=adhesion
self.tension=tension
self.action=action
self.issolvent=issolvent
self.reaction=reaction
self.ionisation=ionisation
self.tunneling=tunneling
self.nommenclature=nommenclature
self.earthmass=earthmass
self.occurence=occurence
self.pH=pH
[docs]
class BasePlot(ABC):
r""" Base class deals with Machine learning and conventional Plots.
The `BasePlot` can not be instanciated. It is build on the top of other
plotting classes and its attributes are used for external plots.
Hold others optional informations:
================== =======================================================
Property Description
================== =======================================================
fig_dpi dots-per-inch resolution of the figure
*default* is 300
fig_num number of the figure instance. *default* is ``1``
fig_aspect ['equal'| 'auto'] or float, figure aspect. Can be
rcParams["image.aspect"]. *default* is ``auto``.
fig_size size of figure in inches (width, height)
*default* is [5, 5]
savefig savefigure's name, *default* is ``None``
fig_orientation figure orientation. *default* is ``landscape``
fig_title figure title. *default* is ``None``
fs size of font of axis tick labels, axis labels are
fs+2. *default* is 6
ls [ '-' | '.' | ':' ] line style of mesh lines
*default* is '-'
lc line color of the plot, *default* is ``k``
lw line weight of the plot, *default* is ``1.5``
alpha transparency number, *default* is ``0.5``
font_weight weight of the font , *default* is ``bold``.
ms size of marker in points. *default* is 5
marker style of marker in points. *default* is ``o``.
marker_facecolor facecolor of the marker. *default* is ``yellow``
marker_edgecolor edgecolor of the marker. *default* is ``cyan``.
marker_edgewidth width of the marker. *default* is ``3``.
xminorticks minortick according to x-axis size and *default* is 1.
yminorticks minortick according to y-axis size and *default* is 1.
font_size size of font in inches (width, height)
*default* is 3.
font_style style of font. *default* is ``italic``
bins histograms element separation between two bar.
*default* is ``10``.
xlim limit of x-axis in plot. *default* is None
ylim limit of y-axis in plot. *default* is None
xlabel label name of x-axis in plot. *default* is None
ylabel label name of y-axis in plot. *default* is None
rotate_xlabel angle to rotate `xlabel` in plot. *default* is None
rotate_ylabel angle to rotate `ylabel` in plot. *default* is None
leg_kws keyword arguments of legend. *default* is empty dict.
plt_kws keyword arguments of plot. *default* is empty dict
plt_style keyword argument of 2d style. *default* is ``pcolormesh``
plt_shading keyword argument of Axes pycolormesh shading. It can be
['flat'|'nearest'|'gouraud'|'auto'].*default* is
'auto'
imshow_interp ['bicubic'|'nearest'|'bilinear'|'quadractic' ] kind of
interpolation for 'imshow' plot. Click `interpol_imshow`_
to get furher details about the interpolation method.
*default* is ``None``.
rs [ '-' | '.' | ':' ] line style of `Recall` metric
*default* is '--'
ps [ '-' | '.' | ':' ] line style of `Precision `metric
*default* is '-'
rc line color of `Recall` metric *default* is ``(.6,.6,.6)``
pc line color of `Precision` metric *default* is ``k``
s size of items in scattering plots. default is ``fs*40.``
cmap matplotlib colormap. *default* is `jet_r`
gls [ '-' | '.' | ':' ] line style of grid
*default* is '--'.
glc line color of the grid plot, *default* is ``k``
glw line weight of the grid plot, *default* is ``2``
galpha transparency number of grid, *default* is ``0.5``
gaxis axis to plot grid.*default* is ``'both'``
gwhich type of grid to plot. *default* is ``major``
tp_axis axis to apply ticks params. default is ``both``
tp_labelsize labelsize of ticks params. *default* is ``italic``
tp_bottom position at bottom of ticks params. *default*
is ``True``.
tp_top position at the top of ticks params. *default*
is ``True``.
tp_labelbottom see label on the bottom of the ticks. *default*
is ``False``
tp_labeltop see the label on the top of ticks. *default* is ``True``
cb_orientation orientation of the colorbar. *default* is ``vertical``
cb_aspect aspect of the colorbar. *default* is 20.
cb_shrink shrink size of the colorbar. *default* is ``1.0``
cb_pad pad of the colorbar of plot. *default* is ``.05``
cb_anchor anchor of the colorbar. *default* is ``(0.0, 0.5)``
cb_panchor proportionality anchor of the colorbar. *default* is
`` (1.0, 0.5)``.
cb_label label of the colorbar. *default* is ``None``.
cb_spacing spacing of the colorbar. *default* is ``uniform``
cb_drawedges draw edges inside of the colorbar. *default* is ``False``
cb_format format of the colorbar values. *default* is ``None``.
sns_orient seaborn fig orientation. *default* is ``v`` which refer
to vertical
sns_style seaborn style
sns_palette seaborn palette
sns_height seaborn height of figure. *default* is ``4.``.
sns_aspect seaborn aspect of the figure. *default* is ``.7``
sns_theme_kws seaborn keywords theme arguments. default is ``{
'style':4., 'palette':.7}``
verbose control the verbosity. Higher value, more messages.
*default* is ``0``.
================== =======================================================
"""
@abstractmethod
def __init__(self,
savefig: str = None,
fig_num: int = 1,
fig_size: tuple = (12, 8),
fig_dpi:int = 300,
fig_legend: str = None,
fig_orientation: str ='landscape',
fig_title:str = None,
fig_aspect:str='auto',
font_size: float =3.,
font_style: str ='italic',
font_weight: str = 'bold',
fs: float = 5.,
ms: float =3.,
marker: str = 'o',
markerfacecolor: str ='yellow',
markeredgecolor: str = 'cyan',
markeredgewidth: float = 3.,
lc: str = 'k',
ls: str = '-',
lw: float = 1.,
alpha: float = .5,
bins: int = 10,
xlim: list = None,
ylim: list= None,
xminorticks: int=1,
yminorticks: int =1,
xlabel: str = None,
ylabel: str = None,
rotate_xlabel: int = None,
rotate_ylabel: int =None ,
leg_kws: dict = dict(),
plt_kws: dict = dict(),
plt_style:str="pcolormesh",
plt_shading: str="auto",
imshow_interp:str =None,
s: float= 40.,
cmap:str='jet_r',
show_grid: bool = False,
galpha: float = .5,
gaxis: str = 'both',
gc: str = 'k',
gls: str = '--',
glw: float = 2.,
gwhich: str = 'major',
tp_axis: str = 'both',
tp_labelsize: float = 3.,
tp_bottom: bool =True,
tp_top: bool = True,
tp_labelbottom: bool = False,
tp_labeltop: bool = True,
cb_orientation: str = 'vertical',
cb_aspect: float = 20.,
cb_shrink: float = 1.,
cb_pad: float =.05,
cb_anchor: tuple = (0., .5),
cb_panchor: tuple= (1., .5),
cb_label: str = None,
cb_spacing: str = 'uniform' ,
cb_drawedges: bool = False,
cb_format: float = None ,
sns_orient: str ='v',
sns_style: str = None,
sns_palette: str= None,
sns_height: float=4. ,
sns_aspect:float =.7,
sns_theme_kws: dict = None,
verbose: int=0,
):
self.savefig=savefig
self.fig_num=fig_num
self.fig_size=fig_size
self.fig_dpi=fig_dpi
self.fig_legend=fig_legend
self.fig_orientation=fig_orientation
self.fig_title=fig_title
self.fig_aspect=fig_aspect
self.font_size=font_size
self.font_style=font_style
self.font_weight=font_weight
self.fs=fs
self.ms=ms
self.marker=marker
self.marker_facecolor=markerfacecolor
self.marker_edgecolor=markeredgecolor
self.marker_edgewidth=markeredgewidth
self.lc=lc
self.ls=ls
self.lw=lw
self.alpha=alpha
self.bins=bins
self.xlim=xlim
self.ylim=ylim
self.x_minorticks=xminorticks
self.y_minorticks=yminorticks
self.xlabel=xlabel
self.ylabel=ylabel
self.rotate_xlabel=rotate_xlabel
self.rotate_ylabel=rotate_ylabel
self.leg_kws=leg_kws
self.plt_kws=plt_kws
self.plt_style=plt_style
self.plt_shading=plt_shading
self.imshow_interp=imshow_interp
self.s=s
self.cmap=cmap
self.show_grid=show_grid
self.galpha=galpha
self.gaxis=gaxis
self.gc=gc
self.gls=gls
self.glw=glw
self.gwhich=gwhich
self.tp_axis=tp_axis
self.tp_labelsize=tp_labelsize
self.tp_bottom=tp_bottom
self.tp_top=tp_top
self.tp_labelbottom=tp_labelbottom
self.tp_labeltop=tp_labeltop
self.cb_orientation=cb_orientation
self.cb_aspect=cb_aspect
self.cb_shrink=cb_shrink
self.cb_pad=cb_pad
self.cb_anchor=cb_anchor
self.cb_panchor=cb_panchor
self.cb_label=cb_label
self.cb_spacing=cb_spacing
self.cb_drawedges=cb_drawedges
self.cb_format=cb_format
self.sns_orient=sns_orient
self.sns_style=sns_style
self.sns_palette=sns_palette
self.sns_height=sns_height
self.sns_aspect=sns_aspect
self.verbose=verbose
self.sns_theme_kws=sns_theme_kws or {'style':self.sns_style,
'palette':self.sns_palette,
}
self.cb_props = {
pname.replace('cb_', '') : pvalues
for pname, pvalues in self.__dict__.items()
if pname.startswith('cb_')
}
[docs]
class ElectricalMethods (ABC) :
""" Base class of geophysical electrical methods
The electrical geophysical methods are used to determine the electrical
resistivity of the earth's subsurface. Thus, electrical methods are
employed for those applications in which a knowledge of resistivity
or the resistivity distribution will solve or shed light on the problem
at hand. The resolution, depth, and areal extent of investigation are
functions of the particular electrical method employed. Once resistivity
data have been acquired, the resistivity distribution of the subsurface
can be interpreted in terms of soil characteristics and/or rock type and
geological structure. Resistivity data are usually integrated with other
geophysical results and with surface and subsurface geological data to
arrive at an interpretation. Get more infos by consulting this
`link <https://wiki.aapg.org/Electrical_methods>`_ .
The :class:`watex.methods.electrical.ElectricalMethods` compose the base
class of all the geophysical methods that images the underground using
the resistivity values. Is another Base class of :mod:`~.methods.electrical`
especially the :class:`~.methods.electrical.ResistivityProfiling` and
:class:`~.methods.electrical.VerticalSounding`. It is composed of the
details of geolocalisation of the survey area and the array configuration.
Holds on others optionals infos in ``kws`` arguments:
====================== ============== ===================================
Attributes Type Description
====================== ============== ===================================
AB float, array Distance of the current electrodes
in meters. `A` and `B` are used
as the first and second current
electrodes by convention. Note that
`AB` is considered as an array of
depth measurement when using the
vertical electrical sounding |VES|
method i.e. AB/2 half-space. Default
is ``200``meters.
MN float, array Distance of the current electrodes
in meters. `M` and `N` are used as
the first and second potential
electrodes by convention. Note that
`MN` is considered as an array of
potential electrode spacing when
using the collecting data using the
vertical electrical sounding |VES|
method i.e MN/2 halfspace. Default
is ``20.``meters.
arrangement str Type of dipoles `AB` and `MN`
arrangememts. Can be *schlumberger*
*Wenner- alpha / wenner beta*,
*Gradient rectangular* or *dipole-
dipole*. Default is *schlumberger*.
area str The name of the survey location or
the exploration area.
fromlog10 bool Set to ``True`` if the given
resistivities values are collected
on base 10 logarithm.
utm_zone str string (##N or ##S). utm zone in
the form of number and North or South
hemisphere, 10S or 03N.
datum str well known datum ex. WGS84, NAD27,
etc.
projection str projected point in lat and lon in
Datum `latlon`, as decimal degrees
or 'UTM'.
epsg int epsg number defining projection (see
http://spatialreference.org/ref/
for moreinfo). Overrides utm_zone
if both are provided.
====================== ============== ===================================
Notes
-------
The `ElectricalMethods` consider the given resistivity values as
a normal values and not on base 10 logarithm. So if log10 values
are given, set the argument `fromlog10` value to ``True``.
.. |VES| replace:: Vertical Electrical Sounding
"""
@abstractmethod
def __init__(self,
AB: float = 200. ,
MN: float = 20.,
arrangement: str = 'schlumberger',
area : str = None,
projection: str ='lonlat',
datum: str ='WGS84',
epsg: int =None,
utm_zone: str = None,
fromlog10:bool =False,
verbose: int = 0,
) -> None:
self.AB=AB
self.MN=MN
self.arrangememt=Config.arrangement(arrangement)
self.utm_zone=utm_zone
self.projection=projection
self.datum=datum
self.epsg=epsg
self.area=area
self.fromlog10=fromlog10
self.verbose=verbose
[docs]
class IsEdi(ABC):
""" Assert SEG MT/EMAP Data Interchange Standard EDI-file .
Is an abstract Base class for control the valid EDI [1]_. It is also
used to ckeck whether object is an instance of EDI object.
EDI stands for Electrical Data Interchange module can read and write an *.edi
file as the 'standard ' format of magnetotellurics. Each section of the .edi
file belongs to a class object, thus the elements of each section are attributes
for easy access. Edi is outputted following the SEG documentation and rules
of EMAP (Electromagnetic Array Profiling) and MT sections.
Examples
--------
>>> import pycsamt
>>> from watex.property import IsEdi
>>> from watex.methods.em import EM
>>> IsEdi.register (pycsamt.core.edi.Edi )
>>> ediObj= EM().fit(r'data/edis').ediObjs_ [0] # one edi-file for assertion
>>> isinstance (ediObj, IsEdi)
... True
References
------------
.. [1] Wight, D.E., Drive, B., 1988. MT/EMAP Data Interchange Standard,
1rt ed. Society of Exploration Geophysicists, Texas 7831, USA.
"""
@property
@abstractmethod
def is_valid (self):
""" Assert whether EDI is valid."""
pass
@staticmethod
def _assert_edi (file: str ,
deep: bool =True
)-> bool :
""" Assert EDI- file .
:param file: str - path-like object
:param deep: bool - Open the file and assert whether it is a valid EDI
if ``False``, just control the EDI extension.
:return: bool- ``True`` if EDI is valid and ``False`` otherwise.
"""
msg = (" Unrecognized SEG EDI-file. Follow the paper of"
" [Wight, D.E., Drive, B., 1988.]"
" <https://www.mtnet.info/docs/seg_mt_emap_1987.pdf>"
" to build a correct EDI- file."
)
flag = False
if file is None :
raise FileHandlingError("NoneType can not be checked. Please"
" provide the right file.")
if not os.path.isfile(file):
raise FileNotFoundError(f"{file!r} is not file. Expect a Path-like"
" object to EDI-file.")
if isinstance(file , str):
flag = os.path.splitext(file )[-1].replace('.', '')
if not deep:
if flag =='edi':
return True
# Open the file now
if flag !='edi':
raise EDIError("Commonly SEG-EDI file must have extension *.edi."
f" Got {flag!r}. Set 'deep=True' to check whether"
" the file contents match an expected EDI contents."
)
try :
with open (file, 'r', encoding ='utf8') as f :
edi_data =f.readlines()
except PermissionError:
msg =''.join(['https://stackoverflow.com/questions/36434764/',
'permissionerror-errno-13-permission-denied'])
raise PermissionError("This Error occurs because you try to access"
" a file from Python without having the necessary"
" permissions. Please read the following guide"
f" {msg!r} to fix that issue")
if flag =='edi':
if (_EDI[0] not in edi_data[0]) or (
_EDI[-1] not in edi_data[-1]):
raise EDIError(msg)
flag =True
else : raise EDIError(msg)
return flag
[docs]
class P:
"""
Data properties are values that are hidden to avoid modifications alongside
the packages. Its was used for assertion, comparison etceteara. These are
enumerated below into a property objects.
Is a property class that handles the |ERP| and |VES| attributes. Along
the :mod:`~.methods.electrical`, it deals with the electrical dipole
arrangements, the data classsification and assert whether it is able to
be read by the scripts. It is a lind of "asserter". Accept data or reject
data provided by the used indicated the way to sanitize it before feeding
to the algorithm.
.. |ERP| replace:: Electrical resistivity profiling
Parameters
-----------
**frcolortags**: Stands for flow rate colors tags. Values are
'#CED9EF','#9EB3DD', '#3B70F2', '#0A4CEF'.
**ididctags**: Stands for the list of index set in dictionary which encompasses
key and values of all different prefixes.
**isation**: List of prefixes used for indexing the stations in the |ERP|.
**ieasting**: List of prefixes used for indexing the easting coordinates array.
**inorthing**: List of prefixes used to index the northing coordinates.
**iresistivity** List of prefix used for indexing the apparent resistivity
values in the |ERP| data collected during the survey.
**isren**: Is the list of heads columns during the data collections. Any data
head |ERP| data provided should be converted into
the following arangement:
+----------+-------------+-----------+-----------+
|station | resistivity | easting | northing |
+----------+-------------+-----------+-----------+
**isrll**: Is the list of heads columns during the data collections. Any data
head |ERP| data provided should be converted into
the following arangement:
+----------+-------------+-------------+----------+
|station | resistivity | longitude | latitude |
+----------+-------------+-------------+----------+
**P**: Typing class for fectching the properties.
Examples
---------
>>> from watex.property import P
>>> P.idicttags
... <property at 0x1ec1f2c3ae0>
>>> P().idictags
...
{'station': ['pk', 'sta', 'pos'], 'longitude': ['east', 'x', 'long', 'lon'],
'latitude': ['north', 'y', 'lat'], 'resistivity': ['rho', 'app', 'res']}
>>> {k:v for k, v in P.__dict__.items() if '__' not in k}
... {'_station': ['pk', 'sta', 'pos'],
'_easting': ['east', 'x', 'long'],
'_northing': ['north', 'y', 'lat'],
'_resistivity': ['rho', 'app', 'res'],
'frcolortags': <property at 0x1ec1f2fee00>,
'idicttags': <property at 0x1ec1f2c3ae0>,
'istation': <property at 0x1ec1f2c3ea0>,
'ieasting': <property at 0x1ec1f2c39f0>,
'inorthing': <property at 0x1ec1f2c3c70>,
'iresistivity': <property at 0x1ec1f2c3e00>,
'isenr': <property at 0x1ec1f2c3db0>}
>>> P().isrll
... ['station','resistivity','longitude','latitude']
>>> from watex.property import P
>>> pObj = P()
>>> P.idictags
... <property at 0x15b2248a450>
>>> pObj.idicttags
... {'station': ['pk', 'sta', 'pos'],
... 'resistivity': ['rho', 'app', 'res', 'se', 'sounding.values'],
... 'longitude': ['long', 'lon'],
... 'latitude': ['lat'],
... 'easting': ['east', 'x'],
... 'northing': ['north', 'y']}
>>> rphead = ['res', 'x', 'y', '']
>>> pObj (rphead) # sanitize the given resistivity profiling head data.
... ['resistivity', 'easting', 'northing']
>>> rphead = ['lat', 'x', 'rho', '']
... ['latitude', 'easting', 'resistivity']
>>> rphead= ['pos', 'x', 'lon', 'north', 'latitud', 'app.res' ]
>>> pObj (rphead)
... ['station', 'easting', 'longitude', 'northing', 'latitude', 'resistivity']
>>> # --> for sounding head assertion
>>> vshead=['ab', 's', 'rho', 'potential']
>>> pObj (vshead, kind ='ves')
... ['AB', 'resistivity'] # in the list of vshead,
... # only 'AB' and 'resistivity' columns are recognized.
"""
station_prefix = [
'pk','sta','pos'
]
easting_prefix =[
'east','x',
]
northing_prefix = [
'north','y',
]
lon_prefix =[
'long', 'lon'
]
lat_prefix = [
'lat'
]
resistivity_prefix = [
'rho','app','res', 'se', 'sounding.values'
]
erp_headll= [
'station', 'resistivity', 'longitude','latitude',
]
erp_headen= [
'station', 'resistivity', 'easting','northing',
]
ves_head =['AB', 'MN', 'rhoa']
param_options = [
['bore', 'for'],
['x','east'],
['y', 'north'],
['pow', 'puiss', 'pa'],
['magn', 'amp', 'ma'],
['shape', 'form'],
['type'],
['sfi', 'if'],
['lat'],
['lon'],
['lwi', 'wi'],
['ohms', 'surf'],
['geol'],
['flow', 'deb']
]
param_ids =[
'id',
'east',
'north',
'power',
'magnitude',
'shape',
'type',
'sfi',
'lat',
'lon',
'lwi',
'ohmS',
'geol',
'flow'
]
ves_props = dict (_AB= ['ab', 'ab/2', 'current.electrodes',
'depth', 'thickness'],
_MN=['mn', 'mn/2', 'potential.electrodes', 'mnspacing'],
)
all_prefixes = { f'_{k}':v for k, v in zip (
erp_headll + erp_headen[2:] , [
station_prefix,
resistivity_prefix,
lon_prefix,
lat_prefix,
easting_prefix,
northing_prefix,
northing_prefix,
]
)}
all_prefixes = {**all_prefixes , **ves_props}
def __init__( self, hl =None ) :
self.hl = hl
for key , value in self.all_prefixes.items() :
self.__setattr__( key , value)
def _check_header_item (self, it , kind ='erp'):
""" Check whether the item exists in the property dictionnary.
Use param `kind` to select the type of header that the data must
collected:
`kind` = ``erp`` -> for Electrical Resistivity Profiling
`kind` = ``ves`` - > for Vertical Electrical Sounding
"""
dict_ = self.idictcpr if kind =='ves' else self.idicttags
for k, val in dict_.items():
for s in val :
if str(it).lower().find(s)>=0:
return k
return
def __call__(self, hl: list = None , kind :str ='erp'):
""" Rename the given header to hold the properties
header values.
Call function could return ``None`` whether the
given header item in `hl` does not match any item in property
headers.
:param hl: list or array,
list of the given headers.
:param kind: str
Type of data fed into the algorithm. Can be ``ves`` for Vertical
Electrical Sounding and ``erp`` for Electrical Resistivity Profiling .
:Example:
>>> from watex.property import P
>>> test_v= ['pos', 'easting', 'north', 'rhoa', 'lat', 'longitud']
>>> pobj = P(test_v)
>>> pobj ()
... ['station', 'easting', 'northing', 'resistivity',
'latitude', 'longitude']
>>> test_v2 = test_v + ['straa', 'nourmai', 'opirn']
>>> pobj (test_v2)
... ['station', 'easting', 'northing', 'resistivity',
'latitude', 'longitude']
"""
v_ =list()
self.hl = hl or self.hl
if self.hl is not None:
self.hl = [self.hl] if isinstance(self.hl, str ) else self.hl
if hasattr(self.hl, '__iter__'):
for item in self.hl :
v_.append( self._check_header_item(item, kind))
# uncomment this for deprecating warning. Henceforth we use
# lamba instead
# v_=list(filter((None).__ne__, v_))
v_ = list(filter(lambda item: item is not None, v_))
return None if len (v_) ==0 else v_
@property
def frcolortags (self):
""" set the dictionnary"""
return dict ((f'fr{k}', f'#{v}') for k, v in zip(
range(4), ('CED9EF','9EB3DD', '3B70F2', '0A4CEF' )
)
)
@property
def idicttags (self):
""" Is the collection of data properties """
return dict ( (k, v) for k, v in zip(
self.isrll + self.isren[2:],
[self.istation, self.iresistivity, self.ilon,
self.ilat, self.ieasting, self.inorthing ])
)
@property
def istation(self) :
""" Use prefix to identify station location positions """
return self._station
@property
def ilon (self):
""" Use prefix to identify longitude coordinates if given in the
dataset. """
return self._longitude
@property
def ilat(self):
""" Use prefix to identify latitude coordinates if given in the
dataset. """
return self._latitude
@property
def ieasting (self):
""" Use prefix to identify easting coordinates if given in the
dataset. """
return self._easting
@property
def inorthing(self):
""" Use prefix to identify northing coordinates if given in the
dataset. """
return self._northing
@property
def iresistivity(self):
""" Use prefix to identify the resistivity values in the dataset"""
return self._resistivity
@property
def isrll(self):
""" `SRLL` is the abbreviation of `S`for ``Stations``,`R`` for
resistivity, `L` for ``Longitude`` and `L` for ``Latitude``.
`SRLL` is the expected columns in Electrical resistivity profiling.
Indeed, it keeps the traditional collections sheets
during the survey. """
return self.erp_headll
@property
def isren(self):
""" `SREN` is the abbreviation of `S`for ``Stations``,`R``for
resistivity, `E` for ``easting`` and `N` for ``northing``.
`SREN` is the expected columns in Electrical resistivity profiling.
Indeed, it keeps the traditional collections sheets
during the survey. """
return self.erp_headen
@property
def icpr (self):
""" Keep only the Vertical Electrical Sounding header data ..."""
return [k.replace('_', '')
for k in self.ves_props.keys() ] +['resistivity']
@property
def idictcpr (self):
""" cpr stands for current-potentials and resistivity. They compose the
main property values when collected the vertical electrical sounding
data."""
# return {f'{k.replace("_", "")}': v for k , v in {
# **self.ves_props, **{'resistivity': self.iresistivity}}.items()}
return {f'{k.replace("_", "")}': v for k , v in {
**self.ves_props, **{'resistivity': self.iresistivity,
'longitude': self.ilon,
'latitude': self.ilat,
'easting': self.ieasting,
'northing': self.inorthing }}.items()
}
[docs]
class BagoueNotes:
r"""
A contest class about the `Bagoue dataset`.
The dataset comes from Bagoue region, located in WestAfrica and lies
between longitudes 6° and 7° W and latitudes 9° and 11° N in the north of
Cote d’Ivoire.
The average FR observed in this area fluctuates between 1
and 3 m3/h. Refer to the link of case story paper in the `repository docs`_
to visualize the location map of the study area with the geographical
distribution of the various boreholes in the region. The geophysical data
and boreholesdata were collected from National Office of Drinking Water(ONEP)
and West-Africa International Drilling Company (FORACO-CI) during the
Presidential Emergency Program (PPU) in 2012-2013 and the National Drinking
Water Supply Program (PNAEP) in 2014.
The data are firstly composed of Electrical resistivity profile (ERP) data
collected from geophysical survey lines with various arrays such as
Schlumberger, gradient rectangle and Wenner :math:`\alpha` or :math:`\beta`
and the Vertical electricalsounding (VES) data carried out on the selected anomalies.
The configuration used during the ERP is Schlumberger with distance of
:math:`AB = 200m \quad \text{and} \quad MN =20m`.
The class gives some details about the test dataset used throughout the
`WATex`_ packages. It is a guidance for the user to get any details about
the data preprocessed in order to wuick implement or testing the method.
Some examples to fetching infos and data are illustrated below:
Examples
-----------
>>> from watex.datasets import fetch_data
>>> bag_records = fetch_data('original').get('DESCR')
... 'https://doi.org/10.5281/zenodo.5571534: bagoue-original'
>>> data_contests =fetch_data('original').get('dataset-contest')
... {'__documentation:': '`watex.property.BagoueNotes.__doc__`',
... '__area': 'https://en.wikipedia.org/wiki/Ivory_Coast',
... '__casehistory': 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021WR031623',
... '__wikipages': 'https://github.com/WEgeophysics/watex/wiki',
... '__citations': ('https://doi.org/10.1029/2021wr031623',
... ' https://doi.org/10.5281/zenodo.5529368')}
>>> #--> fetching X, y dat
>>> # get the list of tags before
>>> tags=fetch_data('original').get('tags')
... ('Bagoue original', ...,'Bagoue prepared sets', 'Bagoue untouched test sets')
>>> len(tags)
... 11
>>> --> fetch the preprocessing sets of data
>>> X, y = fetch_data('preprocessing')
>>> X.shape , y.shape
... ((344, 8), (344,))
>>> list(X.columns)
... ['power', 'magnitude', 'sfi', 'ohmS', 'lwi', 'shape', 'type', 'geol']
>>> X, y = fetch_data('prepared') # data are vectorized and onehotencoded
... ((344, 18), (344,))
>>> X, y = fetch_data('test sets')
>>> X.shape , y.shape
... ((87, 12), (87,))
.. _repository docs: https://github.com/WEgeophysics/watex#documentation>
"""
bagkeys = ('num',
'name',
'east',
'north',
'power',
'magnitude',
'shape',
'type',
'geol',
'ohmS',
'flow'
)
bagvalues = [
'Numbering the data-erp-ves-boreholes',
'Borehole code',
'easting :UTM:29P-30N-WGS84',
'northing :UTM:29P-30N-WGS84',
'anomaly `power` or anomaly width in meter(m).'
'__ref :doc:`watex.utils.exmath.compute_power`',
'anomaly `magnitude` or `height` in Ω.m '
'__ref :doc:`watex.utils.exmath.compute_magnitude`',
'anomaly `standard fracturing index`, no unit<=sqrt(2)'
'__ref :doc:`watex.utils.exmath.compute_sfi`',
'anomaly `shape`. Can be `V`W`M`K`L`U`H`'
'__ref :doc:`watex.utils.exmath.get_shape`',
'anomaly `shape`. Can be `EC`CP`CB2P`NC`__'
'ref :doc:`watex.utils.exmath.get_type`',
'most dominant geology structure of the area where'
' the erp or ves (geophysical survey) is done.',
'Ohmic surface compute on sounding curve in '
'relationship with VES1D inversion (Ω.m2)'
'__ref :doc:`watex.methods.electrical.VerticalSounding`',
'flow rate value of drilling in m3/h'
]
bagattr_infos ={
key:val for key, val in zip(bagkeys, bagvalues)
}
[docs]
class Config:
""" Container of property elements.
Out of bag to keep unmodificable elements. Trick to encapsulate all the
element that are not be allow to be modified.
"""
@property
def arraytype (self):
""" Different array from |ERP| configuration.
Array-configuration can be added as the development progresses.
"""
return {
1 : (
['Schlumberger','AB>> MN','slbg'],
'S'
),
2 : (
['Wenner','AB=MN'],
'W'
),
3: (
['Dipole-dipole','dd','AB<BM>MN','MN<NA>AB'],
'DD'
),
4: (
['Gradient-rectangular','[AB]MN', 'MN[AB]','[AB]'],
'GR'
)
}
@property
def parsers(self ):
""" Readable format that can be read and parse the data """
return {
".csv" : pd.read_csv,
".xlsx": pd.read_excel,
".json": pd.read_json,
".html": pd.read_html,
".sql" : pd.read_sql,
".xml" : pd.read_xml ,
".fwf" : pd.read_fwf,
".pkl" : pd.read_pickle,
".sas" : pd.read_sas,
".spss": pd.read_spss,
# ".orc" : pd.read_orc,
}
[docs]
@staticmethod
def writers (object):
""" Write frame formats."""
return {".csv" : object.to_csv,
".hdf" : object.to_hdf,
".sql" : object.to_sql,
".dict" : object.to_dict,
".xlsx" : object.to_excel,
".json" : object.to_json,
".html" : object.to_html ,
".feather": object.to_feather,
".tex" : object.to_latex,
".stata" : object.to_stata,
".gbq" : object.to_gbq,
".rec" : object.to_records,
".str" : object.to_string,
".clip" : object.to_clipboard,
".md" : object.to_markdown,
".parq" : object.to_parquet,
# ".orc" : object.to_orc,
".pkl" : object.to_pickle
}
[docs]
@staticmethod
def arrangement(a: int | str ):
""" Assert whether the given arrangement is correct.
:param a: int, float, str - Type of given electrical arrangement.
:returns:
- The correct arrangement name
- ``0`` which means ``False`` or a wrong given arrangements.
"""
for k, v in Config().arraytype.items():
if a == k or str(a).lower().strip() in ','.join (
v[0]).lower() or a ==v[1]:
return v[0][0].lower()
return 0
@property
def geo_rocks_properties(self ):
""" Get some sample of the geological rocks. """
return {
"hard rock" : [1e99,1e6 ],
"igneous rock": [1e6, 1e3],
"duricrust" : [5.1e3 , 5.1e2],
"gravel/sand" : [1e4 , 7.943e0],
"conglomerate" : [1e4 , 8.913e1],
"dolomite/limestone" : [1e5 , 1e3],
"permafrost" : [1e5 , 4.169e2],
"metamorphic rock" : [5.1e2 , 1e1],
"tills" : [8.1e2 , 8.512e1],
"standstone conglomerate" : [1e4 , 8.318e1],
"lignite/coal": [7.762e2 , 1e1],
"shale" : [5.012e1 , 3.20e1],
"clay" : [1e2 , 5.012e1],
"saprolite" : [6.310e2 , 3.020e1],
"sedimentary rock": [1e4 , 1e0],
"fresh water" : [3.1e2 ,1e0],
"salt water" : [1e0 , 1.41e0],
"massive sulphide" : [1e0 , 1e-2],
"sea water" : [1.231e-1 ,1e-1],
"ore minerals" : [1e0 , 1e-4],
"graphite" : [3.1623e-2, 3.162e-3]
}
@property
def rockpatterns(self):
"""Default geological rocks patterns.
pattern are not exhaustiv, can be added and changed. This pattern
randomly choosen its not exatly match the rocks geological patterns
as described with the conventional geological swatches relate to
the USGS(US Geological Survey ) swatches- references and FGDC
(Digital cartographic Standard for Geological Map Symbolisation
-FGDCgeostdTM11A2_A-37-01cs2.eps)
The following symbols can be used to create a matplotlib pattern.
.. code-block:: none
make _pattern:{'/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'}
/ - diagonal hatching
\\ - back diagonal
| - vertical
- - horizontal
+ - crossed
x - crossed diagonal
o - small circle
O - large circle
. - dots
* - stars
"""
return {
"hard rock" : ['.+++++.', (.25, .5, .5)],
"igneous rock": ['.o.o.', (1., 1., 1.)],
"duricrust" : ['+.+',(1., .2, .36)],
"gravel" : ['oO',(.75,.86,.12)],
"sand": ['....',(.23, .36, .45)],
"conglomerate" : ['.O.', (.55, 0., .36)],
"dolomite" : ['.-.', (0., .75, .23)],
"limestone" : ['//.',(.52, .23, .125)],
"permafrost" : ['o.', (.2, .26, .75)],
"metamorphic rock" : ['*o.', (.2, .2, .3)],
"tills" : ['-.', (.7, .6, .9)],
"standstone ": ['..', (.5, .6, .9)],
"lignite coal": ['+/.',(.5, .5, .4)],
"coal": ['*.', (.8, .9, 0.)],
"shale" : ['=', (0., 0., 0.7)],
"clay" : ['=.',(.9, .8, 0.8)],
"saprolite" : ['*/',(.3, 1.2, .4)],
"sedimentary rock": ['...',(.25, 0., .25)],
"fresh water" : ['.-.',(0., 1.,.2)],
"salt water" : ['o.-',(.2, 1., .2)],
"massive sulphide" : ['.+O',(1.,.5, .5 )],
"sea water" : ['.--',(.0, 1., 0.)],
"ore minerals" : ['--|',(.8, .2, .2)],
"graphite" : ['.++.',(.2, .7, .7)],
}
[docs]
class References:
"""
References information for a citation.
Holds the following information:
================ ========== =============================================
Attributes Type Explanation
================ ========== =============================================
author string Author names
title string Title of article, or publication
journal string Name of journal
doi string DOI number
year int year published
================ ========== =============================================
More attributes can be added by inputing a key word dictionary
Examples
---------
>>> from watex.property import References
>>> refobj = References(
**{'volume':18, 'pages':'234--214',
'title':'watex :A machine learning research for hydrogeophysic' ,
'journal':'Computers and Geosciences',
'year':'2021', 'author':'DMaryE'}
)
>>> refobj.journal
Out[21]: 'Computers and Geosciences'
"""
def __init__(
self,
author=None,
title=None,
journal=None,
volume=None,
doi=None,
year=None,
**kws
):
self.author=author
self.title=title
self.journal=journal
self.volume=volume
self.doi=doi
self.year=year
for key in list(kws.keys()):
setattr(self, key, kws[key])
[docs]
class Copyright:
"""
Information of copyright, mainly about the use of data can use
the data. Be sure to read over the conditions_of_use.
Holds the following informations:
================= =========== ===========================================
Attributes Type Explanation
================= =========== ===========================================
References References citation of published work using these data
conditions_of_use string conditions of use of data used for testing
program
release_status string release status [ open | public |proprietary]
================= =========== ===========================================
More attributes can be added by inputing a key word dictionary
Examples
----------
>>> from watex.property import Copyright
>>> copbj =Copyright(**{'owner':'University of AI applications',
... 'contact':'WATER4ALL'})
>>> copbj.contact
Out[20]: 'WATER4ALL
"""
cuse =(
"All Data used for software demonstration mostly located in "
" data directory <data/> cannot be used for commercial and "
" distributive purposes. They can not be distributed to a third"
" party. However, they can be used for understanding the program."
" Some available ERP and VES raw data can be found on the record"
" <'10.5281/zenodo.5571534'>. Whereas EDI-data e.g. EMAP/MT data,"
" can be collected at http://ds.iris.edu/ds/tags/magnetotelluric-data/."
" The metadata from both sites are available free of charge and may"
" be copied freely, duplicated and further distributed provided"
" these data are cited as the reference."
)
def __init__(
self,
release_status=None,
additional_info=None,
conditions_of_use=None,
**kws
):
self.release_status=release_status
self.additional_info=additional_info
self.conditions_of_use=conditions_of_use or self.cuse
self.References=References()
for key in list(kws.keys()):
setattr(self, key, kws[key])
[docs]
class Person:
"""
Information for a person
================ ========== =============================================
Attributes Type Explanation
================ ========== =============================================
email string email of person
name string name of person
organization string name of person's organization
organization_url string organizations web address
================ ========== =============================================
More attributes can be added by inputing a key word dictionary
Examples
----------
>>> from watex.property import Person
>>> person =Person(**{'name':'ABA', 'email':'aba@water4all.ai.org',
... 'phone':'00225-0769980706',
... 'organization':'WATER4ALL'})
>>> person.name
Out[23]: 'ABA
>>> person.organization
Out[25]: 'WATER4ALL'
"""
def __init__(
self,
email=None,
name=None,
organization=None,
organization_url=None,
**kws
):
self.email=email
self.name=name
self.organization=organization
self.organization_url=organization_url
for key in list(kws.keys()):
setattr(self, key, kws[key])
[docs]
class Software:
"""
software info
================= =========== =============================================
Attributes Type Explanation
================= =========== =============================================
name string name of software
version string version of sotware
Author string Author of software
release string latest version release
================= =========== =============================================
More attributes can be added by inputing a key word dictionary
Examples
----------
>>> from watex.property import Software
>>> Software(**{'release':'0.11.23'})
"""
def __init__(
self,
name=None,
version=None,
release=None,
**kws
):
self.name=name
self.version=version
self.release=release
self.Author=Person()
for key in kws:
setattr(self, key, kws[key])
