How to use the pykrige.core._find_statistics function in PyKrige

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github bsmurphy / PyKrige / pykrige / ok.py View on Github external
else:
                print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        self.delta, self.sigma, self.epsilon = _find_statistics(
            np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED)).T,
            self.Z,
            self.variogram_function,
            self.variogram_model_parameters,
            self.coordinates_type,
        )
        self.Q1 = core.calcQ1(self.epsilon)
        self.Q2 = core.calcQ2(self.epsilon)
        self.cR = core.calc_cR(self.Q2, self.sigma)
        if self.verbose:
            print("Q1 =", self.Q1)
            print("Q2 =", self.Q2)
            print("cR =", self.cR, "\n")
github bsmurphy / PyKrige / pykrige / uk.py View on Github external
else:
                print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        self.delta, self.sigma, self.epsilon = _find_statistics(
            np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED)).T,
            self.Z,
            self.variogram_function,
            self.variogram_model_parameters,
            "euclidean",
        )
        self.Q1 = core.calcQ1(self.epsilon)
        self.Q2 = core.calcQ2(self.epsilon)
        self.cR = core.calc_cR(self.Q2, self.sigma)
        if self.verbose:
            print("Q1 =", self.Q1)
            print("Q2 =", self.Q2)
            print("cR =", self.cR, "\n")

        if self.verbose:
            print("Initializing drift terms...")
github bsmurphy / PyKrige / pykrige / ok.py View on Github external
print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        if enable_statistics:
            self.delta, self.sigma, self.epsilon = _find_statistics(
                np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED)).T,
                self.Z,
                self.variogram_function,
                self.variogram_model_parameters,
                self.coordinates_type,
            )
            self.Q1 = core.calcQ1(self.epsilon)
            self.Q2 = core.calcQ2(self.epsilon)
            self.cR = core.calc_cR(self.Q2, self.sigma)
            if self.verbose:
                print("Q1 =", self.Q1)
                print("Q2 =", self.Q2)
                print("cR =", self.cR, "\n")
        else:
            self.delta, self.sigma, self.epsilon, self.Q1, self.Q2, self.cR = [None] * 6
github bsmurphy / PyKrige / pykrige / uk.py View on Github external
else:
                print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        self.delta, self.sigma, self.epsilon = _find_statistics(
            np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED)).T,
            self.Z,
            self.variogram_function,
            self.variogram_model_parameters,
            "euclidean",
        )
        self.Q1 = core.calcQ1(self.epsilon)
        self.Q2 = core.calcQ2(self.epsilon)
        self.cR = core.calc_cR(self.Q2, self.sigma)
        if self.verbose:
            print("Q1 =", self.Q1)
            print("Q2 =", self.Q2)
            print("cR =", self.cR, "\n")
github bsmurphy / PyKrige / pykrige / uk3d.py View on Github external
else:
                print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        self.delta, self.sigma, self.epsilon = _find_statistics(
            np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED)).T,
            self.VALUES,
            self.variogram_function,
            self.variogram_model_parameters,
            "euclidean",
        )
        self.Q1 = core.calcQ1(self.epsilon)
        self.Q2 = core.calcQ2(self.epsilon)
        self.cR = core.calc_cR(self.Q2, self.sigma)
        if self.verbose:
            print("Q1 =", self.Q1)
            print("Q2 =", self.Q2)
            print("cR =", self.cR, "\n")

        if self.verbose:
            print("Initializing drift terms...")
github bsmurphy / PyKrige / pykrige / ok3d.py View on Github external
else:
                print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        self.delta, self.sigma, self.epsilon = _find_statistics(
            np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED)).T,
            self.VALUES,
            self.variogram_function,
            self.variogram_model_parameters,
            "euclidean",
        )
        self.Q1 = core.calcQ1(self.epsilon)
        self.Q2 = core.calcQ2(self.epsilon)
        self.cR = core.calc_cR(self.Q2, self.sigma)
        if self.verbose:
            print("Q1 =", self.Q1)
            print("Q2 =", self.Q2)
            print("cR =", self.cR, "\n")
github bsmurphy / PyKrige / pykrige / ok3d.py View on Github external
else:
                print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        self.delta, self.sigma, self.epsilon = _find_statistics(
            np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED)).T,
            self.VALUES,
            self.variogram_function,
            self.variogram_model_parameters,
            "euclidean",
        )
        self.Q1 = core.calcQ1(self.epsilon)
        self.Q2 = core.calcQ2(self.epsilon)
        self.cR = core.calc_cR(self.Q2, self.sigma)
        if self.verbose:
            print("Q1 =", self.Q1)
            print("Q2 =", self.Q2)
            print("cR =", self.cR, "\n")
github bsmurphy / PyKrige / pykrige / uk3d.py View on Github external
else:
                print("Using '%s' Variogram Model" % self.variogram_model)
                print("Partial Sill:", self.variogram_model_parameters[0])
                print(
                    "Full Sill:",
                    self.variogram_model_parameters[0]
                    + self.variogram_model_parameters[2],
                )
                print("Range:", self.variogram_model_parameters[1])
                print("Nugget:", self.variogram_model_parameters[2], "\n")
        if self.enable_plotting:
            self.display_variogram_model()

        if self.verbose:
            print("Calculating statistics on variogram model fit...")
        self.delta, self.sigma, self.epsilon = _find_statistics(
            np.vstack((self.X_ADJUSTED, self.Y_ADJUSTED, self.Z_ADJUSTED)).T,
            self.VALUES,
            self.variogram_function,
            self.variogram_model_parameters,
            "euclidean",
        )
        self.Q1 = core.calcQ1(self.epsilon)
        self.Q2 = core.calcQ2(self.epsilon)
        self.cR = core.calc_cR(self.Q2, self.sigma)
        if self.verbose:
            print("Q1 =", self.Q1)
            print("Q2 =", self.Q2)
            print("cR =", self.cR, "\n")