TNO Intern

Commit 5a477ea6 authored by Florian Knappers's avatar Florian Knappers
Browse files

fix small renaming error

parent 4042e69e

pythermogis/transmissivity.py

+5 −5
Original line number Diff line number Diff line
@@ -9,7 +9,7 @@ def generate_thickness_permeability_transmissivity_for_pvalues( 
    ln_permeability_mean: float,

    ln_permeability_sd: float,

    p_values: xr.DataArray,

    nsamples: int = 10000,

    n_samples: int = 10000,

) -> float:

    """

    Given thickness provided as a normal distribution and ln(permeability)
@@ -67,11 +67,11 @@ def generate_thickness_permeability_transmissivity_for_pvalues( 


    if thickness_sd == 0:

        thickness_pvalues = np.full(len(p_value_fractions), thickness_mean)

        thickness_samples = np.full(nsamples, thickness_mean)

        thickness_samples = np.full(n_samples, thickness_mean)

    else:

        thickness_dist = stats.norm(loc=thickness_mean, scale=thickness_sd)

        thickness_pvalues = thickness_dist.ppf(p_value_fractions)

        thickness_samples = thickness_dist.rvs(nsamples)

        thickness_samples = thickness_dist.rvs(n_samples)

        thickness_samples = np.clip(thickness_samples, a_min=0.01, a_max=None)



    ln_permeability_dist = stats.norm(
@@ -81,10 +81,10 @@ def generate_thickness_permeability_transmissivity_for_pvalues( 


    # Sampling method for transmissivity

    transmissivity_samples = np.sort(

        np.exp(ln_permeability_dist.rvs(nsamples) + np.log(thickness_samples))

        np.exp(ln_permeability_dist.rvs(n_samples) + np.log(thickness_samples))

    )



    sample_indexes = np.array(p_value_fractions * (nsamples - 1))

    sample_indexes = np.array(p_value_fractions * (n_samples - 1))

    transmissivity_pvalues_sampled = transmissivity_samples[sample_indexes.astype(int)]



    return thickness_pvalues, permeability_pvalues, transmissivity_pvalues_sampled

tests/test_transmissivity.py

+7 −7
Original line number Diff line number Diff line
@@ -32,7 +32,7 @@ class PyThermoGIS(TestCase): 
        thickness_sd = 5

        ln_perm_mean = 5

        ln_perm_sd = 0.5

        nSamples = 100000

        n_samples = 100000

        p_values_list = [1, 10, 20, 30, 40, 50, 60, 70, 80, 90]



        #
@@ -57,7 +57,7 @@ class PyThermoGIS(TestCase): 
            ln_perm_mean,

            ln_perm_sd,

            p_values,

            kwargs={"nSamples": nSamples},

            kwargs={"n_samples": n_samples},

            input_core_dims=[[], [], [], [], []],

            output_core_dims=[[], [], []],

            vectorize=True,
@@ -72,7 +72,7 @@ class PyThermoGIS(TestCase): 
            self.generate_transmissivity_java(

                ln_perm_mean,

                ln_perm_sd,

                nSamples,

                n_samples,

                p_values_list,

                thickness_mean,

                thickness_sd,
@@ -127,7 +127,7 @@ class PyThermoGIS(TestCase): 
        self,

        ln_perm_mean,

        ln_perm_sd,

        nSamples,

        n_samples,

        p_values_list,

        thickness_mean,

        thickness_sd,
@@ -149,13 +149,13 @@ class PyThermoGIS(TestCase): 
            for pValue in p_values_list

        ]



        permeabilitySamples = permeabilityDistribution.generateSamples(nSamples)

        thicknessSamples = thicknessDistribution.generateSamples(nSamples)

        permeabilitySamples = permeabilityDistribution.generateSamples(n_samples)

        thicknessSamples = thicknessDistribution.generateSamples(n_samples)

        thicknessSamples = np.clip(thicknessSamples, a_min=0.01, a_max=None)



        trans_samples = np.sort(np.exp(permeabilitySamples + np.log(thicknessSamples)))

        trans_p_value_java = [

            trans_samples[int((100 - p_value) / 100 * nSamples)]

            trans_samples[int((100 - p_value) / 100 * n_samples)]

            for p_value in p_values_list

        ]