From 4d165f174c7ac6d040932224b2aa49e94556124b Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 30 Sep 2024 16:44:39 +0000 Subject: [PATCH 1/2] [pre-commit.ci] pre-commit autoupdate MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit updates: - [github.com/astral-sh/ruff-pre-commit: v0.6.7 → v0.6.8](https://github.com/astral-sh/ruff-pre-commit/compare/v0.6.7...v0.6.8) --- .pre-commit-config.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 1908133..6912b11 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -42,7 +42,7 @@ repos: additional_dependencies: [black==23.7.0] - repo: https://github.com/astral-sh/ruff-pre-commit - rev: "v0.6.7" + rev: "v0.6.8" hooks: - id: ruff args: ["--fix", "--show-fixes"] From cdf59ce94405f0764032c132f7e0522a64329462 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Mon, 30 Sep 2024 16:44:50 +0000 Subject: [PATCH 2/2] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- docs/bayesian_fitting.ipynb | 8 ++------ docs/flow.ipynb | 4 +--- docs/fluids.ipynb | 5 +---- docs/forecast.ipynb | 10 ++++------ docs/forecast_varying.ipynb | 5 +---- docs/oil_flow.ipynb | 10 ++++------ 6 files changed, 13 insertions(+), 29 deletions(-) diff --git a/docs/bayesian_fitting.ipynb b/docs/bayesian_fitting.ipynb index 0bfbc4f..84b2db7 100644 --- a/docs/bayesian_fitting.ipynb +++ b/docs/bayesian_fitting.ipynb @@ -96,9 +96,7 @@ "tau_test = 2\n", "M_test = 300\n", "true_prod = M_test * derivative(rf_func, time_on_production / tau_test, dx=0.01)\n", - "production = true_prod * np.random.default_rng(42).normal(\n", - " 1, 0.1, size=len(time_on_production)\n", - ")\n", + "production = true_prod * np.random.default_rng(42).normal(1, 0.1, size=len(time_on_production))\n", "cum_production = cumulative_trapezoid(production, time_on_production, initial=0)\n", "\n", "fig, ax = plt.subplots()\n", @@ -246,9 +244,7 @@ "\n", "ax2.plot(\n", " time_on_production,\n", - " az.extract(posterior_predictive, group=\"posterior_predictive\", num_samples=100)[\n", - " \"cum\"\n", - " ],\n", + " az.extract(posterior_predictive, group=\"posterior_predictive\", num_samples=100)[\"cum\"],\n", " color=\"steelblue\",\n", ")\n", "ax2.plot(time_on_production, cum_production, color=\"peru\")\n", diff --git a/docs/flow.ipynb b/docs/flow.ipynb index 5741d27..91fb855 100644 --- a/docs/flow.ipynb +++ b/docs/flow.ipynb @@ -217,9 +217,7 @@ ], "source": [ "fig, ax = plt.subplots()\n", - "ax.plot(\n", - " time, res_realgas.recovery_factor(density=True), \"-.\", label=\"Rate from density\"\n", - ")\n", + "ax.plot(time, res_realgas.recovery_factor(density=True), \"-.\", label=\"Rate from density\")\n", "ax.plot(time, rf2, \"--\", label=\"Recovery factor from frac face\")\n", "ax.legend()\n", "ax.set(\n", diff --git a/docs/fluids.ipynb b/docs/fluids.ipynb index e566f23..f29f659 100644 --- a/docs/fluids.ipynb +++ b/docs/fluids.ipynb @@ -173,10 +173,7 @@ "from bluebonnet.fluids.water import compressibility_water_McCain\n", "\n", "c_g = [compressibility_DAK(200, p, *pseudocritical_point) for p in pressure]\n", - "c_o = [\n", - " oil_compressibility_Standing(200, p, 35, 0.8, 800, *pseudocritical_point)\n", - " for p in pressure\n", - "]\n", + "c_o = [oil_compressibility_Standing(200, p, 35, 0.8, 800, *pseudocritical_point) for p in pressure]\n", "c_w = compressibility_water_McCain(200, pressure, 0.0)\n", "\n", "fig, ax = plt.subplots()\n", diff --git a/docs/forecast.ipynb b/docs/forecast.ipynb index e32c642..de0f45c 100644 --- a/docs/forecast.ipynb +++ b/docs/forecast.ipynb @@ -97,9 +97,9 @@ "time_on_production = np.linspace(1e-2, t_end, 500) * fake_tau\n", "\n", "# Add some randomness to make this interesting\n", - "randomness = np.random.default_rng(42).normal(\n", - " 0, 2e-3, size=len(time_on_production)\n", - ") / np.sqrt(time_on_production + 0.1)\n", + "randomness = np.random.default_rng(42).normal(0, 2e-3, size=len(time_on_production)) / np.sqrt(\n", + " time_on_production + 0.1\n", + ")\n", "fake_rf = rf_func(time_on_production / fake_tau)\n", "fake_rate = m_factor * np.maximum(np.gradient(fake_rf) + randomness, 0)\n", "cum_production = cumulative_trapezoid(fake_rate, time_on_production, initial=0)\n", @@ -453,9 +453,7 @@ } ], "source": [ - "rf_func = interp1d(\n", - " time, rf_twophase, bounds_error=False, fill_value=(0, rf_twophase[-1])\n", - ")\n", + "rf_func = interp1d(time, rf_twophase, bounds_error=False, fill_value=(0, rf_twophase[-1]))\n", "scaling_curve = ForecasterOnePhase(rf_func)\n", "scaling_curve.fit(time_on_production, fake_cum)\n", "print(\n", diff --git a/docs/forecast_varying.ipynb b/docs/forecast_varying.ipynb index d6ed085..92b8189 100644 --- a/docs/forecast_varying.ipynb +++ b/docs/forecast_varying.ipynb @@ -244,10 +244,7 @@ "# This file contains an estimate of initial pressure. That's all I need it for here.\n", "well_file = f\"https://media.githubusercontent.com/media/frank1010111/bluebonnet/main/data/WellData_{well_number}.csv\"\n", "pressure_initial = float(\n", - " pd.read_csv(well_file)\n", - " .set_index(\"Field\")\n", - " .loc[\"Initial Pressure Estimate (psi)\"]\n", - " .iloc[0]\n", + " pd.read_csv(well_file).set_index(\"Field\").loc[\"Initial Pressure Estimate (psi)\"].iloc[0]\n", ")\n", "\n", "result = fit_production_pressure(\n", diff --git a/docs/oil_flow.ipynb b/docs/oil_flow.ipynb index 0624cbd..f78ce3f 100644 --- a/docs/oil_flow.ipynb +++ b/docs/oil_flow.ipynb @@ -106,9 +106,7 @@ } ], "source": [ - "pvt_oil.plot(x=\"pressure\", y=[\"Bo\", \"z-factor\", \"viscosity\"]).set(\n", - " ylabel=\"value\", xlim=(0, 9000)\n", - ");" + "pvt_oil.plot(x=\"pressure\", y=[\"Bo\", \"z-factor\", \"viscosity\"]).set(ylabel=\"value\", xlim=(0, 9000));" ] }, { @@ -276,9 +274,9 @@ "\n", "# scale pseudopressure\n", "pseudopressure = interp1d(df_pvt.pressure, df_pvt.pseudopressure)\n", - "df_pvt_mp[\"pseudopressure\"] = (\n", - " pseudopressure(df_pvt_mp[\"pressure\"]) - pseudopressure(p_frac)\n", - ") / (pseudopressure(p_res) - pseudopressure(p_frac))\n", + "df_pvt_mp[\"pseudopressure\"] = (pseudopressure(df_pvt_mp[\"pressure\"]) - pseudopressure(p_frac)) / (\n", + " pseudopressure(p_res) - pseudopressure(p_frac)\n", + ")\n", "\n", "fig, ax = plt.subplots()\n", "df_pvt_mp.plot(x=\"pressure\", y=\"pseudopressure\", ax=ax)\n",