Merge pull request #52 from frank1010111/pre-commit-ci-update-config

[pre-commit.ci] pre-commit autoupdate
frank1010111 · Oct 2, 2024 · 7118063 · 7118063
2 parents 0a60f73 + cdf59ce
commit 7118063
Show file tree

Hide file tree

Showing 7 changed files with 14 additions and 30 deletions.
diff --git 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"]

diff --git 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
@@ -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
@@ -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
@@ -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
@@ -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
@@ -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",