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[pre-commit.ci] pre-commit autoupdate #21

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[pre-commit.ci] pre-commit autoupdate #21

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b73683b
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Sep 16, 2024
d039c06
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Sep 16, 2024
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14 changes: 7 additions & 7 deletions .pre-commit-config.yaml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.4.0
rev: v4.6.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
Expand All @@ -11,19 +11,19 @@ repos:
args: ["--autofix", "--indent=2", "--no-sort-keys"]

- repo: https://github.com/psf/black
rev: 23.3.0
rev: 24.8.0
hooks:
- id: black
args: ["--line-length", "100"]

- repo: https://github.com/charliermarsh/ruff-pre-commit
rev: "v0.0.260"
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: "v0.6.5"
hooks:
- id: ruff
args: ["--fix"]

- repo: https://github.com/nbQA-dev/nbQA
rev: 1.7.0
rev: 1.8.7
hooks:
- id: nbqa-ruff
args: ["--fix"]
Expand All @@ -35,7 +35,7 @@ repos:
args: ["--py37-plus"]

- repo: https://github.com/pre-commit/mirrors-prettier
rev: v2.2.1
rev: v4.0.0-alpha.8
hooks:
- id: prettier
language_version: system
Expand All @@ -51,7 +51,7 @@ repos:
)$"

- repo: https://github.com/pre-commit/mirrors-prettier
rev: v2.2.1
rev: v4.0.0-alpha.8
hooks:
- id: prettier
name: prettier-markdown
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7 changes: 4 additions & 3 deletions notebooks/Figure-1.ipynb
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Expand Up @@ -15,11 +15,12 @@
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import os\n",
"\n",
"import fsspec\n",
"import json\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt"
"import matplotlib.pyplot as plt\n",
"import numpy as np"
]
},
{
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9 changes: 5 additions & 4 deletions notebooks/Figure-3.ipynb
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Expand Up @@ -15,13 +15,14 @@
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import os\n",
"\n",
"import fsspec\n",
"import json\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import statsmodels.formula.api as smf\n",
"import matplotlib.pyplot as plt"
"import pandas as pd\n",
"import statsmodels.formula.api as smf"
]
},
{
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34 changes: 24 additions & 10 deletions notebooks/Figure-5.ipynb
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Expand Up @@ -15,12 +15,13 @@
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import os\n",
"\n",
"import fsspec\n",
"import json\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"from matplotlib import ticker"
]
},
Expand Down Expand Up @@ -93,9 +94,15 @@
" np.percentile(data[key][\"delta_arbocs\"], 75) / get(key)[\"arbocs\"][\"issuance\"]\n",
" for key in data.keys()\n",
"]\n",
"df[\"absolute_low\"] = [np.percentile(data[key][\"delta_arbocs\"], 5) for key in data.keys()]\n",
"df[\"absolute_med\"] = [np.percentile(data[key][\"delta_arbocs\"], 50) for key in data.keys()]\n",
"df[\"absolute_high\"] = [np.percentile(data[key][\"delta_arbocs\"], 95) for key in data.keys()]\n",
"df[\"absolute_low\"] = [\n",
" np.percentile(data[key][\"delta_arbocs\"], 5) for key in data.keys()\n",
"]\n",
"df[\"absolute_med\"] = [\n",
" np.percentile(data[key][\"delta_arbocs\"], 50) for key in data.keys()\n",
"]\n",
"df[\"absolute_high\"] = [\n",
" np.percentile(data[key][\"delta_arbocs\"], 95) for key in data.keys()\n",
"]\n",
"df[\"project_size\"] = [get(key)[\"arbocs\"][\"issuance\"] for key in data.keys()]\n",
"df[\"cp_slag\"] = [get(key)[\"carbon\"][\"common_practice\"][\"value\"] for key in data.keys()]\n",
"df[\"alternate_slag\"] = [np.percentile(data[key][\"alt_slag\"], 50) for key in data.keys()]\n",
Expand All @@ -117,8 +124,10 @@
"metadata": {},
"outputs": [],
"source": [
"def format_si(num, precision=0, suffixes=[\"\", \"K\", \"M\", \"G\", \"T\", \"P\"], show_suffix=False):\n",
" m = sum([abs(num / 1000.0 ** x) >= 1 for x in range(1, len(suffixes))])\n",
"def format_si(\n",
" num, precision=0, suffixes=[\"\", \"K\", \"M\", \"G\", \"T\", \"P\"], show_suffix=False\n",
"):\n",
" m = sum([abs(num / 1000.0**x) >= 1 for x in range(1, len(suffixes))])\n",
" if show_suffix:\n",
" return f\"{num/1000.0**m:.{precision}f}{suffixes[m]}\"\n",
" else:\n",
Expand Down Expand Up @@ -154,7 +163,10 @@
" total.append(np.nansum([data[key][\"delta_arbocs\"][i] for key in data.keys()]))\n",
" total_arbocs = np.percentile(total, [5, 50, 95])\n",
" total_percentage = np.percentile(total, [5, 50, 95]) / np.sum(\n",
" [[x for x in db if x[\"id\"] == key][0][\"arbocs\"][\"issuance\"] for key in data.keys()]\n",
" [\n",
" [x for x in db if x[\"id\"] == key][0][\"arbocs\"][\"issuance\"]\n",
" for key in data.keys()\n",
" ]\n",
" )"
]
},
Expand Down Expand Up @@ -284,7 +296,9 @@
"axs[1].vlines(df[\"id\"], -1, 1.5, color=(0.95, 0.95, 0.95), linewidth=1)\n",
"axs[1].hlines([0], [0], [len(df) - 1], color=(0.75, 0.75, 0.75), linewidth=2)\n",
"axs[1].plot(df[\"id\"], df[\"percent_med\"], \".\", color=\"#7EB36A\", markersize=12)\n",
"axs[1].vlines(df[\"id\"], df[\"percent_low\"], df[\"percent_high\"], color=\"black\", linewidth=1.25)\n",
"axs[1].vlines(\n",
" df[\"id\"], df[\"percent_low\"], df[\"percent_high\"], color=\"black\", linewidth=1.25\n",
")\n",
"axs[1].set_xticks([])\n",
"axs[1].set_ylim([-1.1, 1.1])\n",
"axs[1].set_ylabel(\"Crediting error (%)\")\n",
Expand Down
38 changes: 26 additions & 12 deletions notebooks/Figure-6.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -15,9 +15,10 @@
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import os\n",
"\n",
"import fsspec\n",
"import json\n",
"import geopandas\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
Expand All @@ -26,7 +27,6 @@
"from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n",
"from shapely.geometry import Point\n",
"\n",
"\n",
"crs = \"+proj=aea +lat_0=23 +lon_0=-96 +lat_1=29.5 +lat_2=45.5 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs=True\""
]
},
Expand Down Expand Up @@ -100,7 +100,9 @@
"outputs": [],
"source": [
"proj_centroids = {\n",
" project[\"opr_id\"]: Point(project[\"shape_centroid\"][0][0], project[\"shape_centroid\"][0][1])\n",
" project[\"opr_id\"]: Point(\n",
" project[\"shape_centroid\"][0][0], project[\"shape_centroid\"][0][1]\n",
" )\n",
" for project in db\n",
" if (79 in project[\"supersection_ids\"])\n",
" and (\n",
Expand All @@ -119,7 +121,9 @@
"outputs": [],
"source": [
"proj_points = geopandas.GeoDataFrame(\n",
" data=list(proj_centroids.keys()), geometry=list(proj_centroids.values()), crs=\"epsg:4326\"\n",
" data=list(proj_centroids.keys()),\n",
" geometry=list(proj_centroids.values()),\n",
" crs=\"epsg:4326\",\n",
")"
]
},
Expand Down Expand Up @@ -214,9 +218,9 @@
"metadata": {},
"outputs": [],
"source": [
"vmin, vmax = arbitrage_df.mean_local_slag.quantile(0.025), arbitrage_df.mean_local_slag.quantile(\n",
" 0.975\n",
")\n",
"vmin, vmax = arbitrage_df.mean_local_slag.quantile(\n",
" 0.025\n",
"), arbitrage_df.mean_local_slag.quantile(0.975)\n",
"\n",
"norm = mpl.colors.Normalize(vmin, vmax)"
]
Expand Down Expand Up @@ -276,9 +280,13 @@
"outputs": [],
"source": [
"supersection_sections = (\n",
" ecomap_sections.loc[ecomap_sections[\"MAP_UNIT_S\"].isin(ecosections)].to_crs(crs).copy()\n",
" ecomap_sections.loc[ecomap_sections[\"MAP_UNIT_S\"].isin(ecosections)]\n",
" .to_crs(crs)\n",
" .copy()\n",
")\n",
"supersection_sections[\"slag\"] = supersection_sections[\"MAP_UNIT_S\"].map(\n",
" slag_per_section\n",
")\n",
"supersection_sections[\"slag\"] = supersection_sections[\"MAP_UNIT_S\"].map(slag_per_section)\n",
"supersection_outline = supersection_sections.dissolve(\"PROJECT\")"
]
},
Expand Down Expand Up @@ -327,10 +335,14 @@
" vmax=55,\n",
" legend_kwds={\"label\": \"\", \"orientation\": \"vertical\"},\n",
")\n",
"cax.set_ylabel(\"$\\Delta$ Carbon\\n(tCO2e / acre)\", loc=\"center\", labelpad=-75, fontsize=12)\n",
"cax.set_ylabel(\n",
" \"$\\\\Delta$ Carbon\\n(tCO2e / acre)\", loc=\"center\", labelpad=-75, fontsize=12\n",
")\n",
"cax.yaxis.set_ticks_position(\"none\")\n",
"\n",
"proj_points.to_crs(crs).plot(ax=ax[0], marker=\"^\", color=\"k\", markersize=100, edgecolor=None)\n",
"proj_points.to_crs(crs).plot(\n",
" ax=ax[0], marker=\"^\", color=\"k\", markersize=100, edgecolor=None\n",
")\n",
"supersection_outline.plot(ax=ax[0], edgecolor=\"k\", lw=0.2, color=\"None\")\n",
"\n",
"supersection_sections.plot(\n",
Expand All @@ -342,7 +354,9 @@
" vmin=-55,\n",
" vmax=55,\n",
")\n",
"proj_points.to_crs(crs).plot(ax=ax[1], marker=\"^\", color=\"k\", markersize=100, edgecolor=None)\n",
"proj_points.to_crs(crs).plot(\n",
" ax=ax[1], marker=\"^\", color=\"k\", markersize=100, edgecolor=None\n",
")\n",
"\n",
"\n",
"xys = {\"M261D\": (0.7, 0.25), \"M261A\": (0.15, 0.8), \"M261B\": (0.4, 0.15)}\n",
Expand Down
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