From 48989cc7e1d6e017ebe6f634dd69a184123eddba Mon Sep 17 00:00:00 2001 From: Paul Natsuo Kishimoto Date: Thu, 16 Jan 2025 10:49:17 +0100 Subject: [PATCH] Include *.ipynb in ruff format checking Format 2 files. --- pyproject.toml | 4 - tutorial/transport/py_transport.ipynb | 74 +++++++++++-------- .../transport/py_transport_scenario.ipynb | 64 +++++++++------- 3 files changed, 79 insertions(+), 63 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 3c322b8f8..13989297e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -112,10 +112,6 @@ markers = [ ] tmp_path_retention_policy = "none" -[tool.ruff] -# TEMPORARY Exclude tutorial files -extend-exclude = ["*.ipynb"] - [tool.ruff.lint] select = ["C9", "E", "F", "I", "W"] # FIXME the following exceed this limit diff --git a/tutorial/transport/py_transport.ipynb b/tutorial/transport/py_transport.ipynb index efac6e40d..a36cd9fa6 100644 --- a/tutorial/transport/py_transport.ipynb +++ b/tutorial/transport/py_transport.ipynb @@ -54,8 +54,9 @@ "metadata": {}, "outputs": [], "source": [ - "# load required packages \n", + "# Import required packages\n", "import pandas as pd\n", + "\n", "import ixmp" ] }, @@ -65,7 +66,7 @@ "metadata": {}, "outputs": [], "source": [ - "# launch the ix modeling platform using the default back end\n", + "# Launch the ix modeling platform using the default back end\n", "mp = ixmp.Platform()\n", "\n", "# The following lines have the same effect:\n", @@ -79,14 +80,14 @@ "metadata": {}, "outputs": [], "source": [ - "# details for creating a new scenario in the ix modeling platform \n", + "# details for creating a new scenario in the ix modeling platform\n", "model = \"transport problem\"\n", "scenario = \"standard\"\n", - "annot = \"Dantzig's transportation problem for illustration and testing\" \n", + "annot = \"Dantzig's transportation problem for illustration and testing\"\n", "\n", "# initialize a new ixmp.Scenario\n", "# the parameter version='new' indicates that this is a new scenario instamce\n", - "scen = ixmp.Scenario(mp, model, scenario, version='new', annotation=annot)" + "scen = ixmp.Scenario(mp, model, scenario, version=\"new\", annotation=annot)" ] }, { @@ -114,11 +115,11 @@ "metadata": {}, "outputs": [], "source": [ - "# define the sets of locations of canning plants and markets \n", + "# define the sets of locations of canning plants and markets\n", "scen.init_set(\"i\")\n", "scen.add_set(\"i\", [\"seattle\", \"san-diego\"])\n", "scen.init_set(\"j\")\n", - "scen.add_set(\"j\", [\"new-york\", \"chicago\", \"topeka\"]) " + "scen.add_set(\"j\", [\"new-york\", \"chicago\", \"topeka\"])" ] }, { @@ -128,7 +129,7 @@ "outputs": [], "source": [ "# display the set 'i'\n", - "scen.set('i')" + "scen.set(\"i\")" ] }, { @@ -161,19 +162,19 @@ "metadata": {}, "outputs": [], "source": [ - "# capacity of plant i in cases \n", - "# add parameter elements one-by-one (string and value) \n", + "# capacity of plant i in cases\n", + "# add parameter elements one-by-one (string and value)\n", "scen.init_par(\"a\", idx_sets=\"i\")\n", "scen.add_par(\"a\", \"seattle\", 350, \"cases\")\n", "scen.add_par(\"a\", \"san-diego\", 600, \"cases\")\n", "\n", - "# demand at market j in cases \n", - "# add parameter elements as dataframe (with index names) \n", + "# demand at market j in cases\n", + "# add parameter elements as dataframe (with index names)\n", "scen.init_par(\"b\", idx_sets=\"j\")\n", "b_data = [\n", - " {'j': \"new-york\", 'value': 325, 'unit': \"cases\"},\n", - " {'j': \"chicago\", 'value': 300, 'unit': \"cases\"},\n", - " {'j': \"topeka\", 'value': 275, 'unit': \"cases\"}\n", + " {\"j\": \"new-york\", \"value\": 325, \"unit\": \"cases\"},\n", + " {\"j\": \"chicago\", \"value\": 300, \"unit\": \"cases\"},\n", + " {\"j\": \"topeka\", \"value\": 275, \"unit\": \"cases\"},\n", "]\n", "b = pd.DataFrame(b_data)\n", "scen.add_par(\"b\", b)" @@ -185,7 +186,7 @@ "metadata": {}, "outputs": [], "source": [ - "scen.par('b')" + "scen.par(\"b\")" ] }, { @@ -204,14 +205,14 @@ "metadata": {}, "outputs": [], "source": [ - "# distance in thousands of miles \n", + "# distance in thousands of miles\n", "scen.init_par(\"d\", idx_sets=[\"i\", \"j\"])\n", - "# add more parameter elements as dataframe by index names \n", + "# add more parameter elements as dataframe by index names\n", "d_data = [\n", - " {'i': \"seattle\", 'j': \"new-york\", 'value': 2.5, 'unit': \"km\"},\n", - " {'i': \"seattle\", 'j': \"chicago\", 'value': 1.7, 'unit': \"km\"},\n", - " {'i': \"seattle\", 'j': \"topeka\", 'value': 1.8, 'unit': \"km\"},\n", - " {'i': \"san-diego\", 'j': \"new-york\", 'value': 2.5, 'unit': \"km\"},\n", + " {\"i\": \"seattle\", \"j\": \"new-york\", \"value\": 2.5, \"unit\": \"km\"},\n", + " {\"i\": \"seattle\", \"j\": \"chicago\", \"value\": 1.7, \"unit\": \"km\"},\n", + " {\"i\": \"seattle\", \"j\": \"topeka\", \"value\": 1.8, \"unit\": \"km\"},\n", + " {\"i\": \"san-diego\", \"j\": \"new-york\", \"value\": 2.5, \"unit\": \"km\"},\n", "]\n", "d = pd.DataFrame(d_data)\n", "scen.add_par(\"d\", d)\n", @@ -223,9 +224,13 @@ }, { "cell_type": "raw", - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "raw" + } + }, "source": [ - "Scalar f freight in dollars per case per thousand miles /90/ ; " + "Scalar f freight in dollars per case per thousand miles /90/ ;" ] }, { @@ -234,8 +239,8 @@ "metadata": {}, "outputs": [], "source": [ - "# cost per case per 1000 miles \n", - "# initialize scalar with a value and a unit (and optionally a comment) \n", + "# cost per case per 1000 miles\n", + "# initialize scalar with a value and a unit (and optionally a comment)\n", "scen.init_scalar(\"f\", 90.0, \"USD/km\")" ] }, @@ -255,8 +260,8 @@ "# commit new scenario to the database\n", "# no changes can then be made to the scenario data until a check-out is performed\n", "comment = \"importing Dantzig's transport problem for illustration\"\n", - "comment += \" and testing of the Python interface using a generic datastructure\" \n", - "scen.commit(comment) \n", + "comment += \" and testing of the Python interface using a generic datastructure\"\n", + "scen.commit(comment)\n", "\n", "# set this new scenario as the default version for the model/scenario name\n", "scen.set_as_default()" @@ -273,12 +278,16 @@ }, { "cell_type": "raw", - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "raw" + } + }, "source": [ "Variables\n", " x(i,j) shipment quantities in cases\n", " z total transportation costs in thousands of dollars ;\n", - " \n", + "\n", "Equations\n", " cost define objective function\n", " supply(i) observe supply limit at plant i\n", @@ -321,7 +330,7 @@ "metadata": {}, "outputs": [], "source": [ - "scen.solve(model='dantzig')" + "scen.solve(model=\"dantzig\")" ] }, { @@ -357,7 +366,8 @@ "metadata": {}, "outputs": [], "source": [ - "# display the quantities and marginals (=shadow prices) of the demand balance constraints\n", + "# Display the quantities and marginals (=shadow prices) of the demand balance\n", + "# constraints\n", "scen.equ(\"demand\")" ] }, diff --git a/tutorial/transport/py_transport_scenario.ipynb b/tutorial/transport/py_transport_scenario.ipynb index 23d2e075c..e75cd95ba 100644 --- a/tutorial/transport/py_transport_scenario.ipynb +++ b/tutorial/transport/py_transport_scenario.ipynb @@ -38,8 +38,7 @@ "metadata": {}, "outputs": [], "source": [ - "# load required packages\n", - "import pandas as pd\n", + "# Import required packages\n", "import ixmp" ] }, @@ -60,8 +59,8 @@ "outputs": [], "source": [ "# Model and scenario name for Dantzig's transport problem\n", - "model = 'canning problem'\n", - "scenario = 'standard'" + "model = \"canning problem\"\n", + "scenario = \"standard\"" ] }, { @@ -106,7 +105,8 @@ "outputs": [], "source": [ "from ixmp.testing import make_dantzig\n", - "scen = make_dantzig(mp, solve='.')" + "\n", + "scen = make_dantzig(mp, solve=\".\")" ] }, { @@ -135,8 +135,9 @@ "metadata": {}, "outputs": [], "source": [ - "# show only the distances for connections from Seattle by filtering the pandas.DataFrame returned above\n", - "d[d['i'] == \"seattle\"]" + "# Show only the distances for connections from Seattle by filtering the pandas.DataFrame\n", + "# returned above\n", + "d[d[\"i\"] == \"seattle\"]" ] }, { @@ -148,8 +149,8 @@ "# for faster access or more complex filtering,\n", "# it may be easier to only load specific parameter elements using a dictionary\n", "ele_filter = {}\n", - "ele_filter['i'] = ['seattle']\n", - "ele_filter['j'] = ['chicago', 'topeka']\n", + "ele_filter[\"i\"] = [\"seattle\"]\n", + "ele_filter[\"j\"] = [\"chicago\", \"topeka\"]\n", "\n", "d_filtered = scen.par(\"d\", ele_filter)\n", "d_filtered" @@ -172,7 +173,12 @@ "outputs": [], "source": [ "# create a new scenario by cloning the scenario (without keeping the solution)\n", - "scen_detroit = scen.clone(model=model, scenario='detroit', annotation='extend the Transport problem by a new city', keep_solution=False)" + "scen_detroit = scen.clone(\n", + " model=model,\n", + " scenario=\"detroit\",\n", + " annotation=\"extend the Transport problem by a new city\",\n", + " keep_solution=False,\n", + ")" ] }, { @@ -192,13 +198,13 @@ "outputs": [], "source": [ "# reduce demand in chicago\n", - "scen_detroit.add_par('b', 'chicago', 200, 'cases')\n", + "scen_detroit.add_par(\"b\", \"chicago\", 200, \"cases\")\n", "\n", "# add a new city with demand and distances\n", - "scen_detroit.add_set('j', 'detroit')\n", - "scen_detroit.add_par('b', 'detroit', 150, 'cases')\n", - "scen_detroit.add_par('d', ['seattle', 'detroit'], 1.7, 'cases')\n", - "scen_detroit.add_par('d', ['san-diego', 'detroit'], 1.9, 'cases')" + "scen_detroit.add_set(\"j\", \"detroit\")\n", + "scen_detroit.add_par(\"b\", \"detroit\", 150, \"cases\")\n", + "scen_detroit.add_par(\"d\", [\"seattle\", \"detroit\"], 1.7, \"cases\")\n", + "scen_detroit.add_par(\"d\", [\"san-diego\", \"detroit\"], 1.9, \"cases\")" ] }, { @@ -226,7 +232,7 @@ "metadata": {}, "outputs": [], "source": [ - "scen_detroit.solve(model='dantzig')" + "scen_detroit.solve(model=\"dantzig\")" ] }, { @@ -249,21 +255,21 @@ "outputs": [], "source": [ "# display the objective value of the solution in the baseline scenario\n", - "scen.var('z')" + "scen.var(\"z\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": { - "jupyter": { - "name": "scen-detroit-z" - } + "jupyter": { + "name": "scen-detroit-z" + } }, "outputs": [], "source": [ "# display the objective value of the solution in the \"detroit\" scenario\n", - "scen_detroit.var('z')" + "scen_detroit.var(\"z\")" ] }, { @@ -272,8 +278,9 @@ "metadata": {}, "outputs": [], "source": [ - "# display the quantities transported from canning plants to demand locations in the baseline scenario\n", - "scen.var('x')" + "# Display the quantities transported from canning plants to demand locations in the\n", + "# baseline scenario\n", + "scen.var(\"x\")" ] }, { @@ -282,8 +289,9 @@ "metadata": {}, "outputs": [], "source": [ - "# display the quantities transported from canning plants to demand locations in the \"detroit\" scenario\n", - "scen_detroit.var('x')" + "# Display the quantities transported from canning plants to demand locations in the\n", + "# \"detroit\" scenario\n", + "scen_detroit.var(\"x\")" ] }, { @@ -292,7 +300,8 @@ "metadata": {}, "outputs": [], "source": [ - "# display the quantities and marginals (=shadow prices) of the demand balance constraints in the baseline scenario\n", + "# Display the quantities and marginals (=shadow prices) of the demand balance\n", + "# constraints in the baseline scenario\n", "scen.equ(\"demand\")" ] }, @@ -302,7 +311,8 @@ "metadata": {}, "outputs": [], "source": [ - "# display the quantities and marginals (=shadow prices) of the demand balance constraints in the \"detroit\" scenario\n", + "# Display the quantities and marginals (=shadow prices) of the demand balance\n", + "# constraints in the \"detroit\" scenario\n", "scen_detroit.equ(\"demand\")" ] },