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    "src/cubedynamics/verbs/biology.py": "42ea84cc706f7c059dfa71a01de38f103f5332c50d8587b8871a4bbeaa40e109",
    "src/cubedynamics/verbs/combine.py": "c05747b9305a9fb03361e799dd752388919233e0ed4b3188e20a49455b8f3351",
    "src/cubedynamics/verbs/custom.py": "63633b70eef925fe3e970e686605bb6b59c633ea2cb234846b6848f14d99629e",
    "src/cubedynamics/verbs/diagnostics.py": "ac443170252fa856c0e9a960ad2dcf6ed9d5273c742063afffccf3eb3227499f",
    "src/cubedynamics/verbs/events.py": "fdb698fcce64cdfe77541be6c59cc361e3080cc5fd324fde866afafb800a5daa",
    "src/cubedynamics/verbs/fire.py": "34fc19d999002b519badd68e2edf19c3ac83f489d023bf659e6876b04089ea1e",
    "src/cubedynamics/verbs/flatten.py": "9d2b60deed812b1ce892364b94fe4a56c91b4d186ce0e4d125461f8f362bcda4",
    "src/cubedynamics/verbs/landsat_mpc.py": "5d7a1fb6fd22711f7e76d6ff7399fe72dd4fe73516949cebbd9559ae75f43446",
    "src/cubedynamics/verbs/models.py": "1b7308169df32ba6357019a15dab46b6d2dc636b8ad0e08a4ba92e0dbe1644f9",
    "src/cubedynamics/verbs/plot.py": "a72f0f982ea91b3a71a65ed2b38db6667415839c0a3feac359633b245b706cce",
    "src/cubedynamics/verbs/plot_mean.py": "551bed3b922028207d6bfad6f5f31cef6036222c3469dbae029724f1cd6ee50e",
    "src/cubedynamics/verbs/states.py": "47b06f52f096147a8bc21eaf641872ee35270994c0dff38a1a20d5c17993f40a",
    "src/cubedynamics/verbs/stats.py": "e3c4190b9113886477c11dbefea14af6b3c76a2c77e637c3b583b7fee5b23153",
    "src/cubedynamics/verbs/synchrony.py": "66df50f622cbc6968ca156d2a1b08d93bb82103148e53bc22bdcb1d5f3839bd6",
    "src/cubedynamics/verbs/tubes.py": "148c26bf82aa8a8e71f65586bae2f417f83314cef0cb3c07f0ac9436f6282fa4",
    "src/cubedynamics/verbs/vase.py": "b9b7a1580b6774dec533daa7438f4dc54ecf8707f4f265f7809b4bba6d2d11cf",
    "src/cubedynamics/version.py": "5aff1387d57ebdb1b6b9713a8d9567f37c2f8e767e9a01be65a30cbb967b8296",
    "src/cubedynamics/viewers/__init__.py": "5a53d090c36d3c8b4303204da667226b996c3bc23bbb2342732e7486d68deadd",
    "src/cubedynamics/viewers/cube_viewer.py": "8505d96f14e8c0fc196776d0cce9d8859179404ff10e2e805074c118526f1306",
    "src/cubedynamics/viewers/simple_plot.py": "7dc6c90d34cba1b600c31f4c122ac85da2f46844d6b016b881aa1b93426e1ab9",
    "src/cubedynamics/viz/__init__.py": "b957afd6ca1c8c7e72d72d16c4af6d996efa8602e17e7d0edba33149405534e3",
    "src/cubedynamics/viz/lexcube_viz.py": "16f42bf21ec4be34632a2fb70ba3e1e4aea35501edc2615dfd59cb1669ff88a4",
    "src/cubedynamics/viz/qa_plots.py": "cb9d8f00e446f7cda6e84b7a39b08ba66f95348a2bde29a6317b90697a9d378c",
    "tests/fixtures/real_data/gridmet_badlands_july_2001.nc": "a36b2c4e1164d0a85429bc855fd94b32eb708a0f72e6be96f4959fc92bfe2721",
    "tests/fixtures/real_data/gridmet_badlands_july_2001.provenance.json": "fa13beaad547747eeaf7764b1b08bb481ca08bc3fc97761fa153bd90c6370888",
    "tests/fixtures/real_data/prism_boulder_january_2024.nc": "630b8857d8e0e66409bed3c03194ead009506d093adae5411f39727e0c0e4cf7",
    "tests/fixtures/real_data/prism_boulder_january_2024.provenance.json": "a06bf922f0b5524ab7e53d740c1f869d7e8d9c95be934cde62b1ae7143691127"
  },
  "policy": "Generated real-data teaching results; fixture QA is not live-source certification.",
  "results": {
    "anomaly": {
      "caption": "PRISM, Boulder, 16 January 2024: absolute maximum temperature above and anomaly below. anomaly() subtracts each pixel\u2019s 10\u201320 January mean; the diverging scale is centered on zero.",
      "example_key": "anomaly",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\nwindow = (pipe(cube)\n          | v.apply(lambda c: c.sel(time=slice(\"2024-01-10\", \"2024-01-20\")))).unwrap()\nassert window.sizes[\"time\"] == 11\ndepartures = (pipe(window) | v.anomaly(dim=\"time\")).unwrap()\n\nfig, axes = plt.subplots(2, 1, figsize=(5.4, 6.5), layout=\"constrained\")\nwindow.sel(time=\"2024-01-16\").plot(ax=axes[0], cmap=\"magma\", cbar_kwargs={\"label\": \"\u00b0C\"})\ndepartures.sel(time=\"2024-01-16\").plot(ax=axes[1], cmap=\"RdBu_r\", center=0,\n                                    cbar_kwargs={\"label\": \"Departure (\u00b0C)\"})\nfor ax, title in zip(axes, [\"Before \u00b7 absolute temperature\", \"After anomaly() \u00b7 local departure\"]):\n    ax.set(title=title, xlabel=\"Longitude (\u00b0E)\", ylabel=\"Latitude (\u00b0N)\")\nplt.show()",
      "fixtures": [
        "prism_boulder_january_2024"
      ],
      "input_type": "REAL DATA",
      "interpretation": "Negative departures mean colder than that pixel\u2019s baseline. The coldest absolute location need not have the largest departure. A short event-window baseline is not a long-term climate normal.",
      "kind": "figure",
      "output": "anomaly.png",
      "producer": "scripts/build_visual_docs.py",
      "requires": [
        "subset"
      ],
      "sha256": "8f29dc3005a97114783fa4de28217bfd638982baece98962629a9f3c250f0888",
      "source_code": "scripts/visual_examples.py"
    },
    "export": {
      "caption": "The PRISM regional-anomaly result is written with to_netcdf() and reopened. An identity assertion checks values, coordinates, names and attributes; the temporary example file is then removed.",
      "example_key": "export",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\nwindow = (pipe(cube)\n          | v.apply(lambda c: c.sel(time=slice(\"2024-01-10\", \"2024-01-20\")))).unwrap()\nassert window.sizes[\"time\"] == 11\ndepartures = (pipe(window) | v.anomaly(dim=\"time\")).unwrap()\nregional_anomaly = (pipe(departures)\n                    | v.mean(dim=(\"y\", \"x\"), keep_dim=False)).unwrap()\nassert regional_anomaly.dims == (\"time\",)\nfrom tempfile import TemporaryDirectory\nwith TemporaryDirectory() as directory:\n    target = Path(directory) / \"regional_anomaly.nc\"\n    saved = (pipe(regional_anomaly) | v.to_netcdf(str(target), engine=\"scipy\")).unwrap()\n    with xr.open_dataarray(target, engine=\"scipy\") as reopened:\n        restored = reopened.load()\n    xr.testing.assert_identical(saved, restored)\noutput_table = pd.DataFrame({\n    \"Check\": [\"Dimensions\", \"Observations\", \"Values and metadata\"],\n    \"Before\": [str(saved.dims), str(saved.size), \"Reference result\"],\n    \"After reopening\": [str(restored.dims), str(restored.size), \"Identical (asserted)\"],\n})\n\ndisplay(output_table)",
      "fixtures": [
        "prism_boulder_january_2024"
      ],
      "input_type": "REAL DATA",
      "interpretation": "Export is an explicit side effect. The compact table is more useful here than another identical curve: it reports the tested round trip.",
      "kind": "table",
      "output": "export.json",
      "producer": "scripts/build_visual_docs.py",
      "requires": [
        "summary"
      ],
      "sha256": "b4387cc2e3adf9ff4cc99c8e812758ccb981a2479b17b0b925f43f26b7b882bc",
      "source_code": "scripts/visual_examples.py"
    },
    "observed": {
      "caption": "Real PRISM daily maximum temperature, Boulder region, 16 January 2024. Selecting a date exposes one spatial face of the cube; north is up.",
      "example_key": "observed",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\n\nfield = cube.sel(time=\"2024-01-16\")\n\nfig, ax = plt.subplots(figsize=(5.4, 3.8), layout=\"constrained\")\nfield.plot(ax=ax, cmap=\"magma\", cbar_kwargs={\"label\": \"Daily maximum (\u00b0C)\"})\nax.set(title=\"PRISM \u00b7 Boulder \u00b7 16 January 2024\",\n       xlabel=\"Longitude (\u00b0E)\", ylabel=\"Latitude (\u00b0N)\")\nplt.show()",
      "fixtures": [
        "prism_boulder_january_2024"
      ],
      "input_type": "REAL DATA",
      "interpretation": "Each cell is a gridded estimate, not a station reading. This map shows absolute temperature; it does not yet say how unusual the day was.",
      "kind": "figure",
      "output": "observed.png",
      "producer": "scripts/build_visual_docs.py",
      "requires": [],
      "sha256": "c39f7db0404eef5014870de84c7669e1c486bc223775552973212c12916948ce",
      "source_code": "scripts/visual_examples.py"
    },
    "sources": {
      "caption": "Two real, source-QA fixtures in their native temperature units and geographic grids. Their places and dates differ; each panel has its own color scale. This is a support check, not evidence of source bias or agreement.",
      "example_key": "sources",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\n\ngridmet = observed_cube(\"gridmet_badlands_july_2001\", \"temperature\")\nassert gridmet.attrs[\"units\"] == \"K\"\n# No conversion, resampling, or date alignment is hidden here.\nassert not np.intersect1d(cube.time.values, gridmet.time.values).size\n\nfig, axes = plt.subplots(2, 1, figsize=(5.4, 6.5), layout=\"constrained\")\ncube.isel(time=0).plot(ax=axes[0], cmap=\"magma\", cbar_kwargs={\"label\": \"PRISM (\u00b0C)\"})\ngridmet.isel(time=0).plot(ax=axes[1], cmap=\"magma\", cbar_kwargs={\"label\": \"gridMET (K)\"})\nfor ax, title in zip(axes, [\"PRISM \u00b7 Boulder \u00b7 1 January 2024\", \"gridMET \u00b7 Badlands \u00b7 1 July 2001\"]):\n    ax.set(title=title, xlabel=\"Longitude (\u00b0E)\", ylabel=\"Latitude (\u00b0N)\")\nplt.show()",
      "fixtures": [
        "prism_boulder_january_2024",
        "gridmet_badlands_july_2001"
      ],
      "input_type": "REAL DATA",
      "interpretation": "These samples cannot support a paired temperature comparison. Obtain overlapping AOIs and dates, explicitly convert K to \u00b0C, and choose a spatial alignment method before comparing products. Native grid cells are approximately 4 km, not identical spatial support.",
      "kind": "figure",
      "output": "sources.png",
      "producer": "scripts/build_visual_docs.py",
      "requires": [],
      "sha256": "a681888f013aa038ad1a9f6b7725615e78fb8e3301ef5d3cefa84733bc0975ab",
      "source_code": "scripts/visual_examples.py"
    },
    "standardize": {
      "caption": "All PRISM grid-cell days in the selected window, before and after per-pixel zscore(). Histograms show distributions on different, explicitly labeled scales; the code asserts equivalence to the direct formula.",
      "example_key": "standardize",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\nwindow = (pipe(cube)\n          | v.apply(lambda c: c.sel(time=slice(\"2024-01-10\", \"2024-01-20\")))).unwrap()\nassert window.sizes[\"time\"] == 11\nstandardized = (pipe(window) | v.zscore(dim=\"time\")).unwrap()\ndirect = (window - window.mean(\"time\")) / window.std(\"time\")\nnp.testing.assert_allclose(standardized, direct, rtol=1e-6, atol=1e-6)\n# Standardization is dimensionless; replace the inherited temperature label.\nstandardized.attrs[\"units\"] = \"1\"\n\nfig, axes = plt.subplots(2, 1, figsize=(5.4, 5.8), layout=\"constrained\")\naxes[0].hist(window.values.ravel(), bins=24, color=\"#246b70\")\naxes[1].hist(standardized.values.ravel(), bins=24, color=\"#246b70\")\naxes[0].set(title=\"Before \u00b7 selected PRISM values\", xlabel=\"Daily maximum (\u00b0C)\", ylabel=\"Cell-days\")\naxes[1].set(title=\"After zscore() \u00b7 per-pixel scaling\", xlabel=\"Standard deviations (unitless)\", ylabel=\"Cell-days\")\nplt.show()",
      "fixtures": [
        "prism_boulder_january_2024"
      ],
      "input_type": "REAL DATA",
      "interpretation": "Each pixel is centered and scaled by its own temporal variability. The pooled histogram is not fitted to a normal distribution, and its cell-days are not independent samples.",
      "kind": "figure",
      "output": "standardize.png",
      "producer": "scripts/build_visual_docs.py",
      "requires": [
        "subset"
      ],
      "sha256": "5ef887050f99ba972339378585c0af2b97ef03b61a009d3c0e736f4cc7352cd1",
      "source_code": "scripts/visual_examples.py"
    },
    "subset": {
      "caption": "PRISM maximum temperature at one Boulder grid cell. The apply/sel stage retains 10\u201320 January 2024 (colored markers) without changing their values.",
      "example_key": "subset",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\n\nwindow = (pipe(cube)\n          | v.apply(lambda c: c.sel(time=slice(\"2024-01-10\", \"2024-01-20\")))).unwrap()\nassert window.sizes[\"time\"] == 11\n\nfig, ax = plt.subplots(figsize=(5.4, 3.4), layout=\"constrained\")\ncube.isel(y=12, x=12).plot(ax=ax, color=\"0.65\", label=\"Full fixture\")\nwindow.isel(y=12, x=12).plot(ax=ax, marker=\"o\", color=\"#246b70\", label=\"Selected days\")\nax.set(title=\"One grid cell \u00b7 select 10\u201320 January\", xlabel=\"Date\", ylabel=\"Daily maximum (\u00b0C)\")\nax.legend(frameon=False)\nplt.show()",
      "fixtures": [
        "prism_boulder_january_2024"
      ],
      "input_type": "REAL DATA",
      "interpretation": "The grey observations remain in cube but not window. Subsequent anomalies use these eleven selected days, not the entire month or a climatology.",
      "kind": "figure",
      "output": "subset.png",
      "producer": "scripts/build_visual_docs.py",
      "requires": [],
      "sha256": "2d698dcd1c57101739112ecd75f019df752a23ae9af0b55166f25479b8dbeeab",
      "source_code": "scripts/visual_examples.py"
    },
    "summary": {
      "caption": "The mean verb reduces PRISM y and x to a daily series for 10\u201320 January. The plotted quantity is the unweighted mean of grid-cell anomalies, in \u00b0C.",
      "example_key": "summary",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\nwindow = (pipe(cube)\n          | v.apply(lambda c: c.sel(time=slice(\"2024-01-10\", \"2024-01-20\")))).unwrap()\nassert window.sizes[\"time\"] == 11\ndepartures = (pipe(window) | v.anomaly(dim=\"time\")).unwrap()\nregional_anomaly = (pipe(departures)\n                    | v.mean(dim=(\"y\", \"x\"), keep_dim=False)).unwrap()\nassert regional_anomaly.dims == (\"time\",)\n\nfig, ax = plt.subplots(figsize=(5.4, 3.4), layout=\"constrained\")\nregional_anomaly.plot(ax=ax, marker=\"o\", color=\"#246b70\")\nax.axhline(0, color=\"0.5\", linewidth=0.8)\nax.set(title=\"After mean() \u00b7 grid-cell average anomaly\", xlabel=\"Date\", ylabel=\"Departure (\u00b0C)\")\nplt.show()",
      "fixtures": [
        "prism_boulder_january_2024"
      ],
      "input_type": "REAL DATA",
      "interpretation": "Space has disappeared from the result, but time remains. This is an equal-cell average on a latitude/longitude grid, not an area-weighted regional estimate.",
      "kind": "figure",
      "output": "summary.png",
      "producer": "scripts/build_visual_docs.py",
      "requires": [
        "anomaly"
      ],
      "sha256": "99a4eafcb46696faaf977a75293fe5f39bdc3d1e2e72ed97204e486eaf1517a7",
      "source_code": "scripts/visual_examples.py"
    },
    "threshold": {
      "caption": "One Boulder PRISM grid cell in January 2024: daily maximum temperature becomes a boolean state. direction='below' includes equality (\u2264 0\u00b0C), verified against the original values.",
      "example_key": "threshold",
      "execution_code": "from pathlib import Path\nimport hashlib\nimport json\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\nimport matplotlib.pyplot as plt\nfrom IPython.display import display\nfrom cubedynamics import pipe, verbs as v\n\n# Run in the cloned repository or beside a downloaded notebook in the repo.\nrepo = next(p for p in (Path.cwd(), *Path.cwd().parents)\n            if (p / \"tests/fixtures/real_data\").is_dir())\n\ndef observed_cube(stem, variable):\n    path = repo / \"tests/fixtures/real_data\" / (stem + \".nc\")\n    record = json.loads(path.with_suffix(\".provenance.json\").read_text())\n    assert hashlib.sha256(path.read_bytes()).hexdigest() == record[\"fixture_sha256\"]\n    with xr.open_dataset(path, engine=\"scipy\") as dataset:\n        assert not dataset.attrs[\"is_synthetic\"]\n        result = dataset[variable].load()  # Only this small, reviewed local extract.\n        result.attrs = {**dataset.attrs, **result.attrs}\n    assert result.dims == (\"time\", \"y\", \"x\")\n    assert np.all(np.diff(result.x) > 0) and np.all(np.diff(result.y) < 0)\n    assert bool(np.isfinite(result).all())\n    return result\n\ncube = observed_cube(\"prism_boulder_january_2024\", \"tmax\").rename(\"temperature\")\nassert cube.attrs[\"units\"] == \"degC\"\n\nplt.rcParams.update({'font.family': 'DejaVu Sans', 'font.size': 12, 'axes.titlesize': 13, 'axes.labelsize': 12, 'figure.facecolor': 'white', 'axes.facecolor': 'white', 'savefig.facecolor': 'white', 'figure.dpi': 140})\n\ncold = (pipe(cube) | v.threshold_state(threshold=0, direction=\"below\")).unwrap()\nsite = cube.isel(y=12, x=12)\nstate = cold.state.isel(y=12, x=12)\nnp.testing.assert_array_equal(state, site <= 0)\n\nfig, axes = plt.subplots(2, 1, figsize=(5.4, 5.4), sharex=True, layout=\"constrained\")\nsite.plot(ax=axes[0], color=\"#246b70\", marker=\"o\")\naxes[0].axhline(0, color=\"0.4\", linestyle=\"--\", label=\"Threshold: 0\u00b0C\")\naxes[0].set(title=\"Before \u00b7 PRISM daily maximum\", ylabel=\"Temperature (\u00b0C)\", xlabel=\"\")\naxes[0].legend(frameon=False)\naxes[1].step(state.time, state.astype(int), where=\"mid\", color=\"#246b70\")\naxes[1].set(title=\"After threshold_state() \u00b7 at or below 0\u00b0C\", xlabel=\"Date\", ylabel=\"State\", yticks=[0, 1], ylim=(-0.1, 1.1))\nplt.show()",
      "fixtures": [
        "prism_boulder_january_2024"
      ],
      "input_type": "REAL DATA",
      "interpretation": "A true state describes a criterion, not an event duration or an ecological impact. This complete fixture has no missing values; missing-data policy must be checked for other inputs.",
      "kind": "figure",
      "output": "threshold.png",
      "producer": "scripts/build_visual_docs.py",
      "requires": [],
      "sha256": "b79766fc148b9c0bb77f62a647404888ac4ba0db94aa669ca88210fe038e652a",
      "source_code": "scripts/visual_examples.py"
    }
  },
  "schema_version": 1,
  "scientific_qa": "python scripts/run_source_qa.py (same reviewed PRISM/gridMET inputs)"
}