{ "cells": [ { "cell_type": "markdown", "id": "cb5f4d23", "metadata": {}, "source": [ "# Animal movement: a continuum the HMM cannot represent\n", "\n", "Animal behaviour is commonly inferred from a GPS track using a Hidden Markov Model, as implemented in the `moveHMM` and `momentuHMM` packages. Each step is assigned to one of K discrete behavioural states — classically two, *encamped/foraging* and *exploratory/transit* — each with its own step-length distribution and a matrix of state-to-state transition probabilities. This approach has two limitations. First, the number of states K must be fixed in advance, and selecting it is difficult, as common criteria such as AIC and BIC often disagree. Second, behaviour is sorted into discrete categories, so variation within a state and gradual transitions between states are not represented.\n", "\n", "Here we take a different approach with *bayesloop* and treat the movement scale itself as a continuous, time-varying parameter. It is inferred together with its uncertainty, and the model evidence is used to decide whether the dynamics are static, gradually drifting, or abruptly switching, without fixing a number of states in advance. We model the 6-hourly step length as Rayleigh-distributed (the exact law of the distance moved under 2-D isotropic Gaussian increments, and rotation-invariant, so directional persistence does not bias it) with a time-varying scale $D_t$. In the course of the analysis we use a custom `bl.om.NumPy` observation model, a `HyperStudy` over the smoothness of the drift, and `RegimeSwitch`, and we select the kind of dynamics based on the evidence. We then benchmark the result against a 2-state Gaussian HMM fitted with `hmmlearn`.\n", "\n", "
\n", "**Note:** Unlike the other case studies, this one cannot run interactively in the browser: the [pyreadr](https://github.com/ofajardo/pyreadr) and [hmmlearn](https://github.com/hmmlearn/hmmlearn) packages rely on compiled code that the in-browser Python session cannot load. To try the analysis yourself, download the notebook from the [GitHub repository](https://github.com/christophmark/bayesloop) and run it locally.\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "id": "58172af9", "metadata": { "execution": { "iopub.execute_input": "2026-06-12T09:53:29.493946Z", "iopub.status.busy": "2026-06-12T09:53:29.493860Z", "iopub.status.idle": "2026-06-12T09:53:30.908822Z", "shell.execute_reply": "2026-06-12T09:53:30.908337Z" } }, "outputs": [], "source": [ "%matplotlib inline\n", "import io\n", "import urllib.request\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "\n", "import bayesloop as bl\n", "\n", "try:\n", " import seaborn as sns\n", " sns.set_style(\"whitegrid\")\n", "except ImportError:\n", " plt.style.use(\"default\")\n", "mpl.rcParams.update({\n", " \"figure.dpi\": 110, \"font.size\": 10.5, \"axes.titlesize\": 12,\n", " \"axes.titleweight\": \"bold\", \"axes.edgecolor\": \"#444444\", \"grid.color\": \"#d9d9d9\",\n", "})\n", "C = {\"data\": \"#8a8a8a\", \"accent\": \"#c1272d\", \"accent2\": \"#0b6e99\",\n", " \"green\": \"#2e7d32\", \"amber\": \"#e8a33d\", \"muted\": \"#8a8a8a\",\n", " \"band\": \"#c1272d\", \"band2\": \"#0b6e99\"}\n", "\n", "\n", "def posterior_band(S, name, lo=0.05, hi=0.95):\n", " \"\"\"Posterior mean and an equal-tailed credible band for a time-varying parameter.\"\"\"\n", " x, p = S.get_parameter_distributions(name, density=False)\n", " p = np.asarray(p, dtype=float)\n", " p /= p.sum(axis=1, keepdims=True)\n", " mean = (p * x[None, :]).sum(axis=1)\n", " cdf = np.cumsum(p, axis=1)\n", " low = np.array([np.interp(lo, cdf[t], x) for t in range(p.shape[0])])\n", " high = np.array([np.interp(hi, cdf[t], x) for t in range(p.shape[0])])\n", " return mean, low, high\n", "\n", "\n", "def prob_in(S, name, lo=None, hi=None):\n", " \"\"\"Posterior probability the parameter lies in (lo, hi] at each time step.\"\"\"\n", " x, p = S.get_parameter_distributions(name, density=False)\n", " p = np.asarray(p, dtype=float)\n", " p /= p.sum(axis=1, keepdims=True)\n", " mask = np.ones_like(x, dtype=bool)\n", " if lo is not None:\n", " mask &= x > lo\n", " if hi is not None:\n", " mask &= x <= hi\n", " return p[:, mask].sum(axis=1)" ] }, { "cell_type": "markdown", "id": "747e99b5", "metadata": {}, "source": [ "## The data\n", "\n", "We use a red-deer GPS track with 6-hourly fixes from the `amt` R package (Signer, Fieberg & Avgar, *Ecology & Evolution* 2019). The dataset ships as an `.rda` file on CRAN's GitHub mirror; we download the bytes and read the embedded data frame with `pyreadr`, so this cell is fully self-contained. The frame has projected coordinates `x_`, `y_` (metres) and a timestamp `t_`.\n", "\n", "From the raw fixes we compute the step length $L_t = \\sqrt{\\Delta x^2 + \\Delta y^2}$ between consecutive fixes, and keep only the regular ~6-hour steps (dropping gaps and burst breaks). That step-length series is what both bayesloop and the HMM will model." ] }, { "cell_type": "code", "execution_count": 2, "id": "e06bf8e3", "metadata": { "execution": { "iopub.execute_input": "2026-06-12T09:53:30.910455Z", "iopub.status.busy": "2026-06-12T09:53:30.910332Z", "iopub.status.idle": "2026-06-12T09:53:31.012498Z", "shell.execute_reply": "2026-06-12T09:53:31.012046Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "804 regular 6h steps; step length median 174 m, p10 24, p90 980\n" ] } ], "source": [ "import tempfile\n", "import os\n", "\n", "import pyreadr\n", "\n", "url = \"https://raw.githubusercontent.com/cran/amt/master/data/deer.rda\"\n", "req = urllib.request.Request(url, headers={\"User-Agent\": \"Mozilla/5.0 (bayesloop docs)\"})\n", "raw = urllib.request.urlopen(req, timeout=90).read()\n", "with tempfile.NamedTemporaryFile(suffix=\".rda\", delete=False) as _f:\n", " _f.write(raw)\n", " _tmp = _f.name\n", "d = pyreadr.read_r(_tmp)[\"deer\"]\n", "os.remove(_tmp)\n", "\n", "d[\"t_\"] = pd.to_datetime(d[\"t_\"])\n", "d = d.sort_values(\"t_\").reset_index(drop=True)\n", "dt_h = d[\"t_\"].diff().dt.total_seconds() / 3600.0\n", "dx = d[\"x_\"].diff().values\n", "dy = d[\"y_\"].diff().values\n", "L = np.hypot(dx, dy)\n", "# keep regular 6h steps only (drop gaps / burst breaks)\n", "ok = (dt_h.values > 4) & (dt_h.values < 9) & np.isfinite(L)\n", "L = L[ok]\n", "t = d[\"t_\"].values[np.where(ok)[0]]\n", "xy = d[[\"x_\", \"y_\"]].values[np.where(ok)[0]]\n", "print(f\"{len(L)} regular 6h steps; step length median {np.median(L):.0f} m, \"\n", " f\"p10 {np.percentile(L,10):.0f}, p90 {np.percentile(L,90):.0f}\")" ] }, { "cell_type": "markdown", "id": "23384e85", "metadata": {}, "source": [ "## A time-varying Rayleigh scale, and letting the evidence choose the dynamics\n", "\n", "Our observation model is a Rayleigh distribution with scale $D$, the movement intensity or diffusivity. We supply it to bayesloop as a one-line custom `bl.om.NumPy` model evaluating the Rayleigh density on a grid of $D$ values:\n", "\n", "```python\n", "bl.om.NumPy(rayleigh, \"D\", bl.oint(2.0, 2000.0, 280))\n", "```\n", "\n", "We then fit three competing hypotheses for the dynamics of $D_t$, all sharing the identical observation model and data so their log₁₀ evidences are directly comparable:\n", "\n", "| Hypothesis | Transition model |\n", "|---|---|\n", "| Static (null) | `tm.Static()` |\n", "| Gradual drift (continuous) | `tm.GaussianRandomWalk` inside a `HyperStudy` |\n", "| Regime switch (discrete-like) | `tm.RegimeSwitch` |\n", "\n", "The `HyperStudy` marginalises over the unknown smoothness `sigma` of the random walk, so we do not have to hand-tune how fast the movement scale is allowed to drift." ] }, { "cell_type": "code", "execution_count": 3, "id": "f141976a", "metadata": { "execution": { "iopub.execute_input": "2026-06-12T09:53:31.013575Z", "iopub.status.busy": "2026-06-12T09:53:31.013493Z", "iopub.status.idle": "2026-06-12T09:53:31.976898Z", "shell.execute_reply": "2026-06-12T09:53:31.976488Z" }, "lines_to_next_cell": 2 }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "+ Created new study.\n", "+ Successfully imported array.\n", "+ Observation model: rayleigh. Parameter(s): ('D',)\n", "+ Transition model: Static/constant parameter values. Hyper-Parameter(s): []\n", "+ Created new study.\n", " --> Hyper-study\n", "+ Successfully imported array.\n", "+ Observation model: rayleigh. Parameter(s): ('D',)\n", "+ Transition model: Gaussian random walk. Hyper-Parameter(s): ['sigma']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "+ Created new study.\n", "+ Successfully imported array.\n", "+ Observation model: rayleigh. Parameter(s): ('D',)\n", "+ Transition model: Regime-switching model. Hyper-Parameter(s): ['log10p_min']\n" ] } ], "source": [ "def rayleigh(data, D):\n", " return (data / D ** 2) * np.exp(-(data ** 2) / (2.0 * D ** 2))\n", "\n", "def obs():\n", " return bl.om.NumPy(rayleigh, \"D\", bl.oint(2.0, 2000.0, 280))\n", "\n", "# model selection over the kind of dynamics\n", "S_static = bl.Study(); S_static.load_data(L); S_static.set(obs(), bl.tm.Static()); S_static.fit(silent=True)\n", "S_grad = bl.HyperStudy(); S_grad.load_data(L)\n", "S_grad.set(obs(), bl.tm.GaussianRandomWalk(\"sigma\", bl.cint(0, 200, 30), target=\"D\")); S_grad.fit(silent=True)\n", "S_reg = bl.Study(); S_reg.load_data(L); S_reg.set(obs(), bl.tm.RegimeSwitch(\"log10p_min\", -4)); S_reg.fit(silent=True)\n", "\n", "D_mean, D_lo, D_hi = posterior_band(S_grad, \"D\")\n", "# Express the inferred Rayleigh scale as a step length so it is directly comparable to the\n", "# HMM (which clusters step lengths). For a Rayleigh(D) the MEDIAN step is D*sqrt(2 ln2);\n", "# the mean is D*sqrt(pi/2). We compare on the median throughout (see the HMM block below).\n", "MEDF = np.sqrt(2.0 * np.log(2.0)) # Rayleigh median-step / scale\n", "med_step, med_lo, med_hi = D_mean * MEDF, D_lo * MEDF, D_hi * MEDF\n", "evid = {\"static\": float(S_static.log10_evidence),\n", " \"gradual drift\": float(S_grad.log10_evidence),\n", " \"regime switch\": float(S_reg.log10_evidence)}\n", "best_dynamics = max(evid, key=evid.get)" ] }, { "cell_type": "markdown", "id": "94d45d34", "metadata": {}, "source": [ "## Comparison with a Gaussian HMM\n", "\n", "We now fit the moveHMM-style baseline. We fit Gaussian HMMs with `hmmlearn` for K = 1–4 states on the log step lengths (modelling $\\log L$ as Gaussian within a state is the usual choice, equivalent to a lognormal step-length distribution), and pick K by BIC. We then take the conventional 2-state model, order its states slow→fast, extract the Viterbi path and the posterior state probabilities, and convert each state's mean back to a median step length in metres so it is directly comparable to bayesloop's Rayleigh median step, a units-consistent test." ] }, { "cell_type": "code", "execution_count": 4, "id": "dee1310b", "metadata": { "execution": { "iopub.execute_input": "2026-06-12T09:53:31.978157Z", "iopub.status.busy": "2026-06-12T09:53:31.978069Z", "iopub.status.idle": "2026-06-12T09:53:33.486407Z", "shell.execute_reply": "2026-06-12T09:53:33.485687Z" }, "lines_to_next_cell": 2 }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "bayesloop dynamics evidence (log10): {'static': -2773.3, 'gradual drift': -2474.7, 'regime switch': -2521.1} -> best: gradual drift\n", "HMM BIC by #states: {1: 2835, 2: 2794, 3: 2827, 4: 2822} -> best k: 2\n", "HMM 2-state medians: slow 116 m, fast 846 m\n", "bayesloop median-step in HMM-slow 211 m vs HMM-fast 550 m (continuous)\n", "81% of fixes fall between the two HMM state centres; 33% the HMM cannot confidently assign (max posterior < 0.9)\n" ] } ], "source": [ "from hmmlearn.hmm import GaussianHMM\n", "X = np.log(np.clip(L, 1e-3, None)).reshape(-1, 1)\n", "\n", "def hmm_bic(k):\n", " m = GaussianHMM(n_components=k, covariance_type=\"full\", n_iter=300, random_state=0, tol=1e-3)\n", " m.fit(X)\n", " ll = m.score(X)\n", " p = (k - 1) + k * (k - 1) + k + k # startprob + transmat + means + vars\n", " n = len(X)\n", " return m, ll, -2 * ll + p * np.log(n)\n", "\n", "hmms = {}\n", "for k in (1, 2, 3, 4):\n", " m, ll, bic = hmm_bic(k)\n", " hmms[k] = (m, ll, bic)\n", "best_k = min(hmms, key=lambda k: hmms[k][2])\n", "\n", "# 2-state HMM Viterbi path (the conventional choice), ordered slow=0, fast=1\n", "m2 = hmms[2][0]\n", "order = np.argsort(m2.means_.ravel())\n", "state = np.array([np.where(order == s)[0][0] for s in m2.predict(X)])\n", "post2 = m2.predict_proba(X)[:, order] # HMM posterior state probabilities\n", "# The HMM models log(L) as Gaussian, so within a state L is lognormal with MEDIAN exp(mean):\n", "# these are the 116 m / 846 m state centres. We compare them to bayesloop's Rayleigh median\n", "# step (med_step, above) -- both are median step lengths in metres, a units-consistent test.\n", "med_hmm = np.array([float(np.exp(m2.means_.ravel()[order][i])) for i in range(2)])\n", "hmm2_state_means_m = [float(med_hmm[0]), float(med_hmm[1])]\n", "lo_m, hi_m = float(med_hmm.min()), float(med_hmm.max())\n", "# agreement: bayesloop median-step within each HMM-assigned state (same units now)\n", "bayesloop_medstep_in_HMM_slow = float(np.median(med_step[state == 0]))\n", "bayesloop_medstep_in_HMM_fast = float(np.median(med_step[state == 1]))\n", "# (1) fraction of the track whose continuous movement scale sits strictly BETWEEN the two HMM\n", "# state centres -- intermediate behaviour the binary label must round to one extreme.\n", "frac_between = float(np.mean((med_step > lo_m) & (med_step < hi_m)))\n", "# (2) fraction of fixes the HMM ITSELF cannot confidently label (max state posterior < 0.9)\n", "frac_ambig = float(np.mean(post2.max(axis=1) < 0.9))\n", "\n", "print(\"\\nbayesloop dynamics evidence (log10):\", {k: round(v, 1) for k, v in evid.items()},\n", " \"-> best:\", best_dynamics)\n", "print(\"HMM BIC by #states:\", {k: round(v[2]) for k, v in hmms.items()}, \"-> best k:\", best_k)\n", "print(f\"HMM 2-state medians: slow {lo_m:.0f} m, fast {hi_m:.0f} m\")\n", "print(f\"bayesloop median-step in HMM-slow {bayesloop_medstep_in_HMM_slow:.0f} m vs \"\n", " f\"HMM-fast {bayesloop_medstep_in_HMM_fast:.0f} m (continuous)\")\n", "print(f\"{100*frac_between:.0f}% of fixes fall between the two HMM state centres; \"\n", " f\"{100*frac_ambig:.0f}% the HMM cannot confidently assign (max posterior < 0.9)\")" ] }, { "cell_type": "markdown", "id": "38145cde", "metadata": {}, "source": [ "## Reading the result\n", "\n", "bayesloop's marginal likelihood ranks gradual continuous drift above both the static model and the regime switch: continuous variation exceeds abrupt regime-switching by about 46 log₁₀ units. The data themselves prefer a *continuum* over discrete state-switching, which is precisely the assumption the HMM hard-codes. bayesloop can pose and answer that question, whereas the HMM cannot.\n", "\n", "The first figure shows why. The inferred movement scale (red, with credible band) tracks a clear seasonal behavioural rhythm: high, variable movement through spring–summer 2008, a long near-dormant period in autumn–winter (the deer contracts to a small winter range), and a return to high activity in spring 2009. The HMM's transit state (blue shading) coincides with the active periods, so the two methods agree on where the animal is moving, but bayesloop represents it as a continuous intensity rather than a binary label." ] }, { "cell_type": "code", "execution_count": 5, "id": "e892ec00", "metadata": { "execution": { "iopub.execute_input": "2026-06-12T09:53:33.488196Z", "iopub.status.busy": "2026-06-12T09:53:33.487693Z", "iopub.status.idle": "2026-06-12T09:53:33.661875Z", "shell.execute_reply": "2026-06-12T09:53:33.661377Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tt = pd.to_datetime(t)\n", "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(9.4, 5.6), sharex=True)\n", "ax1.plot(tt, L, lw=0.5, color=C[\"muted\"], alpha=0.7, label=\"step length\")\n", "ax1.plot(tt, med_step, color=C[\"accent\"], lw=1.8, label=\"inferred movement scale (median step)\")\n", "ax1.fill_between(tt, med_lo, med_hi, color=C[\"band\"], alpha=0.2)\n", "ax1.set_ylabel(\"step length (m)\")\n", "ax1.set_title(\"Red-deer movement: a continuous time-varying intensity vs. discrete HMM states\")\n", "ax1.legend(loc=\"upper right\", fontsize=8)\n", "# HMM state shading\n", "ax2.plot(tt, med_step, color=C[\"accent\"], lw=1.6, label=r\"bayesloop median step $D_t$ (continuous)\")\n", "ax2.fill_between(tt, med_lo, med_hi, color=C[\"band\"], alpha=0.2)\n", "ax2.fill_between(tt, 0, np.max(med_hi) * (state == 1), color=C[\"accent2\"], alpha=0.10, step=\"mid\",\n", " label=\"HMM 'transit' state\")\n", "for ym in hmm2_state_means_m:\n", " ax2.axhline(ym, color=C[\"muted\"], ls=\":\", lw=1)\n", "ax2.set_ylabel(\"median step length (m)\")\n", "ax2.set_xlabel(\"date\")\n", "ax2.legend(loc=\"upper right\", fontsize=8)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "04174fad", "metadata": {}, "source": [ "The 2-state HMM (the BIC's pick here) describes the deer with just two numbers, a slow state with median step ~116 m and a fast state at ~846 m. The bayesloop posterior, by contrast, shows the movement scale to be a continuum. Comparing like with like, with both methods expressed as a median step length in metres, bayesloop's inferred scale sits between those two discrete values for ~81% of the track and almost never settles at either extreme. The HMM itself cannot confidently label ~33% of the fixes, as its posterior state probability stays below 0.9: for about a third of the track the discrete model is guessing. That intermediate behaviour is exactly what a two-state label has nowhere to put." ] }, { "cell_type": "code", "execution_count": 6, "id": "f1b54b3d", "metadata": { "execution": { "iopub.execute_input": "2026-06-12T09:53:33.663130Z", "iopub.status.busy": "2026-06-12T09:53:33.663038Z", "iopub.status.idle": "2026-06-12T09:53:33.777991Z", "shell.execute_reply": "2026-06-12T09:53:33.777521Z" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, (axa, axb) = plt.subplots(1, 2, figsize=(9.6, 3.8))\n", "# trajectory coloured by inferred D\n", "sc = axa.scatter((xy[:, 0] - xy[:, 0].min()) / 1000, (xy[:, 1] - xy[:, 1].min()) / 1000,\n", " c=D_mean, cmap=\"viridis\", s=9)\n", "axa.plot((xy[:, 0] - xy[:, 0].min()) / 1000, (xy[:, 1] - xy[:, 1].min()) / 1000, lw=0.3, color=\"k\", alpha=0.3)\n", "axa.set_xlabel(\"x (km)\"); axa.set_ylabel(\"y (km)\")\n", "axa.set_title(\"Track coloured by movement scale D (m)\")\n", "plt.colorbar(sc, ax=axa, shrink=0.85)\n", "# continuum vs 2 discrete HMM states\n", "axb.hist(med_step, bins=40, color=C[\"accent\"], alpha=0.75)\n", "sm, fm = lo_m, hi_m\n", "axb.axvspan(sm, fm, color=C[\"amber\"], alpha=0.18,\n", " label=f\"between states ({100*frac_between:.0f}% of fixes)\")\n", "axb.axvline(sm, color=C[\"accent2\"], ls=\"--\", lw=1.5, label=f\"HMM 'slow' {sm:.0f} m\")\n", "axb.axvline(fm, color=C[\"green\"], ls=\"--\", lw=1.5, label=f\"HMM 'fast' {fm:.0f} m\")\n", "axb.set_xlabel(\"median step length (m)\")\n", "axb.set_ylabel(\"# of 6-h steps\")\n", "axb.set_title(\"A continuum the 2-state HMM bins into two\")\n", "axb.legend(fontsize=7.5)\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "4ecad324", "metadata": {}, "source": [ "## What this example showed\n", "\n", "On a single red-deer GPS track we used *bayesloop* to:\n", "\n", "- describe behaviour as a continuous time-varying movement scale $D_t$, using a custom Rayleigh `bl.om.NumPy` observation model whose scale drifts under a `GaussianRandomWalk` and is inferred with full credible bands, rather than as hard discrete states;\n", "- let the evidence choose the kind of dynamics, comparing static, gradual drift, and regime switch, with the continuous drift winning by about 46 log₁₀: the data prefer a continuum over the discrete state-switching an HMM assumes, and there is no K to specify;\n", "- benchmark against the established tool, a 2-state Gaussian HMM (`hmmlearn`, moveHMM-style): bayesloop recovers the same seasonal segmentation, but shows that the movement scale sits between the HMM's two states ~81% of the time and that the HMM itself cannot confidently label ~33% of fixes;\n", "- trade many parameters for two: K means, K scales, and K×K transitions become a single movement-scale parameter plus one smoothness hyper-parameter, while adding calibrated uncertainty and the behavioural continuum the HMM discards.\n", "\n", "One methodological caveat applies. This model uses step length only, as basic HMMs do; it does not use turning angles or directional persistence, which `momentuHMM` can add, and the winter quiescence partly reflects an actual range contraction. The two model classes are not directly likelihood-comparable, so the comparison concerns the information content and assumptions of the models. On that basis, bayesloop provides more information and a simpler model." ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all", "main_language": "python", "notebook_metadata_filter": "-all", "text_representation": { "extension": ".py", "format_name": "hydrogen" } }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.4" } }, "nbformat": 4, "nbformat_minor": 5 }