Distribution Overhaul

.github/workflows/python-package.yml

@@ -15,7 +15,7 @@ jobs:
         strategy:
             fail-fast: false
             matrix:
-                python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+                python-version: ["3.10", "3.11", "3.12", "3.13", "3.14"]
 
         steps:
             - uses: actions/checkout@v3

.gitignore

@@ -5,13 +5,14 @@
 .coverage
 .vscode
 .venv
+.mplconfig
 
 *.egg-info
 */__pycache__
 
-uv.lock
-
 dev/
 dist/
 docs/site/
-build/
+build/
+
+*copy*

docs/docs/feature-checklist.md

@@ -3,7 +3,7 @@
 ### 1. Descriptive Statistics
 
 | Feature                             | PyCircStat2           | PyCircStat                | CircStat (MATLAB)  | CircStats (R) | circular (R)                          |
-| ----------------------------------- | --------------------- | ------------------------- | ------------------ | ------------- | ------------------------------------- |
+|-------------------------------------|-----------------------|---------------------------|--------------------|---------------|---------------------------------------|
 | **Measures of Central Tendency**    |                       |                           |                    |               |                                       |
 | Circular Mean                       | `circ_mean`           | `mean(alpha)`             | `circ_mean(alpha)` | `circ.mean`   | `mean.circular`                       |
 | Circular Mean CI                    | `circ_mean_ci`        | `mean(alpha, ci=95)`      | `circ_confmean`    | -             | `mle.vonmises.bootstrap.ci`           |
@@ -31,7 +31,7 @@
 #### One-Sample Tests for Significance
 
 | Feature                     | H0                                  | PyCircStat2         | PyCircStat | CircStat (MATLAB) | CircStats (R) | circular (R)    |
-| --------------------------- | ----------------------------------- | ------------------- | ---------- | ----------------- | ------------- | --------------- |
+|-----------------------------|-------------------------------------|---------------------|------------|-------------------|---------------|-----------------|
 | **Mean Direction**          |                                     |                     |            |                   |               |                 |
 | Rayleigh Test               | $\rho=0$ [^uniform]                 | `rayleigh_test`     | `rayleigh` | `circ_rtest`      | `r.test`      | `rayleigh.test` |
 | V-Test                      | $\rho=0$                            | `V_test`            | `vtest`    | `circ_vtest`      | `v0.test`     | -               |
@@ -46,7 +46,7 @@
 #### Multi-Sample Tests for Significance
 
 | Feature                         | H0                                            | PyCircStat2                  | PyCircStat        | CircStat (MATLAB) | CircStats (R)     | circular (R)           |
-| ------------------------------- | --------------------------------------------- | ---------------------------- | ----------------- | ----------------- | ----------------- | ---------------------- |
+|---------------------------------|-----------------------------------------------|------------------------------|-------------------|-------------------|-------------------|------------------------|
 | **Mean Direction**              |                                               |                              |                   |                   |                   |                        |
 | Circular Analysis of Variance   | $\mu_1 = \dots = \mu_n$                       | `circ_anova`                 | -                 | -                 | -                 | `aov.circular`         |
 | Watson-Williams Test [^one-way] | $\mu_1 = \dots = \mu_n$                       | `watson_williams_test`       | `watson_williams` | `circ_wwtest`     | -                 | `watson.williams.test` |
@@ -66,7 +66,7 @@
 #### Goodness-of-fit Tests
 
 | Feature             | H0         | PyCircStat2        | PyCircStat   | CircStat (MATLAB) | CircStats (R) | circular (R)       |
-| ------------------- | ---------- | ------------------ | ------------ | ----------------- | ------------- | ------------------ |
+|---------------------|------------|--------------------|--------------|-------------------|---------------|--------------------|
 | Kuiper’s Test       | $\rho = 0$ | `circ_kuiper_test` | `kupier`     | `circ_kuipertest` | `kuiper`      | `kuiper.test`      |
 | Rao’s Spacing Test  | $\rho = 0$ | `rao_spacing_test` | `raospacing` | `circ_raotest`    | `rao.spacing` | `rao.spacing.test` |
 | Watson's Test       | $\rho = 0$ | `watson_test`      | -            | -                 | `watson`      | `watson.test`      |
@@ -75,7 +75,7 @@
 
 ### 3. Correlation & Regression
 | Feature                       | PyCircStat2    | PyCircStat | CircStat (MATLAB) | CircStats (R) | circular (R)              |
-| ----------------------------- | -------------- | ---------- | ----------------- | ------------- | ------------------------- |
+|-------------------------------|----------------|------------|-------------------|---------------|---------------------------|
 | Circular-Circular Correlation | `circ_corrcc`  | `corrcc`   | `circ_corrcc`     | `circ.cor`    | `cor.circular`            |
 | Circular-Linear Correlation   | `circ_corrcl`  | `corrcl`   | `circ_corrcl`     | -             | -                         |
 | Circular-Circular Regression  | `CCRegression` | -          | -                 | `circ.reg`    | `lm.circular(type="c-c")` |
@@ -85,10 +85,12 @@
 
 ### 4. Circular Distributions
 
+All circular distributions assume angles are on ``[0, 2π)``. Inputs are automatically wrapped to that support as a convenience. We remove SciPy's ``loc``/``scale`` convention—parameters like ``mu``, ``rho``, etc. are the only inputs. 
+
 #### Symmetric Circular Distributions
 
 | Feature              | Method | PyCircStat2               | PyCircStat       | CircStat (MATLAB) | CircStats (R) | circular (R)        |
-| -------------------- | ------ | ------------------------- | ---------------- | ----------------- | ------------- | ------------------- |
+|----------------------|--------|---------------------------|------------------|-------------------|---------------|---------------------|
 | Circular Uniform     | PDF    | `circularuniform.pdf`     | -                | -                 | -             | `dcircularuniform`  |
 |                      | CDF    | `circularuniform.cdf`     | -                | -                 | -             | -                   |
 |                      | PPF    | `circularuniform.ppf`     | -                | -                 | -             | -                   |
@@ -134,15 +136,10 @@
 |                      | PPF    | `jonespewsey.ppf`         | -                | -                 | -             | -                   |
 |                      | RVS    | `jonespewsey.rvs`         | -                | -                 | -             | -                   |
 |                      | Fit    | `jonespewsey.fit`         | -                | -                 | -             | -                   |
-| Kato-Jones           | PDF    | -                         | -                | -                 | -             | `dkatojones`        |
-|                      | CDF    | -                         | -                | -                 | -             | -                   |
-|                      | PPF    | -                         | -                | -                 | -             | -                   |
-|                      | RVS    | -                         | -                | -                 | -             | `rkatojones`        |
-|                      | Fit    | -                         | -                | -                 | -             | -                   |
 
 #### Asymmetric Circular Distributions
 | Feature                  | Method | PyCircStat2                  | PyCircStat | CircStat (MATLAB) | CircStats (R) | circular (R)     |
-| ------------------------ | ------ | ---------------------------- | ---------- | ----------------- | ------------- | ---------------- |
+|--------------------------|--------|------------------------------|------------|-------------------|---------------|------------------|
 | Jones-Pewsey Sine-Skewed | PDF    | `jonespewsey_sineskewed.pdf` | -          | -                 | -             | -                |
 |                          | CDF    | `jonespewsey_sineskewed.cdf` | -          | -                 | -             | -                |
 |                          | PPF    | `jonespewsey_sineskewed.ppf` | -          | -                 | -             | -                |
@@ -158,6 +155,11 @@
 |                          | PPF    | `inverse_batschelet.ppf`     | -          | -                 | -             | -                |
 |                          | RVS    | `inverse_batschelet.rvs`     | -          | -                 | -             | -                |
 |                          | Fit    | `inverse_batschelet.fit`     | -          | -                 | -             | -                |
+| Kato-Jones               | PDF    | `katojones.pdf`              | -          | -                 | -             | `dkatojones`     |
+|                          | CDF    | `katojones.cdf`              | -          | -                 | -             | -                |
+|                          | PPF    | `katojones.ppf`              | -          | -                 | -             | -                |
+|                          | RVS    | `katojones.rvs`              | -          | -                 | -             | `rkatojones`     |
+|                          | Fit    | `katojones.fit`              | -          | -                 | -             | -                |
 | Wrapped Stable           | PDF    | `wrapstable.pdf`             | -          | -                 | -             | -                |
 |                          | CDF    | `wrapstable.cdf`             | -          | -                 | -             | -                |
 |                          | PPF    | `wrapstable.ppf`             | -          | -                 | -             | -                |
@@ -172,4 +174,3 @@
 [^F]: $F$ stands for distributions.
 [^one-way]: Yet anothr one-way ANOVA.
 [^two-way]: Two-way ANOVA.
-

docs/mkdocs.yml

@@ -12,6 +12,8 @@ plugins:
     - mkdocstrings:
           handlers:
               python:
+                  paths:
+                      - ../pycircstat2
                   options:
                       show_source: true
                       docstring_style: "numpy"

examples/T0-utils.ipynb

@@ -280,14 +280,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Last updated: 2025-03-11 17:56:28CET\n",
+      "Last updated: 2025-11-03 14:20:54CET\n",
       "\n",
       "Python implementation: CPython\n",
-      "Python version       : 3.12.9\n",
-      "IPython version      : 8.31.0\n",
+      "Python version       : 3.12.12\n",
+      "IPython version      : 9.6.0\n",
       "\n",
-      "numpy      : 2.2.3\n",
-      "pycircstat2: 0.1.12\n",
+      "numpy      : 2.3.4\n",
+      "pycircstat2: 0.1.15\n",
       "\n",
       "Watermark: 2.5.0\n",
       "\n"
@@ -302,7 +302,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": ".venv (3.12.12)",
    "language": "python",
    "name": "python3"
   },
@@ -316,7 +316,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.9"
+   "version": "3.12.12"
   },
   "orig_nbformat": 4
  },

examples/T1-descriptive-statistics.ipynb

@@ -66,7 +66,7 @@
     "c11 = Circular(data=b11)\n",
     "\n",
     "u, r = circ_mean_and_r(alpha=c11.alpha)\n",
-    "print(f\"μ={np.rad2deg(u).round(2)}, r={r.round(2)}\")"
+    "print(f\"μ={np.round(np.rad2deg(u), 2)}, r={np.round(r, 2)}\")"
    ]
   },
   {
@@ -100,13 +100,13 @@
     "\n",
     "mp1 = circ_moment(alpha=c11.alpha, p=1, centered=False)\n",
     "u1, r1 = convert_moment(mp1)    \n",
-    "print(f\"μ1={np.rad2deg(u1).round(2)}, r1={r1.round(2)}\")\n",
+    "print(f\"μ1={np.round(np.rad2deg(u1), 2)}, r1={np.round(r1, 2)}\")\n",
     "\n",
     "# second moment\n",
     "\n",
     "mp2 = circ_moment(alpha=c11.alpha, p=2, centered=False)\n",
     "u2, r2 = convert_moment(mp2)\n",
-    "print(f\"μ2={np.rad2deg(u2).round(2)}, r2={r2.round(2)}\")"
+    "print(f\"μ2={np.round(np.rad2deg(u2), 2)}, r2={np.round(r2, 2)}\")"
    ]
   },
   {
@@ -310,13 +310,13 @@
     "c1 = Circular(data=d1)\n",
     "s = angular_std(alpha=c1.alpha)\n",
     "s0 = circ_std(alpha=c1.alpha)\n",
-    "print(f\"s={np.rad2deg(s).round()}, s0={np.rad2deg(s0).round()}\")\n",
+    "print(f\"s={np.round(np.rad2deg(s))}, s0={np.round(np.rad2deg(s0))}\")\n",
     "\n",
     "d2 = load_data('D2', source='zar')\n",
     "c2 = Circular(data=d2['θ'].values[:], w=d2['w'].values[:])\n",
     "s = angular_std(alpha=c2.alpha, w=c2.w)\n",
     "s0 = circ_std(alpha=c2.alpha, w=c2.w)\n",
-    "print(f\"s={np.rad2deg(s).round()}, s0={np.rad2deg(s0).round()}\")"
+    "print(f\"s={np.round(np.rad2deg(s))}, s0={np.round(np.rad2deg(s0))}\")"
    ]
   },
   {
@@ -336,7 +336,7 @@
     }
    ],
    "source": [
-    "from pycircstat2.descriptive import compute_C_and_S, circ_var, circ_r\n",
+    "from pycircstat2.descriptive import compute_C_and_S, circ_var\n",
     "C, S = compute_C_and_S(alpha=c2.alpha, w=c2.w)\n",
     "np.sqrt(C**2 + S**2), circ_r(alpha=c2.alpha, w=c2.w)"
    ]
@@ -402,12 +402,12 @@
     "    n=circ_zar_ex4_ch26.n,\n",
     "    method=\"approximate\",\n",
     ")\n",
-    "print(np.rad2deg([lb, ub]).round())"
+    "print(np.round(np.rad2deg([lb, ub])))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -420,7 +420,7 @@
       "median                    279.0                     247.5                     245.0               \n",
       "mean                      280.8                     248.7                     247.6               \n",
       "95% median CI             [245. 315.]               [229. 277.]               [229. 267.]         \n",
-      "95% bootstrap mean CI     [266.2 305.3]             [216.  266.5]             [230.2 262.1]       \n",
+      "95% bootstrap mean CI     [263.  306.9]             [227.7 272.5]             [234.5 263.2]       \n",
       "95% large-sample mean CI  -                         -                         [232.7 262.5]       \n"
      ]
     }
@@ -438,29 +438,29 @@
     "    \n",
     "    e = np.deg2rad(d)\n",
     "    mean = circ_mean(e)\n",
-    "    table['mean'].append(np.rad2deg(mean).round(1))\n",
+    "    table['mean'].append(np.round(np.rad2deg(mean), 1))\n",
     "    median = circ_median(e, method='deviation', average_method=\"unique\")\n",
-    "    table['median'].append(np.rad2deg(median).round(1))\n",
+    "    table['median'].append(np.round(np.rad2deg(median),1))\n",
     "\n",
     "    # CI for median\n",
     "    median_lb, median_ub, ci = circ_median_ci(alpha=e, method='deviation')\n",
-    "    table['95% median CI'].append(np.rad2deg([median_lb, median_ub]).round(1))\n",
+    "    table['95% median CI'].append(np.round(np.rad2deg([median_lb, median_ub]), 1))\n",
     "\n",
     "    # CI for mean using bootstrap\n",
     "    mean_lb, mean_ub = circ_mean_ci(\n",
     "        alpha=e,\n",
     "        B=200,\n",
     "        method=\"bootstrap\",\n",
     "    )\n",
-    "    table['95% bootstrap mean CI'].append(np.rad2deg([mean_lb, mean_ub]).round(1))\n",
+    "    table['95% bootstrap mean CI'].append(np.round(np.rad2deg([mean_lb, mean_ub]), 1))\n",
     "\n",
     "    if i == 2:\n",
     "        # CI for mean using dispersion\n",
     "        mean_lb_large_sample, mean_ub_large_sample = circ_mean_ci(\n",
     "            alpha=e,\n",
     "            method=\"dispersion\",\n",
     "        )\n",
-    "        table['95% large-sample mean CI'].append(np.rad2deg([mean_lb_large_sample, mean_ub_large_sample]).round(1))\n",
+    "        table['95% large-sample mean CI'].append(np.round(np.rad2deg([mean_lb_large_sample, mean_ub_large_sample]), 1))\n",
     "    else:\n",
     "        table['95% large-sample mean CI'].append('-')\n",
     "\n",
@@ -481,14 +481,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Last updated: 2025-03-11 17:57:05CET\n",
+      "Last updated: 2025-11-03 14:19:06CET\n",
       "\n",
       "Python implementation: CPython\n",
-      "Python version       : 3.12.9\n",
-      "IPython version      : 8.31.0\n",
+      "Python version       : 3.12.12\n",
+      "IPython version      : 9.6.0\n",
       "\n",
-      "pycircstat2: 0.1.12\n",
-      "numpy      : 2.2.3\n",
+      "numpy      : 2.3.4\n",
+      "pycircstat2: 0.1.15\n",
       "\n",
       "Watermark: 2.5.0\n",
       "\n"
@@ -503,7 +503,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": ".venv (3.12.12)",
    "language": "python",
    "name": "python3"
   },
@@ -517,7 +517,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.9"
+   "version": "3.12.12"
   },
   "orig_nbformat": 4
  },