Updated readme

Author: max-models

.gitignore

@@ -164,7 +164,7 @@ cython_debug/
 
 # Figures and videos
 figures/
-*.png
+#*.png
 *.pdf
 *.jpg
 *.jpeg
@@ -188,4 +188,4 @@ figures/
 env*
 
 # VS code
-.vscode/*
+.vscode/*

README.md

@@ -1,246 +1,85 @@
-# maxplotlib
+# Maxlotlib
 
 
-# maxplotlib
+# Maxplotlib
 
-A clean, expressive wrapper around **Matplotlib** for producing
-publication-quality figures with minimal boilerplate. Swap backends
-without rewriting your data — render the same canvas as a crisp PNG, an
-interactive Plotly chart, or camera-ready **TikZ** code for LaTeX.
+A clean, expressive wrapper around **Matplotlib** **tikzfigure** for
+producing publication-quality figures with minimal boilerplate. Swap
+backends without rewriting your data — render the same canvas as a crisp
+PNG, an interactive Plotly chart, or camera-ready **TikZ** code for
+LaTeX.
 
 ## Install
 
 ``` bash
-python -m venv env && source env/bin/activate
 pip install maxplotlibx
 ```
 
-For development extras (tests, docs, linting):
-
-``` bash
-pip install "maxplotlibx[dev]"
-```
-
 ## Showcase
 
-``` python
-import numpy as np
-from maxplotlib import Canvas
-
-rng = np.random.default_rng(0)
-x   = np.linspace(0, 2 * np.pi, 300)
-
-canvas, axes = Canvas.subplots(nrows=2, ncols=2, width="18cm", ratio=0.65)
-
-# ── top-left: multi-line with legend ──────────────────────────────────────────
-ax = axes[0][0]
-ax.plot(x, np.sin(x),           color="royalblue",  linewidth=2, label=r"$\sin(x)$")
-ax.plot(x, np.cos(x),           color="tomato",     linewidth=2,
-        linestyle="dashed",     label=r"$\cos(x)$")
-ax.plot(x, np.sin(2 * x) * 0.5, color="seagreen",   linewidth=1.5,
-        linestyle="dotted",     label=r"$\frac{1}{2}\sin(2x)$")
-ax.set_xlabel("x")
-ax.set_ylabel("amplitude")
-ax.set_title("Line plots")
-ax.set_legend(True)
-ax.set_grid(True)
-
-# ── top-right: scatter coloured by distance ────────────────────────────────────
-ax = axes[0][1]
-n  = 250
-sx = rng.standard_normal(n)
-sy = rng.standard_normal(n)
-ax.scatter(sx, sy, c=np.hypot(sx, sy), s=25, alpha=0.8)
-ax.set_xlabel("x")
-ax.set_ylabel("y")
-ax.set_title("Scatter — coloured by distance")
-ax.set_aspect("equal")
-
-# ── bottom-left: bar chart ────────────────────────────────────────────────────
-ax     = axes[1][0]
-months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun",
-          "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
-temps  = [3, 4, 8, 13, 18, 22, 24, 23, 18, 12, 7, 4]
-month_idx = np.arange(len(months))
-ax.bar(month_idx, temps, color="steelblue", width=0.7, label="avg °C")
-ax.set_xticks(month_idx, labels=months)
-ax.set_xlabel("month")
-ax.set_ylabel("temperature (°C)")
-ax.set_title("Bar chart")
-
-# ── bottom-right: fill_between confidence band ────────────────────────────────
-ax   = axes[1][1]
-mean = np.sin(x) * np.exp(-x / (2 * np.pi))
-std  = 0.15 + 0.1 * np.abs(np.cos(x))
-ax.plot(x, mean, color="darkorchid", linewidth=2, label="mean")
-ax.fill_between(x, mean - std, mean + std, alpha=0.25, color="darkorchid",
-                label="±1 σ")
-ax.set_xlabel("x")
-ax.set_ylabel("y")
-ax.set_title("Confidence band")
-ax.set_legend(True)
-ax.set_grid(True)
-
-canvas.suptitle("maxplotlib — four plot types, one canvas")
-fig, _ = canvas.plot()
-fig
-```
-
-<div id="fig-showcase">
-
-<div class="cell-output cell-output-display" execution_count="2">
-
-<div id="fig-showcase-1">
-
-<img src="README_files/figure-commonmark/fig-showcase-output-1.png"
-data-ref-parent="fig-showcase" />
-
-(a) maxplotlib showcase — four plot types, one canvas.
-
-</div>
-
-</div>
-
-<div class="cell-output cell-output-display">
-
-<div id="fig-showcase-2">
-
-<img src="README_files/figure-commonmark/fig-showcase-output-2.png"
-id="fig-showcase-2" data-ref-parent="fig-showcase" />
-
-(b)
-
-</div>
-
-</div>
-
-Figure 1
-
-</div>
-
-## Quick start
-
-### One-liner with `Canvas.subplots()`
-
-`Canvas.subplots()` mirrors `plt.subplots()` but returns a `Canvas` and
-subplot axes that speak the maxplotlib API.
+### Quickstart
 
 ``` python
 import numpy as np
 from maxplotlib import Canvas
 
 x = np.linspace(0, 2 * np.pi, 200)
+y = np.sin(x)
 
-canvas, ax = Canvas.subplots(width="10cm", ratio=0.55)
-ax.plot(x, np.sin(x), color="royalblue", label=r"$\sin(x)$", linewidth=2)
-ax.plot(x, np.cos(x), color="tomato",    label=r"$\cos(x)$", linewidth=2,
-        linestyle="dashed")
-ax.set_xlabel("x")
-ax.set_ylabel("y")
-ax.set_legend(True)
-ax.set_grid(True)
-canvas.show()
+canvas, ax = Canvas.subplots()
+ax.plot(x, y)
 ```
 
-### Canvas-level shortcut API
-
-For single-subplot figures every plot method is available directly on
-the `Canvas` object — no need to grab an axes handle:
+Plot the figure with the default (matplotlib) backend:
 
 ``` python
-canvas = Canvas(ratio=0.5, fontsize=12)
-canvas.add_line(x, np.sin(x), label="sin", color="steelblue")
-canvas.add_line(x, np.cos(x), label="cos", color="darkorange", linestyle="dashed")
-canvas.set_xlabel("angle (rad)")
-canvas.set_ylabel("amplitude")
-canvas.set_legend(True)
 canvas.show()
 ```
 
-## Key features
-
-### Multiple backends — same API
+![](README_files/figure-markdown_strict/cell-3-output-1.png)
 
-| Backend | How to use | Output |
-|----|----|----|
-| `matplotlib` (default) | `canvas.show()` | inline PNG / static file |
-| `plotly` | `fig = canvas.plot(backend='plotly')` | interactive HTML widget |
-| `tikzfigure` | `tz = canvas.plot(backend='tikzfigure')` | LaTeX `\draw` commands |
+Alternatively, plot with the TikZ backend (not done yet):
 
 ``` python
-# Render as interactive Plotly figure
-fig = canvas.plot(backend="plotly")
-fig.show()
-
-# Export TikZ code for a LaTeX document
-tikz = canvas.plot(backend="tikzfigure")
-print(tikz.generate_tikz())
+canvas.show(backend="tikzfigure")
 ```
 
-### Layers
+![](README_files/figure-markdown_strict/cell-4-output-1.png)
 
-Tag each plot call with a `layer=` integer. Then render any subset —
-handy for step-by-step derivations, lecture slides, or overlays.
+### Layers
 
 ``` python
-canvas, ax = Canvas.subplots()
-ax.plot(x, np.sin(x), layer=0, label=r"$\sin(x)$",        color="steelblue")
-ax.plot(x, np.cos(x), layer=1, label=r"$\cos(x)$",        color="tomato")
-ax.plot(x, np.sin(x) * np.cos(x), layer=2,
-        label=r"$\sin(x)\cos(x)$", color="seagreen", linestyle="dashed")
-
-canvas.show(layers=[0])       # only sin
-canvas.show(layers=[0, 1])    # sin + cos
-canvas.show()                 # everything
-```
+x = np.linspace(0, 2 * np.pi, 200)
 
-### Size and typography
+canvas, ax = Canvas.subplots(width="10cm", ratio=0.55)
 
-Pass physical dimensions and a font size; maxplotlib converts to the
-correct `figsize` automatically.
+ax.plot(x, np.sin(x), color="steelblue", label=r"$\sin(x)$", layer=0)
+ax.plot(x, np.cos(x), color="tomato", label=r"$\cos(x)$", layer=1)
+ax.plot(
+    x,
+    np.sin(x) * np.cos(x),
+    color="seagreen",
+    label=r"$\sin(x)\cos(x)$",
+    linestyle="dashed",
+    layer=2,
+)
 
-``` python
-canvas = Canvas(width="17cm", ratio=0.5, fontsize=11)
+ax.set_xlabel("x")
+ax.set_legend(True)
 ```
 
-`ratio` accepts a float **or** the string `"golden"` (default) for the
-golden ratio.
-
-### Saving figures
+Show layer 0 only, then layers 0 and 1, then everything:
 
 ``` python
-canvas.savefig("figure.pdf")     # vector PDF
-canvas.savefig("figure.png")     # raster PNG
-canvas.savefig("figure.svg")     # SVG
+canvas.show(layers=[0])
 ```
 
-## Plot types
-
-| Method                            | Description                    |
-|-----------------------------------|--------------------------------|
-| `ax.plot(x, y)`                   | Line plot                      |
-| `ax.scatter(x, y)`                | Scatter plot                   |
-| `ax.bar(categories, values)`      | Bar chart                      |
-| `ax.fill_between(x, y1, y2)`      | Shaded band                    |
-| `ax.errorbar(x, y, yerr)`         | Error bars                     |
-| `ax.axhline(y)` / `ax.axvline(x)` | Reference lines                |
-| `ax.annotate(text, xy)`           | Annotation with optional arrow |
-
-## Tutorials
-
-Step-by-step Jupyter notebooks in `tutorials/`:
+![](README_files/figure-markdown_strict/cell-6-output-1.png)
 
-| Notebook             | Topic                            |
-|----------------------|----------------------------------|
-| `tutorial_01`        | Quick start                      |
-| `tutorial_02`        | Multiple subplots                |
-| `tutorial_03`        | All plot types                   |
-| `tutorial_04`        | Colours, linestyles, markers     |
-| `tutorial_05`        | Axes, ticks, scales, annotations |
-| `tutorial_06`        | Layers                           |
-| `tutorial_07_tikz`   | TikZ backend                     |
-| `tutorial_08_plotly` | Plotly backend                   |
+Show all layers:
 
-## License
+``` python
+canvas.show()
+```
 
-MIT — see [`LICENSE`](LICENSE).
+![](README_files/figure-markdown_strict/cell-7-output-1.png)