kopia lustrzana https://github.com/sepandhaghighi/samila
501 wiersze
11 KiB
Plaintext
501 wiersze
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Samila Demo"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"try:\n",
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" import google.colab\n",
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" !{sys.executable} -m pip -q -q install samila\n",
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"except:\n",
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" pass"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"import random\n",
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"import math\n",
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"from samila import GenerativeImage, Projection, Marker"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Basic Generation\n",
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"If we call `generate` with no input parameters, we get a plot from two random equations"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g1 = GenerativeImage()\n",
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"g1.generate()\n",
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"g1.plot()\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Assigning Functions\n",
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"By defining `f1` and `f2`, we can control the general shape of the plot"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def f1(x, y):\n",
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" result = random.uniform(-1,1) * x**2 - math.sin(y**2) + abs(y-x)\n",
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" return result\n",
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"\n",
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"def f2(x, y):\n",
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" result = random.uniform(-1,1) * y**3 - math.cos(x**2) + 2*x\n",
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" return result\n",
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"\n",
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"g2 = GenerativeImage(f1, f2)\n",
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"g2.generate()\n",
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"g2.plot()\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Projection\n",
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"We can use the `projection` attribute to define the coordinate system to transform our functions\n",
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"\n",
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"The avaliable projections are `RECTILINEAR`, `POLAR`, `AITOFF`, `HAMMER`, `LAMBERT`, `MOLLWEIDE` and `RANDOM`"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2 = GenerativeImage(f1, f2)\n",
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"g2.generate()\n",
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"\n",
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"for p in list(Projection):\n",
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" print(p)\n",
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" g2.plot(projection=p)\n",
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" plt.show()\n",
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" plt.close()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Marker\n",
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"We can use the `marker` attribute to change the plotting marker.\n",
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"\n",
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"The available markers are `POINT`, `PIXEL`, `CIRCLE`, `TRIANGLE_DOWN`, `TRIANGLE_UP`, `TRIANGLE_LEFT`, `TRIANGLE_RIGHT`, `TRI_DOWN`, `TRI_UP`, `TRI_LEFT`, `TRI_RIGHT`, `OCTAGON`, `SQUARE`, `PENTAGON`, `PLUS`, `PLUS_FILLED`, `STAR`, `HEXAGON_VERTICAL`, `HEXAGON_HORIZONTAL`, `X`, `X_FILLED`, `DIAMOND`, `DIAMON_THIN`, `VLINE`, `HLINE` and `RANDOM`."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2 = GenerativeImage(f1, f2)\n",
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"g2.generate()\n",
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"\n",
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"for m in list(Marker):\n",
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" print(m)\n",
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" g2.plot(marker=m, spot_size=100)\n",
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" plt.show()\n",
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" plt.close()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Rotation\n",
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"You can even rotate your art by using `rotation` parameter. Enter your desired rotation for the image in degrees and you will have it.\n",
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"\n",
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"* Default rotation is 0."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g = GenerativeImage(f1, f2)\n",
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"g.generate()\n",
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"g.plot(rotation=45)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Range\n",
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"\n",
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"Control the range over which the input values span"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2 = GenerativeImage(f1, f2)\n",
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"g2.generate(start=-1.5*math.pi, step=0.007, stop=0)\n",
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"g2.plot(projection=Projection.POLAR)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Color\n",
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"\n",
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"We can assign colors for both the background as well as the line\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2 = GenerativeImage(f1, f2)\n",
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"g2.generate()\n",
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"g2.plot(color=\"maroon\", bgcolor=\"antiquewhite\", projection=Projection.POLAR)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* Supported colors are available in `VALID_COLORS` list\n",
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"* `color` and `bgcolor` parameters supported formats:\n",
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"\n",
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" 1. Color name (example: `color=\"yellow\"`)\n",
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" 2. RGB/RGBA (example: `color=(0.1,0.1,0.1)`, `color=(0.1,0.1,0.1,0.1)`)\n",
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" 3. Hex (example: `color=\"#eeefff\"`)\n",
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" 4. Random (example: `color=\"random\"`)\n",
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" 5. Complement (example: `color=\"complement\", bgcolor=\"blue\"`)\n",
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" 6. Transparent (example: `bgcolor=\"transparent\"`)\n",
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" 7. List (example: `color=[\"black\", \"#fffeef\",...]`)\n",
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"\n",
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"⚠️ **Transparent** mode is only available for background\n",
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"\n",
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"⚠️ **List** mode is only available for color\n",
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"\n",
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"⚠️ In **List** mode, the length of this list must be equal to the lengths of data1 and data2"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Point Color\n",
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"\n",
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"You can make your custom color map and use it in Samila"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"colorarray = [\n",
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" [0.7, 0.2, 0.2, 1],\n",
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" [0.6, 0.3, 0.2, 1],\n",
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" \"black\",\n",
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" [0.4, 0.4, 0.3, 1],\n",
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" [0.3, 0.4, 0.4, 1],\n",
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" \"#ff2561\"]\n",
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"g2.generate()\n",
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"g2.plot(cmap=colorarray, color=g2.data2, projection=Projection.POLAR)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Spot Size\n",
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"\n",
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"We can also change the size of the plot marker"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2 = GenerativeImage(f1, f2)\n",
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"g2.generate()\n",
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"g2.plot(color=\"yellow\", bgcolor=\"darkslategray\", spot_size=0.25)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Random Seeds\n",
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"If we do not pass in a seed when calling `generate`, a random seed will be created for us\n",
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"\n",
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"Passing this seed into `generate` will guarantee plot reproducibility"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"seed = g2.seed\n",
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"print(seed)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2 = GenerativeImage(f1, f2)\n",
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"g2.generate(seed)\n",
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"g2.plot(color=\"yellow\", bgcolor=\"darkslategray\", spot_size=0.05)\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Saving Images\n",
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"\n",
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"Save generated images\n",
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"\n",
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"Use the `depth` attribute to increase the resolution"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2.save_image(file_adr=\"test.png\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2.save_image(file_adr=\"test_high_res.png\", depth=3)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Saving Data\n",
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"\n",
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"Save generated image data\n",
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"\n",
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"It can then be loaded into a `GenerativeImage` instance"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2.save_data(file_adr=\"data.json\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g2 = GenerativeImage(data=open('data.json', 'r'))\n",
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"g2.plot()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Saving Config\n",
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"\n",
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"Save generated image config. It contains string formats of functions which is also human readable\n",
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"\n",
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"It can then be loaded into a `GenerativeImage` instance"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g1.save_config(file_adr=\"config.json\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g1 = GenerativeImage(config=open('config.json', 'r'))\n",
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"g1.generate()\n",
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"g1.plot()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## NFT.storage"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Upload generated image directly to [NFT.storage](https://nft.storage)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g1.nft_storage(api_key=\"YOUR_API_KEY\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g1.nft_storage(api_key=\"YOUR_API_KEY\", timeout=5000)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can also upload your config/data to nft storage as follows:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g1.nft_storage(api_key=\"YOUR_API_KEY\", upload_config=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"g1.nft_storage(api_key=\"YOUR_API_KEY\", upload_data=True)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"* Default timeout is **3000** seconds"
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]
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}
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],
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