kopia lustrzana https://github.com/sepandhaghighi/samila
590 wiersze
13 KiB
Plaintext
590 wiersze
13 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": "markdown",
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"metadata": {},
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"source": [
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"### Version : 1.4\n",
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"---"
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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, GenerateMode"
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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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"## Magic\n",
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"If we create a `GenerativeImage` instance with no input parameters, we will get a plot generated 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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"## Generation Mode"
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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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"We have the option to select from various generation modes.\n",
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"\n",
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"ℹ️ The avaliable modes are `F1_VS_F2`, `F2_VS_F1`, `F1_VS_INDEX`, `F2_VS_INDEX`, `INDEX_VS_F1`, `INDEX_VS_F2`, `F1_VS_X1`, `F1_VS_X2`, `F2_VS_X1`, `F2_VS_X2`, `X1_VS_F1`, `X1_VS_F2`, `X2_VS_F1` and `X2_VS_F2`"
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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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"ℹ️ Default mode is `F1_VS_F2`"
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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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"\n",
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"for mode in list(GenerateMode):\n",
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" print(mode)\n",
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" g2.generate(mode=mode)\n",
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" g2.plot()\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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"## 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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"ℹ️ 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": "markdown",
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"metadata": {},
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"source": [
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"ℹ️ Default projection is `RECTILINEAR`"
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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 projection in list(Projection):\n",
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" print(projection)\n",
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" g2.plot(projection=projection)\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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"ℹ️ 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": "markdown",
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"metadata": {},
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"source": [
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"ℹ️ Default marker is `POINT`"
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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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"ℹ️ 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": "markdown",
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"metadata": {},
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"source": [
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"ℹ️ Default range is $(-\\pi, \\pi)$"
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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": "markdown",
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"metadata": {},
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"source": [
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"ℹ️ Default color is `black`\n",
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"\n",
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"ℹ️ Default background-color is `white`"
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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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"ℹ️ Supported colors are available in `VALID_COLORS` list\n",
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"\n",
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"ℹ️ `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": "markdown",
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"metadata": {},
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"source": [
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"ℹ️ Default spot-size is `0.01`"
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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",
|
||
"metadata": {},
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||
"source": [
|
||
"## 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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||
{
|
||
"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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},
|
||
{
|
||
"cell_type": "code",
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||
"execution_count": null,
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||
"metadata": {},
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||
"outputs": [],
|
||
"source": [
|
||
"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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||
{
|
||
"cell_type": "markdown",
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||
"metadata": {},
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||
"source": [
|
||
"## NFT.storage"
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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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||
},
|
||
{
|
||
"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": [
|
||
"g1.nft_storage(api_key=\"YOUR_API_KEY\")"
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||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
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||
"source": [
|
||
"g1.nft_storage(api_key=\"YOUR_API_KEY\", timeout=5000)"
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||
]
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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"You can also upload your config/data to nft storage as follows:"
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||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"g1.nft_storage(api_key=\"YOUR_API_KEY\", upload_config=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"g1.nft_storage(api_key=\"YOUR_API_KEY\", upload_data=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"⚠️ This method is deprecated and may be removed in future releases\n",
|
||
"\n",
|
||
"ℹ️ Default timeout is `3000` seconds\n",
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||
"\n",
|
||
"ℹ️ Default gateway is `IPFS_IO`"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
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