{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "considerable-start",
"metadata": {},
"outputs": [],
"source": [
"from lets_plot import *"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "grateful-williams",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" \n",
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"LetsPlot.setup_html()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "color-smith",
"metadata": {},
"outputs": [],
"source": [
"LetsPlot.set_theme(theme_minimal())"
]
},
{
"cell_type": "markdown",
"id": "breeding-sheet",
"metadata": {},
"source": [
"#### Draw arrows\n",
"\n",
"- the arrowhead always points to the specified coordinate of the segment\n",
"- the segment itself is drawn so that it does not intersect with its arrow\n",
"- no beveled corners (previously, acute angle could be drawn beveled)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "amateur-security",
"metadata": {},
"outputs": [],
"source": [
"def plot_with_arrows(angle, type='open'):\n",
" return ggplot() \\\n",
" + geom_vline(xintercept=0) \\\n",
" + geom_vline(xintercept=1) \\\n",
" + geom_segment(x=0, xend=1, y=0, yend=0,\n",
" size=5,\n",
" alpha=0.5,\n",
" arrow=arrow(ends='both', type=type, length=75, angle=angle)) \\\n",
" + ggsize(600, 350)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "demonstrated-template",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plot_with_arrows(10)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "cognitive-partition",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"plot_with_arrows(30)"
]
},
{
"cell_type": "markdown",
"id": "integral-migration",
"metadata": {},
"source": [
"#### 'space' parameter - additional space to shorten a segment by moving the start/end"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "blocked-trader",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() \\\n",
" + geom_vline(xintercept=0) \\\n",
" + geom_vline(xintercept=1) \\\n",
" + geom_segment(x=0, xend=1, y=0, yend=0,\n",
" size=5, \n",
" alpha=0.5,\n",
" arrow=arrow(ends='both', type='open', length=75, angle=15),\n",
" spacer=15) \\\n",
" + ggsize(600, 200)"
]
},
{
"cell_type": "markdown",
"id": "unlikely-corruption",
"metadata": {},
"source": [
"#### New aesthetics: `size_start,start_end` and `stroke_start,stroke_end`"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "hollow-activity",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x = [-1, 0, 1]\n",
"y = [-1, 1, -1]\n",
"shape = [1, 16, 21]\n",
"size = [1, 2, 3]\n",
"stroke = [1, 0, 2]\n",
"\n",
"x_end = x[1:] + [x[0]]\n",
"y_end = y[1:] + [y[0]]\n",
"size_end = size[1:] + [size[0]]\n",
"stroke_end = stroke[1:] + [stroke[0]]\n",
"\n",
"data = {\n",
" 'x': x,\n",
" 'y': y,\n",
" 'shape': shape,\n",
" 'size': size,\n",
" 'stroke': stroke,\n",
" 'x_end': x_end,\n",
" 'y_end': y_end,\n",
" 'size_end': size_end,\n",
" 'stroke_end': stroke_end,\n",
"}\n",
"\n",
"plot = ggplot(data, aes('x','y')) \\\n",
" + geom_point(aes(size='size', shape='shape', stroke='stroke'), color='#4575b4', fill='#abd9e9') \\\n",
" + scale_size(range=[20,30], guide='none') \\\n",
" + scale_stroke(range=[0,10], guide='none') \\\n",
" + scale_shape_identity() \\\n",
" + lims(x=[-1.5, 1.5], y=[-1.5, 1.5])\n",
"\n",
"plot"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "disturbed-survival",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Draw segments using offsets from start/end using aesthetics\n",
"\n",
"# Also need to set the same scale settings:\n",
"se_scales = scale_continuous(['size_start','size_end'], range=[20,30], guide='none') \\\n",
" + scale_continuous(['stroke_start','stroke_end'], range=[0,10], guide='none')\n",
"\n",
"plot \\\n",
" + geom_segment(aes(xend='x_end', yend='y_end', \n",
" size_start='size', size_end='size_end',\n",
" stroke_start='stroke', stroke_end='stroke_end'),\n",
" arrow=arrow(type='open', ends='both', length=15, angle=15)) \\\n",
" + se_scales"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "cooked-celebrity",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# For start coordfinate only\n",
"\n",
"plot \\\n",
" + geom_segment(aes(xend='x_end', yend='y_end', \n",
" size_end='size_end', stroke_end='stroke_end'),\n",
" arrow=arrow(type='open', ends='last', length=15, angle=15)) \\\n",
" + se_scales"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "engaging-effects",
"metadata": {},
"outputs": [],
"source": [
"# Example from https://stackoverflow.com/questions/14647988/arranging-arrows-between-points-nicely-in-ggplot2\n",
"\n",
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"np.random.seed(7)\n",
"\n",
"points = pd.DataFrame({\n",
" 'x': np.random.uniform(size=10),\n",
" 'y': np.random.uniform(size=10),\n",
" 'class': np.arange(1, 11),\n",
" 'size': np.random.uniform(1000, 100000, size=10)\n",
"})\n",
"\n",
"trans = pd.DataFrame({\n",
" 'from': np.repeat(np.arange(1, 11), 10),\n",
" 'to': np.tile(np.arange(1, 11), 10),\n",
" 'amount': np.random.uniform(size=100) ** 3\n",
"})\n",
"\n",
"trans = pd.merge(trans, points, left_on='from', right_on='class')\n",
"trans = pd.merge(trans, points, left_on='to', right_on='class', suffixes=('.to', '.from'))\n",
"\n",
"trans = trans.loc[(trans['amount'] >= 0.6)]"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "becoming-middle",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot(points, aes(x='x', y='y')) \\\n",
" + geom_point(aes(size='size'), color=\"red\", shape=1, stroke=0.75) \\\n",
" + geom_segment(aes(x='x.from', y='y.from', xend='x.to', yend='y.to', \n",
" size_start='size.from', size_end='size.to'), \n",
" data=trans,\n",
" stroke_start=0.75, stroke_end=0.75,\n",
" alpha=0.7, \n",
" arrow=arrow(type='open', ends='both')) \\\n",
" + scale_continuous(['size','size_start','size_end'], range=[4,20])"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "imported-sequence",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# From doc\n",
"\n",
"import numpy as np\n",
"\n",
"T = 25\n",
"np.random.seed(42)\n",
"t = [0, *np.random.normal(size=T)]\n",
"x = np.cumsum(np.cos(t))\n",
"y = np.cumsum(np.sin(t))\n",
"\n",
"ggplot({'x': x[:-1], 'y': y[:-1], 'xend': x[1:], 'yend': y[1:]}, aes(x='x', y='y')) \\\n",
" + geom_segment(aes(xend='xend', yend='yend', color='xend'),\n",
" arrow=arrow(type='closed', angle=10)) \\\n",
" + scale_color_gradient(low='#2c7bb6', high='#d7191c') \\\n",
" + coord_fixed()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "measured-franchise",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# on LiveMap\n",
"\n",
"# use constants\n",
"\n",
"ggplot(data, aes('x','y')) \\\n",
" + geom_livemap() \\\n",
" + geom_point(size=20, color='#4575b4', alpha=0.5) \\\n",
" + geom_segment(aes(xend='x_end', yend='y_end'),\n",
" size_start=20, size_end=20,\n",
" size=4,\n",
" arrow=arrow(type='closed', ends='last', angle=15))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "sharp-civilian",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Mappings\n",
"\n",
"ggplot(data, aes('x', 'y')) \\\n",
" + geom_livemap() \\\n",
" + geom_point(aes(size='size', shape='shape', stroke='stroke'),data=data, color='#4575b4', fill='#abd9e9') \\\n",
" + geom_segment(aes(xend='x_end', yend='y_end', \n",
" size_start='size', size_end='size_end',\n",
" stroke_start='stroke', stroke_end='stroke_end'),\n",
" size=4,\n",
" arrow=arrow(type='closed', ends='last', angle=15)) \\\n",
" + scale_shape_identity() \\\n",
" + scale_continuous(['size', 'size_start','size_end'], range=[20,30], guide='none') \\\n",
" + scale_continuous(['stroke', 'stroke_start','stroke_end'], range=[0,10], guide='none')"
]
},
{
"cell_type": "markdown",
"id": "decimal-alberta",
"metadata": {},
"source": [
"#### From 'Pushkin as Travller' notebook"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "original-documentary",
"metadata": {},
"outputs": [],
"source": [
"def set_stay_time(data):\n",
" current_moves = moves_df[(moves_df.departure == data['name'])|(moves_df.arrival == data['name'])]\n",
" years = current_moves.year.sort_values().unique()\n",
" years_combined = []\n",
" for year in years:\n",
" if len(years_combined) == 0 or years_combined[-1][1] + 1 != year:\n",
" years_combined.append((year, year))\n",
" else:\n",
" years_combined[-1] = (years_combined[-1][0], year)\n",
" years_combined = [str(year_from) if year_from == year_to else '{0}-{1}'.format(year_from, year_to) \\\n",
" for year_from, year_to in years_combined]\n",
" data['years'] = ', '.join(years_combined)\n",
" return data\n",
"\n",
"places_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/pushkin/places.csv')\n",
"moves_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/pushkin/moves.csv')\n",
"df = moves_df.merge(places_df, left_on='departure', right_on='name')\\\n",
" .rename(columns=dict(longitude='from_lon', latitude='from_lat'))\\\n",
" .drop(columns=['name'])\\\n",
" .merge(places_df, left_on='arrival', right_on='name')\\\n",
" .rename(columns=dict(longitude='to_lon', latitude='to_lat'))\\\n",
" .drop(columns=['name'])\n",
"places_df['years'] = ''\n",
"places_df = places_df.apply(set_stay_time, axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "wound-cable",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ggplot() + \\\n",
" geom_livemap(const_size_zoomin=3) + \\\n",
" geom_segment(aes(x='from_lon', y='from_lat', xend='to_lon', yend='to_lat', color='path'), data=df,\n",
" size_start=3, size_end=3,\n",
" tooltips=layer_tooltips().title(\"Trip\").line(\"@path\"),\n",
" arrow=arrow(type='closed', length=10, angle=15), size=1) + \\\n",
" geom_point(aes(x='longitude', y='latitude'), data=places_df, size=3, color='#F7F4F0',\n",
" tooltips=layer_tooltips().title('@name').line('visited in|@years')) + \\\n",
" geom_point(aes(x='longitude', y='latitude'), data=places_df, size=1.7, color='black',\n",
" tooltips='none') + \\\n",
" scale_color_manual(name='trip name', values=['#addd8e', '#e34a33', '#8856a7', '#2c7fb8',\n",
" '#1c9099', '#006d2c', '#fec44f', '#636363']) + \\\n",
" coord_cartesian(xlim=[26, 58], ylim=[38, 62]) + \\\n",
" ggtitle(\"Alexander Pushkin's Trips\") + \\\n",
" ggsize(800, 600) + \\\n",
" theme(axis_title='blank', axis_text='blank', axis_ticks='blank', axis_line='blank')"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "swedish-guard",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mX = 37.618423\n",
"mY = 55.751244\n",
"pointSize = 2\n",
"\n",
"ggplot(places_df, aes(x='longitude', y='latitude')) + \\\n",
" geom_livemap() + \\\n",
" geom_point(size=pointSize, color='red') + \\\n",
" geom_segment(xend=mX, yend=mY,\n",
" size=0.2,\n",
" size_start=pointSize, size_end=pointSize)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
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}