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feat: web friendly improvements to goals map for US states
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feat: demo note book added
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@victoriahunt
victoriahunt committed Sep 25, 2020
1 parent 4d7c6c9 commit d3466a5
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164 changes: 164 additions & 0 deletions postreise/plot/demo/plot_state_goals_map_demo.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## US State RPS Goals Map with hover-over tool tips\n",
"author: vhunt\n",
"\n",
"updated with breakthrough energy compatible colors 9/23/2020"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from bokeh.io import show\n",
"from postreise.plot import plot_carbon_map \n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"#prepare data for mapping \n",
"\n",
"rps_states = ('AL', 'AR', 'AZ', 'CA', 'CO',\n",
" 'CT', 'DE', 'FL','GA', 'IA', \n",
" 'ID', 'IL', 'IN', 'KS', 'KY',\n",
" 'LA', 'MA', 'MD', 'ME', 'MI',\n",
" 'MN', 'MO', 'MS', 'MT', 'NC', \n",
"\n",
" 'ND', 'NE', 'NH','NJ','NM',\n",
" 'NV','NY', 'OH', 'OK','OR',\n",
" 'PA','RI','SC', 'SD','TN', \n",
" 'TX','UT', 'VA','VT', 'WA',\n",
" 'WI', 'WV','WY',)\n",
"\n",
"color_list = ('#EBEEF1','#EBEEF1','#99CFF6','#0D68DC','#1490FF',\n",
" '#107CED','#1490FF','#EBEEF1','#EBEEF1', '#EBEEF1',\n",
" '#EBEEF1','#1490FF','#99CFF6','#47AFFB','#EBEEF1',\n",
" '#EBEEF1','#107CED','#107CED','#0A55CC','#107CED',\n",
" '#1490FF','#99CFF6', '#EBEEF1', '#99CFF6', '#99CFF6',\n",
" \n",
" '#99CFF6','#EBEEF1','#1490FF','#107CED','#107CED',\n",
" '#107CED', '#0D68DC','#99CFF6','#99CFF6','#1490FF',\n",
" '#47AFFB','#107CED','#99CFF6','#99CFF6','#EBEEF1',\n",
" '#107CED','#47AFFB','#99CFF6','#0A55CC','#0A55CC',\n",
" '#99CFF6','#EBEEF1','#EBEEF1',\n",
" )\n",
"\n",
"label_list = ('no clean energy goals', 'no clean energy goals', '15% in 2025', \n",
" '60% in 2030, 100% in 2045', '30% in 2020, 100% in 2050',\n",
" '44% in 2025','25% in 2025','no clean energy goals', 'no clean energy goals', 'no clean energy goals',\n",
" 'no clean energy goals', '25% in 2025','10% in 2015','20% in 2020','no clean energy goals',\n",
" 'no clean energy goals', ' 35% in 2030','30% in 2020 and 50% in 2030', \n",
" '80% in 2030, 100% in 2050','15% in 2020 and 35% in 2025',\n",
" '25% in 2025','15% in 2020', 'no clean energy goals', '15% in 2020','12.5% in 2020',\n",
" \n",
" '10% in 2020','no clean energy goals','25% in 2025','50% in 2030',\n",
" '40% in 2025, 80% in 2040, 100% in 2045',\n",
" '50% in 2030, 100% in 2050', '70% in 2030, 100% in 2040', '8.5% in 2025', \n",
" '15% in 2020','25% in 2025, 50% in 2040',\n",
" '18% in 2020',\n",
" '16% in 2020, 23.5% in 2025, 31% in 2030, 38.5% in 2035',\n",
" '2% in 2020','10% in 2020', 'no clean energy goals',\n",
" 'no clean energy goals, projected to have 50% in 2030', '20% in 2035', \n",
" '15% in 2025','55% in 2020, 75% in 2030', '80% in 2030, 100% in 2045',\n",
" '10% in 2020', 'no clean energy goals', 'no clean energy goals',\n",
" )\n",
"\n",
"data = {'State': rps_states,\n",
" 'Color': color_list,\n",
" 'Label': label_list,\n",
" }\n",
"\n",
"df = pd.DataFrame (data, columns = ['State','Color','Label'])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"#prepare data for legend\n",
"\n",
"legend_col = ['#EBEEF1',\n",
" '#99CFF6', \n",
" '#47AFFB',\n",
" '#1490FF',\n",
" '#107CED',\n",
" '#0D68DC',\n",
" '#0A55CC',\n",
" ]\n",
"legend_lab = ['no goals',\n",
" '0-15%', \n",
" '15-20%',\n",
" '20-30%',\n",
" '30-50%',\n",
" '50-70%',\n",
" '70-100%',\n",
" ]\n",
"\n",
"data_leg = {'Color': legend_col,\n",
" 'Label': legend_lab,}\n",
"\n",
"df_leg = pd.DataFrame (data_leg, columns = ['Color','Label'])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"goals_demo = plot_carbon_map.plot_states(state_list = df.State, \n",
" col_list = df.Color,\n",
" labels_list = df.Label,\n",
" leg_color = df_leg.Color,\n",
" leg_label = df_leg.Label,\n",
" font_size = '10pt',\n",
" web = True)\n",
"show(goals_demo)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
93 changes: 77 additions & 16 deletions postreise/plot/plot_carbon_map.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,10 +8,11 @@
from postreise.plot.projection_helpers import project_bus
from pyproj import Transformer

# make default states list
# make default states list, lower 48 only
default_states_dict = us_states.data.copy()
del default_states_dict["HI"]
del default_states_dict["AK"]
del default_states_dict["DC"]
default_states_list = list(default_states_dict.keys())

# breakthrough energy (be) color names
Expand Down Expand Up @@ -46,14 +47,26 @@ def get_borders(us_states_dat, state_list=None):
return all_state_xs, all_state_ys


def plot_states(state_list, col_list, labels_list, font_size, us_states_dat=None):
def plot_states(
state_list,
col_list,
labels_list,
leg_color,
leg_label,
font_size,
web=True,
us_states_dat=None,
):
"""Plots US state borders and allows color coding by state,
for example to represent different emissions goals.
:param list state_list: list of us states to color code.
:param list col_list: list of colors associated with states in state_list.
:param list labels_list: list of labels for us states.
:param float font_size: citation font size
:param list leg_color: list of colors for legend
:param list leg_label: list of labels for colors in legend
:param float font_size: citation font size, for non web version only
:param boolean web: if true, formats for website with hover tips
:param dict us_states_dat: if None default to us_states data file, imported from bokeh.
:return: -- map of us states with option to color by value.
"""
Expand All @@ -68,31 +81,61 @@ def plot_states(state_list, col_list, labels_list, font_size, us_states_dat=None

a, b = get_borders(us_states_dat.copy())

tools: str = "pan,wheel_zoom,reset,hover,save"
tools: str = "pan,wheel_zoom,reset,save"
p = figure(
title="US States",
tools=tools,
x_axis_location=None,
y_axis_location=None,
plot_width=800,
plot_height=800,
output_backend="webgl",
sizing_mode="stretch_both",
match_aspect=True,
)

# legend squares, plot behind graph so hidden
for i in range(len(leg_color)):
p.square(
-8.1e6,
[5.2e6, 5.3e6],
fill_color=leg_color[i],
color=leg_color[i],
size=300,
legend_label=leg_label[i],
)

p.add_tile(get_provider(Vendors.CARTODBPOSITRON_RETINA))
p.patches(a, b, fill_alpha=0, fill_color="blue", line_color="black", line_width=2)
# counter

# plot state borders
p.patches(a, b, fill_alpha=0, fill_color="blue", line_color="gray", line_width=2)

a1, b1 = get_borders(us_states_dat.copy(), state_list=state_list)
source = ColumnDataSource(
dict(
xs=a1,
ys=b1,
col=col_list,
col2=["gray" for i in range(48)],
label=labels_list,
state_name=state_list,
)
)

patch = p.patches(
"xs",
"ys",
source=source,
fill_alpha=0.8,
fill_color="col",
line_color="col2",
)

# loop through states and colors, plot patches
n = -1
# loop through states and colors, plot patches
for i in state_list:
n = n + 1
a1, b1 = get_borders(us_states_dat.copy(), state_list=[i])
p.patches(
a1,
b1,
fill_alpha=0.8,
fill_color=[col_list[n]],
line_color="black",
line_width=2,
)
citation = Label(
x=min(a1[0]) + 100000,
y=(max(b1[0]) + min(b1[0])) / 2,
Expand All @@ -106,7 +149,25 @@ def plot_states(state_list, col_list, labels_list, font_size, us_states_dat=None
background_fill_color="white",
background_fill_alpha=0.8,
)
p.add_layout(citation)
if not web:
p.add_layout(citation)

# specify parameters if making figure for website
if web:
hover = HoverTool(
tooltips=[
("State", "@state_name"),
("Goal", "@label"),
],
renderers=[patch],
) # only for circles
p.add_tools(hover)

p.legend.title = "Goals up to 2030"
p.legend.location = "bottom_right"
p.legend.label_text_font_size = "12pt"

p.legend.title_text_font_size = "12pt"
return p


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