def plot_circle_density(nodes, degrees, plot_width=800, plot_height=800):
print("Plotting circle density graph")
TOOLS="hover,pan,wheel_zoom,box_zoom,reset,click,previewsave"
plt.figure(plot_width=plot_width, plot_height=plot_height, tools=TOOLS)
theta = np.random.uniform(0, 2*np.pi, size=len(nodes))
max_d, min_d = np.max(degrees), np.min(degrees)
scale = 1.0/np.log(degrees) - 1.0/np.log(max_d)
xs = np.cos(theta)*scale
ys = np.sin(theta)*scale
source_dict = dict(
xs = xs,
ys = ys,
degrees = degrees,
nodes = nodes,
alphas = np.log(degrees)/np.log(max(degrees)),
)
source = ColumnDataSource(source_dict)
plt.hold(True)
plt.circle('xs', 'ys', source=source,
radius=0.0025,
fill_alpha='alphas',
x_axis_type=None, y_axis_type=None,
title="Density Distribution of Degrees")
plt.text([max(xs), max(xs)],
[.95*max(ys), .85*max(ys)],
["distance from center = 1 / log(deg)",
"angle = random"],
angle=0,
text_baseline="bottom", text_align="right")
hover = [t for t in plt.curplot().tools if isinstance(t, HoverTool)][0]
hover.tooltips = OrderedDict([
('node', '@nodes'), ('degree', '@degrees')
])
plt.hold(False)
return plt.curplot()
def make_box_violin_plot_2(data, maxwidth=0.9):
"""
data: dict[Str -> List[Number]]
maxwidth: float
Maximum width of tornado plot within each factor/facet
Returns the plot object
"""
df = pd.DataFrame(columns=["group", "centers", "width", "height", "texts"])
bar_height = 50
bins = [0, 1e1, 1e2, 1e3, 1e4, 1e5, 1e6]
# Compute histograms, while keeping track of max Y values and max counts
for i, (group, vals) in enumerate(data.iteritems()):
hist, edges = np.histogram(vals, bins)
df = df.append(pd.DataFrame(dict(
group = group,
centers = np.arange(len(hist))*bar_height,
width = np.log10(hist),
height = np.ones(hist.shape)*bar_height,
texts = map(str,hist),
)))
df.replace(-np.inf, 0)
# Normalize the widths
df["width"] *= (maxwidth / df["width"].max())
hold()
width, height = 800, 800
figure(plot_width=width, plot_height=height, title="Degree Distribution",
tools="previewsave",
x_axis_type=None, y_axis_type=None,
x_range=[-420, 420], y_range=[-420, 420],
x_axis_label="Number of nodes (log)", y_label="distribution of degree",
min_border=0, outline_line_color=None,
background_fill="#f0e1d2", border_fill="#f0e1d2")
size = len(df)
rect(np.zeros(size), df["centers"], height=[50 for i in range(size)],
width=df["width"]*width * .8)
text(np.zeros(size), df["centers"], text=df["texts"], angle=np.zeros(size),
text_color= ["#000000"] + ["#FFFFFF" for i in xrange(size-1)],
text_align="center", text_baseline="middle")
text(np.ones(size+1) * -width/2,
[(idx-0.75)*bar_height for idx in range(size+1)],
text=map(str, map(int, bins)), angle=0)
show()
def drawPlot(shapeFilename, zipBorough, zipMaxAgency):
# Read the ShapeFile
dat = shapefile.Reader(shapeFilename)
# Creates a dictionary for zip: {lat_list: [], lng_list: []}.
zipCodes = []
hoverZip = []
hoverAgency = []
hoverComplaints = []
polygons = {'lat_list': [], 'lng_list': [], 'centerLat_list': [], 'centerLon_list': []}
record_index = 0
for r in dat.iterRecords():
currentZip = r[0]
# Keeps only zip codes in NY area.
if currentZip in zipMaxAgency: # was in zipBorough:
# zipCodes.append(currentZip) # moving this line into the parts loop
# Gets shape for this zip.
shape = dat.shapeRecord(record_index).shape
for part in range(len(shape.parts)):
zipCodes.append(currentZip)
hoverZip.append(currentZip)
hoverAgency.append(zipMaxAgency[currentZip][0])
hoverComplaints.append(zipMaxAgency[currentZip][1])
start = shape.parts[part]
if part == len(shape.parts) - 1:
end = len(shape.points)
else:
end = shape.parts[part + 1]
points = shape.points[start : end]
# Breaks into lists for lat/lng.
lngs = [p[0] for p in points]
lats = [p[1] for p in points]
# Calculate centers
center_lngs = min(lngs) + (max(lngs) - min(lngs))/2
center_lats = min(lats) + (max(lats) - min(lats))/2
# Store centroids for current part shape
polygons['centerLat_list'].append(center_lats)
polygons['centerLon_list'].append(center_lngs)
# Stores lat/lng for current zip shape.
polygons['lng_list'].append(lngs)
polygons['lat_list'].append(lats)
record_index += 1
# Palette
##d9d9d9
brewer11 = ['#8dd3c7', '#ffffb3', '#bebada','#fb8072','#80b1d3','#fdb462','#b3de69','#fccde5','#d9d9d9','#bc80bd','#ccebc5']
#brewer11 = ['#a6cee3', '#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c','#fdbf6f','#ff7f00','#cab2d6','#6a3d9a','#ffff99']
#agencies = sorted(list({zipMaxAgency[zipCode] for zipCode in zipMaxAgency}))
biggestComplaints = {}
for zz, aa in zipMaxAgency.iteritems():
if aa[0] in biggestComplaints:
biggestComplaints[aa[0]] += 1
else:
biggestComplaints[aa[0]] = 1
# sorting agencies by number of zip codes (to try to get better colors)
agencies = list(biggestComplaints.iteritems())
agencies = sorted(agencies, key = lambda x: x[1], reverse = True)
agencies = [agency[0] for agency in agencies]
# Assign colors to agencies
agencyColor = {agencies[i] : brewer11[i] for i in range(len(brewer11))}
polygons['colors'] = [agencyColor[zipMaxAgency[zipCode][0]] for zipCode in zipCodes]
# Prepare hover
#source = bk.ColumnDataSource(data=dict(hoverAgency=hoverAgency, hoverZip=hoverZip, hoverComplaintCount=hoverComplaintCount,))
source = bk.ColumnDataSource(data=dict(hoverZip = hoverZip, hoverAgency = hoverAgency, hoverComplaints = hoverComplaints),)
# Creates the Plot
bk.output_file("problem1.html")
bk.hold()
TOOLS="pan,wheel_zoom,box_zoom,reset,previewsave,hover"
fig = bk.figure(title="311 Complaints by Zip Code", \
tools=TOOLS, plot_width=800, plot_height=650)
# Creates the polygons.
bk.patches(polygons['lng_list'], polygons['lat_list'], fill_color=polygons['colors'], line_color="gray", source = source)
# RP: add hover
hover = bk.curplot().select(dict(type=HoverTool))
hover.tooltips = OrderedDict([
("Zip", "@hoverZip"),
("Agency", "@hoverAgency"),
("Number of complaints", "@hoverComplaints"),
])
### Zip codes as text on polygons
#for i in range(len(polygons['centerLat_list'])):
# y = polygons['centerLat_list'][i]
# x = polygons['centerLon_list'][i]
# zipCode = zipCodes[i]
# bk.text([x], [y], text=zipCode, angle=0, text_font_size="8pt", text_align="center", text_baseline="middle")
fonts = ["Comic sans MS", "Papyrus", "Curlz", "Impact", "Zapf dingbats", "Comic sans MS", "Papyrus", "Curlz", "Impact", "Zapf Dingbats", "Comic sans MS"]
### Legend
x = -73.66
y = 40.50
#x = -74.25
#y = 40.9
for agency, color in agencyColor.iteritems():
#print "Color: ", a
#print "x:", x
#print "y:", y
bk.rect([x], [y], color = color, width=0.03, height=0.015)
bk.text([x], [y], text = agency, angle=0, text_font_size="7pt", text_align="center", text_baseline="middle")
y = y + 0.015
#bokeh.embed.components(fig, bokeh.resources.CDN)
bk.show()
def drawPlot(shapeFilename, zipBorough, grids, centers, gridLines):
# Read the ShapeFile
dat = shapefile.Reader(shapeFilename)
# Creates a dictionary for zip: {lat_list: [], lng_list: []}.
zipCodes = []
polygons = {'lat_list': [], 'lng_list': [], 'centerLat_list': [], 'centerLon_list': []}
record_index = 0
for r in dat.iterRecords():
currentZip = r[0]
# Keeps only zip codes in NY area.
if currentZip in zipBorough: # was in zipBorough:
# Gets shape for this zip.
shape = dat.shapeRecord(record_index).shape
for part in range(len(shape.parts)):
zipCodes.append(currentZip)
start = shape.parts[part]
if part == len(shape.parts) - 1:
end = len(shape.points)
else:
end = shape.parts[part + 1]
points = shape.points[start : end]
# Breaks into lists for lat/lng.
lngs = [p[0] for p in points]
lats = [p[1] for p in points]
# Calculate centers
center_lngs = min(lngs) + (max(lngs) - min(lngs))/2
center_lats = min(lats) + (max(lats) - min(lats))/2
# Store centroids for current part shape
polygons['centerLat_list'].append(center_lats)
polygons['centerLon_list'].append(center_lngs)
# Stores lat/lng for current zip shape.
polygons['lng_list'].append(lngs)
polygons['lat_list'].append(lats)
record_index += 1
# Creates the Plot
bk.output_file("problem3.html")
bk.hold()
north = 40.915
east = -73.651
south = 40.496
west = -74.256
width = east - west
height = north - south
x_range = [west - 0.05 * width, east + 0.05 * width]
y_range = [south - 0.05 * height, north + 0.05 * height]
TOOLS="pan,wheel_zoom,box_zoom,reset,previewsave"
fig = bk.figure(title="311 Complaints by Zip Code", \
tools=TOOLS, background_fill = "#f8f8f8", x_range = x_range, y_range = y_range)
circleSizes = [item for sublist in grids['log_counts'] for item in sublist]
# Creates the polygons
cellWidth = gridLines['vLines'][1]-gridLines['vLines'][0]
cellHeight = gridLines['hLines'][1] - gridLines['hLines'][0]
bk.patches(polygons['lng_list'], polygons['lat_list'], fill_color="#fee8c8", line_color="gray")
circleSizes = [0.009 * (size ** 3.7) for size in circleSizes]
bk.scatter(centers['lon'], centers['lat'], size = circleSizes, alpha = 0.4, line_color = None, fill_color = 'red')
bk.hold()
#print type(centers['lon'])
circleSizeArr = np.array(circleSizes)
maxSize = np.max(circleSizeArr)
circleSizeArr[circleSizeArr == 0] = 100
minSize = np.min(circleSizeArr)
#print minSize, maxSize
legendN = 5
legendCircles = list(np.linspace(minSize, maxSize, legendN))
legendCounts = [str(int(math.exp(((size/0.009) ** (1.0/3.7))))) + " complaints" for size in legendCircles]
#print legendCircles
fakeScatter = [0 for x in range(legendN)]
fakeScatterX = [-74.23 for x in range(legendN)]
fakeScatterXtext = [-74.23 + 0.05 for x in range(legendN)]
#fakeScatterY = [40.8 + 0.028*y for y in range(legendN)]
fakeScatterY = [40.8, 40.8 + 0.02, 40.8 + 0.036, 40.8 + 0.056,40.8 + 0.083]
#print fakeScatterX, type(fakeScatterX)
#print fakeScatterY, type(fakeScatterY)
bk.scatter(fakeScatterX, fakeScatterY, size = legendCircles, fill_color = 'red', line_color = None, alpha = 0.4)
bk.text(fakeScatterXtext[1:], fakeScatterY[1:], text = legendCounts[1:], angle = 0, text_align = "left", text_font_size = "7pt", text_baseline = 'middle')
#for i in range(len(fakeScatter)):
# bk.scatter([fakeScatter[i]], [fakeScatter[i]], size = [legendCircles[i]], legend = int(legendCircles[i]), color = 'red', fill_line = None, alpha = 0.4)
# Disable background grid
bk.grid().grid_line_color = None
#print centers
### Legend
#x = -74.25
#y = 40.8
#height = 0.003
#legend_box_y = y + 0.5 * height * len(legendColors)
#bk.rect([x+0.032], [legend_box_y], width = 0.12, height = height*len(legendColors)*1.15, color = "#ffffff", line_color = "gray")
##x = -74.25
##y = 40.9
#for color in legendColors:
## #print "Color: ", a
## #print "x:", x
## #print "y:", y
##
# bk.rect([x], [y], color = color, width=0.03, height=height)
# #bk.text([x], [y], text = agency, angle=0, text_font_size="7pt", text_align="center", text_baseline="middle")
# y = y + height
#legend_bottom_y = 40.797
#legend_top_y = legend_bottom_y + 0.92 * height * len(legendColors)
#bk.text([-74.225], [legend_bottom_y], text = agency2, angle = 0, text_font_size = "7pt", text_align = "left")
#bk.text([-74.225], [legend_top_y], text = agency1, angle = 0, text_font_size = "7pt", text_align = "left")
#bokeh.embed.components(fig, bokeh.resources.CDN)
bk.show()
def drawPlot(shapeFilename, zipBorough, zipMaxAgency):
# Read the ShapeFile
dat = shapefile.Reader(shapeFilename)
# Creates a dictionary for zip: {lat_list: [], lng_list: []}.
zipCodes = []
hoverZip = []
hoverAgency = []
hoverComplaints = []
polygons = {
'lat_list': [],
'lng_list': [],
'centerLat_list': [],
'centerLon_list': []
}
record_index = 0
for r in dat.iterRecords():
currentZip = r[0]
# Keeps only zip codes in NY area.
if currentZip in zipMaxAgency: # was in zipBorough:
# zipCodes.append(currentZip) # moving this line into the parts loop
# Gets shape for this zip.
shape = dat.shapeRecord(record_index).shape
for part in range(len(shape.parts)):
zipCodes.append(currentZip)
hoverZip.append(currentZip)
hoverAgency.append(zipMaxAgency[currentZip][0])
hoverComplaints.append(zipMaxAgency[currentZip][1])
start = shape.parts[part]
if part == len(shape.parts) - 1:
end = len(shape.points)
else:
end = shape.parts[part + 1]
points = shape.points[start:end]
# Breaks into lists for lat/lng.
lngs = [p[0] for p in points]
lats = [p[1] for p in points]
# Calculate centers
center_lngs = min(lngs) + (max(lngs) - min(lngs)) / 2
center_lats = min(lats) + (max(lats) - min(lats)) / 2
# Store centroids for current part shape
polygons['centerLat_list'].append(center_lats)
polygons['centerLon_list'].append(center_lngs)
# Stores lat/lng for current zip shape.
polygons['lng_list'].append(lngs)
polygons['lat_list'].append(lats)
record_index += 1
# Palette
##d9d9d9
brewer11 = [
'#8dd3c7', '#ffffb3', '#bebada', '#fb8072', '#80b1d3', '#fdb462',
'#b3de69', '#fccde5', '#d9d9d9', '#bc80bd', '#ccebc5'
]
#brewer11 = ['#a6cee3', '#1f78b4','#b2df8a','#33a02c','#fb9a99','#e31a1c','#fdbf6f','#ff7f00','#cab2d6','#6a3d9a','#ffff99']
#agencies = sorted(list({zipMaxAgency[zipCode] for zipCode in zipMaxAgency}))
biggestComplaints = {}
for zz, aa in zipMaxAgency.iteritems():
if aa[0] in biggestComplaints:
biggestComplaints[aa[0]] += 1
else:
biggestComplaints[aa[0]] = 1
# sorting agencies by number of zip codes (to try to get better colors)
agencies = list(biggestComplaints.iteritems())
agencies = sorted(agencies, key=lambda x: x[1], reverse=True)
agencies = [agency[0] for agency in agencies]
# Assign colors to agencies
agencyColor = {agencies[i]: brewer11[i] for i in range(len(brewer11))}
polygons['colors'] = [
agencyColor[zipMaxAgency[zipCode][0]] for zipCode in zipCodes
]
# Prepare hover
#source = bk.ColumnDataSource(data=dict(hoverAgency=hoverAgency, hoverZip=hoverZip, hoverComplaintCount=hoverComplaintCount,))
source = bk.ColumnDataSource(data=dict(hoverZip=hoverZip,
hoverAgency=hoverAgency,
hoverComplaints=hoverComplaints), )
# Creates the Plot
bk.output_file("problem1.html")
bk.hold()
TOOLS = "pan,wheel_zoom,box_zoom,reset,previewsave,hover"
fig = bk.figure(title="311 Complaints by Zip Code", \
tools=TOOLS, plot_width=800, plot_height=650)
# Creates the polygons.
bk.patches(polygons['lng_list'],
polygons['lat_list'],
fill_color=polygons['colors'],
line_color="gray",
source=source)
# RP: add hover
hover = bk.curplot().select(dict(type=HoverTool))
hover.tooltips = OrderedDict([
("Zip", "@hoverZip"),
("Agency", "@hoverAgency"),
("Number of complaints", "@hoverComplaints"),
])
### Zip codes as text on polygons
#for i in range(len(polygons['centerLat_list'])):
# y = polygons['centerLat_list'][i]
# x = polygons['centerLon_list'][i]
# zipCode = zipCodes[i]
# bk.text([x], [y], text=zipCode, angle=0, text_font_size="8pt", text_align="center", text_baseline="middle")
fonts = [
"Comic sans MS", "Papyrus", "Curlz", "Impact", "Zapf dingbats",
"Comic sans MS", "Papyrus", "Curlz", "Impact", "Zapf Dingbats",
"Comic sans MS"
]
### Legend
x = -73.66
y = 40.50
#x = -74.25
#y = 40.9
for agency, color in agencyColor.iteritems():
#print "Color: ", a
#print "x:", x
#print "y:", y
bk.rect([x], [y], color=color, width=0.03, height=0.015)
bk.text([x], [y],
text=agency,
angle=0,
text_font_size="7pt",
text_align="center",
text_baseline="middle")
y = y + 0.015
#bokeh.embed.components(fig, bokeh.resources.CDN)
bk.show()
def drawPlot(shapeFilename, zipBorough, grids, centers, gridLines):
# Read the ShapeFile
dat = shapefile.Reader(shapeFilename)
# Creates a dictionary for zip: {lat_list: [], lng_list: []}.
zipCodes = []
polygons = {
'lat_list': [],
'lng_list': [],
'centerLat_list': [],
'centerLon_list': []
}
record_index = 0
for r in dat.iterRecords():
currentZip = r[0]
# Keeps only zip codes in NY area.
if currentZip in zipBorough: # was in zipBorough:
# Gets shape for this zip.
shape = dat.shapeRecord(record_index).shape
for part in range(len(shape.parts)):
zipCodes.append(currentZip)
start = shape.parts[part]
if part == len(shape.parts) - 1:
end = len(shape.points)
else:
end = shape.parts[part + 1]
points = shape.points[start:end]
# Breaks into lists for lat/lng.
lngs = [p[0] for p in points]
lats = [p[1] for p in points]
# Calculate centers
center_lngs = min(lngs) + (max(lngs) - min(lngs)) / 2
center_lats = min(lats) + (max(lats) - min(lats)) / 2
# Store centroids for current part shape
polygons['centerLat_list'].append(center_lats)
polygons['centerLon_list'].append(center_lngs)
# Stores lat/lng for current zip shape.
polygons['lng_list'].append(lngs)
polygons['lat_list'].append(lats)
record_index += 1
# Creates the Plot
bk.output_file("problem3.html")
bk.hold()
north = 40.915
east = -73.651
south = 40.496
west = -74.256
width = east - west
height = north - south
x_range = [west - 0.05 * width, east + 0.05 * width]
y_range = [south - 0.05 * height, north + 0.05 * height]
TOOLS = "pan,wheel_zoom,box_zoom,reset,previewsave"
fig = bk.figure(title="311 Complaints by Zip Code", \
tools=TOOLS, background_fill = "#f8f8f8", x_range = x_range, y_range = y_range)
circleSizes = [item for sublist in grids['log_counts'] for item in sublist]
# Creates the polygons
cellWidth = gridLines['vLines'][1] - gridLines['vLines'][0]
cellHeight = gridLines['hLines'][1] - gridLines['hLines'][0]
bk.patches(polygons['lng_list'],
polygons['lat_list'],
fill_color="#fee8c8",
line_color="gray")
circleSizes = [0.009 * (size**3.7) for size in circleSizes]
bk.scatter(centers['lon'],
centers['lat'],
size=circleSizes,
alpha=0.4,
line_color=None,
fill_color='red')
bk.hold()
#print type(centers['lon'])
circleSizeArr = np.array(circleSizes)
maxSize = np.max(circleSizeArr)
circleSizeArr[circleSizeArr == 0] = 100
minSize = np.min(circleSizeArr)
#print minSize, maxSize
legendN = 5
legendCircles = list(np.linspace(minSize, maxSize, legendN))
legendCounts = [
str(int(math.exp(((size / 0.009)**(1.0 / 3.7))))) + " complaints"
for size in legendCircles
]
#print legendCircles
fakeScatter = [0 for x in range(legendN)]
fakeScatterX = [-74.23 for x in range(legendN)]
fakeScatterXtext = [-74.23 + 0.05 for x in range(legendN)]
#fakeScatterY = [40.8 + 0.028*y for y in range(legendN)]
fakeScatterY = [
40.8, 40.8 + 0.02, 40.8 + 0.036, 40.8 + 0.056, 40.8 + 0.083
]
#print fakeScatterX, type(fakeScatterX)
#print fakeScatterY, type(fakeScatterY)
bk.scatter(fakeScatterX,
fakeScatterY,
size=legendCircles,
fill_color='red',
line_color=None,
alpha=0.4)
bk.text(fakeScatterXtext[1:],
fakeScatterY[1:],
text=legendCounts[1:],
angle=0,
text_align="left",
text_font_size="7pt",
text_baseline='middle')
#for i in range(len(fakeScatter)):
# bk.scatter([fakeScatter[i]], [fakeScatter[i]], size = [legendCircles[i]], legend = int(legendCircles[i]), color = 'red', fill_line = None, alpha = 0.4)
# Disable background grid
bk.grid().grid_line_color = None
#print centers
### Legend
#x = -74.25
#y = 40.8
#height = 0.003
#legend_box_y = y + 0.5 * height * len(legendColors)
#bk.rect([x+0.032], [legend_box_y], width = 0.12, height = height*len(legendColors)*1.15, color = "#ffffff", line_color = "gray")
##x = -74.25
##y = 40.9
#for color in legendColors:
## #print "Color: ", a
## #print "x:", x
## #print "y:", y
##
# bk.rect([x], [y], color = color, width=0.03, height=height)
# #bk.text([x], [y], text = agency, angle=0, text_font_size="7pt", text_align="center", text_baseline="middle")
# y = y + height
#legend_bottom_y = 40.797
#legend_top_y = legend_bottom_y + 0.92 * height * len(legendColors)
#bk.text([-74.225], [legend_bottom_y], text = agency2, angle = 0, text_font_size = "7pt", text_align = "left")
#bk.text([-74.225], [legend_top_y], text = agency1, angle = 0, text_font_size = "7pt", text_align = "left")
#bokeh.embed.components(fig, bokeh.resources.CDN)
bk.show()
# Set x-y ranges
x_range = [str(x) for x in range(-1,11)]
y_range = [str(y) for y in range(-1,-11)]
# Make a rect glyph for each factor
bk.rect("xpos","ypos",0.9,0.9,source=source,
x_range=x_range, y_range=y_range,
fill_alpha=0.6, color="color_prime",
tools="resize", title="Prime Factor Visualization"
)
# Add text to display the number for each box
# Use text_props = dict to set properties of text elements
text_props = {
"source": source,
"angle": 0,
"color": "black",
"text_align": "center",
"text_baseline": "middle"
}
bk.text(x=dict(field="xpos", units="data"),
y=dict(field="ypos", units="data"),
text=dict(field="number", units="data"),
text_font_style="bold", text_font_size="12pt", **text_props)
# turn off grid lines - bk.grid().grid_line_color = None
bk.grid().grid_line_color = None
# show the chart
bk.show()
tools="resize,hover,previewsave,ywheel_zoom", title="ESS Lab Layout",
plot_width=1600, plot_height=3200
)
# Use text_props = dict to set properties of text elements
text_props = {
"source": source,
"angle": 0,
"color": "black",
"text_align": "center",
"text_baseline": "middle"
}
# Make a text glyph for each rect glyph to show the cabinet names and locations
bk.text(x=dict(field="posx", units="data"),
y=dict(field="text_locy", units="data"),
text=dict(field="loc", units="data"),
text_font_style="bold", text_font_size="12pt", **text_props)
bk.text(x=dict(field="posx", units="data"),
y=dict(field="text_namey", units="data"),
text=dict(field="name", units="data"),
text_font_style="bold", text_font_size="9pt", **text_props)
bk.text(x=dict(field="posx", units="data"),
y=dict(field="text_suby", units="data"),
text=dict(field="sub", units="data"),
text_font_style="bold", text_font_size="9pt", **text_props)
# turn off grid lines
bk.grid().grid_line_color = None
# Add hovertool to show equipment in tooltips
def make_box_violin_plot_2(data, maxwidth=0.9):
"""
data: dict[Str -> List[Number]]
maxwidth: float
Maximum width of tornado plot within each factor/facet
Returns the plot object
"""
df = pd.DataFrame(columns=["group", "centers", "width", "height", "texts"])
bar_height = 50
bins = [0, 1e1, 1e2, 1e3, 1e4, 1e5, 1e6]
# Compute histograms, while keeping track of max Y values and max counts
for i, (group, vals) in enumerate(data.iteritems()):
hist, edges = np.histogram(vals, bins)
df = df.append(
pd.DataFrame(
dict(
group=group,
centers=np.arange(len(hist)) * bar_height,
width=np.log10(hist),
height=np.ones(hist.shape) * bar_height,
texts=map(str, hist),
)))
df.replace(-np.inf, 0)
# Normalize the widths
df["width"] *= (maxwidth / df["width"].max())
hold()
width, height = 800, 800
figure(plot_width=width,
plot_height=height,
title="Degree Distribution",
tools="previewsave",
x_axis_type=None,
y_axis_type=None,
x_range=[-420, 420],
y_range=[-420, 420],
x_axis_label="Number of nodes (log)",
y_label="distribution of degree",
min_border=0,
outline_line_color=None,
background_fill="#f0e1d2",
border_fill="#f0e1d2")
size = len(df)
rect(np.zeros(size),
df["centers"],
height=[50 for i in range(size)],
width=df["width"] * width * .8)
text(np.zeros(size),
df["centers"],
text=df["texts"],
angle=np.zeros(size),
text_color=["#000000"] + ["#FFFFFF" for i in xrange(size - 1)],
text_align="center",
text_baseline="middle")
text(np.ones(size + 1) * -width / 2,
[(idx - 0.75) * bar_height for idx in range(size + 1)],
text=map(str, map(int, bins)),
angle=0)
show()
