def create_legend(x_pos, y_pos, color_dict, figure, all_failures, num_fails_to_list):
#Create the Legend for the types of failures we see day to day
for legend,color in color_dict.iteritems() :
figure.circle(x=x_pos, y=y_pos, radius=0, color=color, legend=legend)
figure.legend.orientation = "bottom_left"
def step(counts, bins, label, color, figure):
'''
Add a step plot to 'figure', inplace of a bar plot
Input:
- counts : array-like
Y-axis values
- bins : array-like
Limiting values for x-axis bins
- label : string
Label for this distribution
- color : string
Code defining a color; see ~booq.plot.Colors
- figure : ~pandas.plotting.figure
Output:
- Figure : ~bokeh.plotting.figure
'''
_y,_x = histogram2stepfunction(counts,bins)
figure.line(x=_x,
y=_y,
#line_color="#D95B43",line_width=2,
line_color=color,line_width=2,
legend='label')
import numpy as np
_x = np.diff(bins)/2+bins[:-1]
figure.circle(x=_x,
y=_y,
#line_color="#D95B43",line_width=2,
line_color=color,line_width=2,
fill_color="white",fill_alpha=1,
size=9,
legend='label')
return figure
def add_multiline_and_circle_glyph_to_plot(figure: 'Bokeh Figure', legend: tuple, column_data_source: 'CDS for Bokeh figure', circle_size: int = 8, line_1_color: str='#CC0000', line_2_color: str='orange') -> 'Bokeh Figure':
"""Adds multiple lines + circle glyphs on Bokeh figure, initializes legend and return Bokeh figure."""
figure = DataVisualizationUtils.add_multiline_to_plot(figure, legend, column_data_source)
figure.circle(x='x', y='y1', fill_color=line_1_color,line_color=line_1_color, size=circle_size, source=column_data_source)
figure.circle(x='x', y='y2', fill_color=line_2_color, line_color=line_2_color, size=circle_size, source=column_data_source)
return figure
def bokeh_draw_court(figure, line_width=1, line_color='gray'):
"""Returns a figure with the basketball court lines drawn onto it"""
# hoop
figure.circle(x=0, y=0, radius=7.5, fill_alpha=0,
line_color=line_color, line_width=line_width)
# backboard
figure.line(x=range(-30,31), y=-7.5, line_color=line_color)
# The paint
# outerbox
figure.rect(x=0, y=47.5, width=160, height=190,fill_alpha=0,
line_color=line_color, line_width=line_width)
# innerbox
# left inner box line
figure.line(x=-60, y=np.arange(-47.5, 143.5), line_color=line_color,
line_width=line_width)
# right inner box line
figure.line(x=60, y=np.arange(-47.5, 143.5), line_color=line_color,
line_width=line_width)
# Restricted Zone
figure.arc(x=0, y=0, radius=40, start_angle=pi, end_angle=0,
line_color=line_color, line_width=line_width)
# top free throw arc
figure.arc(x=0, y=142.5, radius=60, start_angle=pi, end_angle=0,
line_color=line_color)
# bottome free throw arc
figure.arc(x=0, y=142.5, radius=60, start_angle=0, end_angle=pi,
line_color=line_color, line_dash="dashed")
# Three point line
# corner three point lines
figure.line(x=-220, y=np.arange(-47.5, 92.5), line_color=line_color,
line_width=line_width)
figure.line(x=220, y=np.arange(-47.5, 92.5), line_color=line_color,
line_width=line_width)
# # three point arc
figure.arc(x=0, y=0, radius=237.5, start_angle=3.528, end_angle=-0.3863,
line_color=line_color, line_width=line_width)
# add center court
# outer center arc
figure.arc(x=0, y=422.5, radius=60, start_angle=0, end_angle=pi,
line_color=line_color, line_width=line_width)
# inner center arct
figure.arc(x=0, y=422.5, radius=20, start_angle=0, end_angle=pi,
line_color=line_color, line_width=line_width)
# outer lines, consistting of half court lines and out of bounds
# lines
figure.rect(x=0, y=187.5, width=500, height=470, fill_alpha=0,
line_color=line_color, line_width=line_width)
return figure
def bokeh_draw_court(figure, line_width=1, line_color='gray'):
"""Returns a figure with the basketball court lines drawn onto it"""
# hoop
figure.circle(x=0, y=0, radius=7.5, fill_alpha=0,
line_color=line_color, line_width=line_width)
# backboard
figure.line(x=range(-30,31), y=-7.5, line_color=line_color)
# The paint
# outerbox
figure.rect(x=0, y=47.5, width=160, height=190,fill_alpha=0,
line_color=line_color, line_width=line_width)
# innerbox
# left inner box line
figure.line(x=-60, y=np.arange(-47.5, 143.5), line_color=line_color,
line_width=line_width)
# right inner box line
figure.line(x=60, y=np.arange(-47.5, 143.5), line_color=line_color,
line_width=line_width)
# Restricted Zone
figure.arc(x=0, y=0, radius=40, start_angle=pi, end_angle=0,
line_color=line_color, line_width=line_width)
# top free throw arc
figure.arc(x=0, y=142.5, radius=60, start_angle=pi, end_angle=0,
line_color=line_color)
# bottome free throw arc
figure.arc(x=0, y=142.5, radius=60, start_angle=0, end_angle=pi,
line_color=line_color, line_dash="dashed")
# Three point line
# corner three point lines
figure.line(x=-220, y=np.arange(-47.5, 92.5), line_color=line_color,
line_width=line_width)
figure.line(x=220, y=np.arange(-47.5, 92.5), line_color=line_color,
line_width=line_width)
# # three point arc
figure.arc(x=0, y=0, radius=237.5, start_angle=3.528, end_angle=-0.3863,
line_color=line_color, line_width=line_width)
# add center court
# outer center arc
figure.arc(x=0, y=422.5, radius=60, start_angle=0, end_angle=pi,
line_color=line_color, line_width=line_width)
# inner center arct
figure.arc(x=0, y=422.5, radius=20, start_angle=0, end_angle=pi,
line_color=line_color, line_width=line_width)
# outer lines, consistting of half court lines and out of bounds
# lines
figure.rect(x=0, y=187.5, width=500, height=470, fill_alpha=0,
line_color=line_color, line_width=line_width)
return figure
def addPlotsToFigure(figure, section):
"""
Add lines or scatter to the figure
"""
try:
figure.xaxis.ticker.desired_num_ticks = 30
except AttributeError as err:
logging.info(f"AttributeError: {err}")
print("bokeh package needs to be updated (pip install bokeh -U)")
sys.exit()
for i, column in enumerate(plotObject.plots[section]["columns"]):
# assert that it is present in dataframe
if column not in plotObject.data.columns:
logging.info(f"Column not found: {column}")
continue
# get boolean with rows without na. Only those will be plotted
bool_not_na = (~pd.isna(plotObject.data.loc[:, column])).to_list()
if re.search(r"^line$", plotObject.plots[section]['plotType'][i],
re.IGNORECASE):
# If line...
figure.line(
plotObject.data.loc[bool_not_na,
plotObject.plots[section]['x_axis']],
plotObject.data.loc[bool_not_na, column],
line_width=2,
color=d3['Category20'][20][plotObject.color],
legend_label=column,
name=column)
elif re.search(r"^scatter$", plotObject.plots[section]['plotType'][i],
re.IGNORECASE):
# If scatter...
figure.circle(
plotObject.data.loc[bool_not_na,
plotObject.plots[section]['x_axis']],
plotObject.data.loc[bool_not_na, column],
size=1,
color=d3['Category20'][20][plotObject.color],
legend_label=column,
name=column)
# Change color for the next plot
plotObject.color += 2 if plotObject.color < 18 else 17
# plot threshold
figure = plot_threshold(figure, section)
# plot peaks of interest
figure = plot_pleak(figure, section)
return figure
def plot_point(figure,
lat,
lon,
alpha=0.5,
color="magenta",
conver_to_mercator=True):
if conver_to_mercator:
lat, lon = gps_loc_to_web_mercator(lat, lon)
figure.circle(x=lat, y=lon, size=4, alpha=alpha, color=color)
return figure
def circle_values(figure, xdata, ydata):
"""
Args: figure = basic figure generated with figure_generator
xdata = dataset for x axis
ydata = dataset for y axis
Return: circle glyph
"""
return figure.circle(x=xdata, y=ydata)
def __plot_stem_and_bulb(figure, series, color, name):
figure.circle(x="index",
y=name,
source=ColumnDataSource(series.to_frame()),
alpha=0.5,
size=10,
color=color)
figure.segment(x0='index',
x1='index',
y0=0,
y1=name,
source=ColumnDataSource(series.to_frame()),
line_width=1,
color=color)
return figure
def x_values(figure, xdata, ydata):
"""
Args: figure = basic figure generated with figure_generator
xdata = dataset for x axis
ydata = dataset for y axis
Return: x glyph overlayed onto circle glyph figure
"""
return figure.circle(x=xdata, y=ydata)
def add_calculated_centroid_figure_mouseover(figure,
centroid,
lat_col="latitude",
lon_col="longitude",
legend=None,
point_color="magenta",
point_size=3,
fill_color="magenta",
cluster_alpha=0.3,
to_mercator=True):
if to_mercator:
lon, lat = gps_loc_to_web_mercator(lat=centroid[lat_col],
lon=centroid[lon_col])
centroid_circle = figure.circle(lon, lat)
else:
centroid_circle = figure.circle(lon=centroid[lon_col],
lat=centroid[lat_col])
centroid_mercator = gps_loc_to_web_mercator(centroid[lat_col],
centroid[lon_col])
sr_source = ColumnDataSource(data=dict(lon=centroid_mercator[0],
lat=centroid_mercator[0],
sr_id=centroid["sr_id"]))
figure.circle("lon",
"lat",
color=point_color,
size=point_size,
legend=legend,
source=sr_source)
glyph = centroid_circle.glyph
glyph.size = 20
glyph.fill_alpha = cluster_alpha
glyph.fill_color = fill_color
glyph.line_alpha = cluster_alpha
glyph.line_color = "firebrick"
glyph.line_dash = [6, 3]
glyph.line_width = 1
def plot_poi(data,
title,
lat_col="latitude",
lon_col="longitude",
width=800,
height=600,
color=pick_random_color(),
figure=None):
if figure is None:
figure = mercator_fig(title,
point_mercator1=None,
point_mercator2=None,
width=width,
height=height)
mercator_loc_df = pd.DataFrame(
user_data_gps_to_web_mercator(data, lat_col=lat_col, lon_col=lon_col))
figure.circle(x=mercator_loc_df[0],
y=mercator_loc_df[1],
size=5,
alpha=0.3,
color=color)
return figure
def add_calculated_centroid_figure(figure,
centroid,
lat_col="latitude",
lon_col="longitude",
legend=None,
point_color="magenta",
point_size=3,
fill_color="magenta",
cluster_alpha=0.3,
to_mercator=True):
if to_mercator:
lon, lat = gps_loc_to_web_mercator(lat=centroid[lat_col],
lon=centroid[lon_col])
centroid_circle = figure.circle(lon, lat)
else:
centroid_circle = figure.circle(lon=centroid[lon_col],
lat=centroid[lat_col])
centroid_mercator = gps_loc_to_web_mercator(centroid[lat_col],
centroid[lon_col])
if legend is None:
figure.circle(centroid_mercator[0],
centroid_mercator[1],
color=point_color,
size=point_size)
else:
figure.circle(centroid_mercator[0],
centroid_mercator[1],
color=point_color,
size=point_size,
legend=legend)
glyph = centroid_circle.glyph
glyph.size = 20
glyph.fill_alpha = cluster_alpha
glyph.fill_color = fill_color
glyph.line_alpha = cluster_alpha
glyph.line_color = "firebrick"
glyph.line_dash = [6, 3]
glyph.line_width = 1
def bokeh_draw_court(figure, line_color='gray', line_width=1):
"""Returns a figure with the basketball court lines drawn onto it
This function draws a court based on the x and y-axis values that the NBA
stats API provides for the shot chart data. For example the center of the
hoop is located at the (0,0) coordinate. Twenty-two feet from the left of
the center of the hoop in is represented by the (-220,0) coordinates.
So one foot equals +/-10 units on the x and y-axis.
Parameters
----------
figure : Bokeh figure object
The Axes object to plot the court onto.
line_color : str, optional
The color of the court lines. Can be a a Hex value.
line_width : float, optional
The linewidth the of the court lines in pixels.
Returns
-------
figure : Figure
The Figure object with the court on it.
"""
# hoop
figure.circle(x=0,
y=0,
radius=7.5,
fill_alpha=0,
line_color=line_color,
line_width=line_width)
# backboard
figure.line(x=range(-30, 31), y=-12.5, line_color=line_color)
# The paint
# outerbox
figure.rect(x=0,
y=47.5,
width=160,
height=190,
fill_alpha=0,
line_color=line_color,
line_width=line_width)
# innerbox
# left inner box line
figure.line(x=-60,
y=np.arange(-47.5, 143.5),
line_color=line_color,
line_width=line_width)
# right inner box line
figure.line(x=60,
y=np.arange(-47.5, 143.5),
line_color=line_color,
line_width=line_width)
# Restricted Zone
figure.arc(x=0,
y=0,
radius=40,
start_angle=pi,
end_angle=0,
line_color=line_color,
line_width=line_width)
# top free throw arc
figure.arc(x=0,
y=142.5,
radius=60,
start_angle=pi,
end_angle=0,
line_color=line_color)
# bottome free throw arc
figure.arc(x=0,
y=142.5,
radius=60,
start_angle=0,
end_angle=pi,
line_color=line_color,
line_dash="dashed")
# Three point line
# corner three point lines
figure.line(x=-220,
y=np.arange(-47.5, 92.5),
line_color=line_color,
line_width=line_width)
figure.line(x=220,
y=np.arange(-47.5, 92.5),
line_color=line_color,
line_width=line_width)
# # three point arc
figure.arc(x=0,
y=0,
radius=237.5,
start_angle=3.528,
end_angle=-0.3863,
line_color=line_color,
line_width=line_width)
# add center court
# outer center arc
figure.arc(x=0,
y=422.5,
radius=60,
start_angle=0,
end_angle=pi,
line_color=line_color,
line_width=line_width)
# inner center arct
figure.arc(x=0,
y=422.5,
radius=20,
start_angle=0,
end_angle=pi,
line_color=line_color,
line_width=line_width)
# outer lines, consistting of half court lines and out of bounds lines
figure.rect(x=0,
y=187.5,
width=500,
height=470,
fill_alpha=0,
line_color=line_color,
line_width=line_width)
return figure
def _draw_court(self, figure, line_width=1):
import numpy as np
pi = 3.14
# hoop
figure.circle(x=0,
y=0,
radius=7.5,
fill_alpha=0,
line_color=self.f_color,
line_width=line_width)
# backboard
figure.line(x=range(-30, 31), y=-12.5, line_color=self.f_color)
# The paint
# outerbox
figure.rect(x=0,
y=47.5,
width=160,
height=190,
fill_alpha=0,
line_color=self.f_color,
line_width=line_width)
# innerbox
# left inner box line
figure.line(x=-60,
y=np.arange(-47.5, 143.5),
line_color=self.f_color,
line_width=line_width)
# right inner box line
figure.line(x=60,
y=np.arange(-47.5, 143.5),
line_color=self.f_color,
line_width=line_width)
# Restricted Zone
figure.arc(x=0,
y=0,
radius=40,
start_angle=pi,
end_angle=0,
line_color=self.f_color,
line_width=line_width)
# top free throw arc
figure.arc(x=0,
y=142.5,
radius=60,
start_angle=pi,
end_angle=0,
line_color=self.f_color)
# bottome free throw arc
figure.arc(x=0,
y=142.5,
radius=60,
start_angle=0,
end_angle=pi,
line_color=self.f_color,
line_dash="dashed")
# Three point line
# corner three point lines
figure.line(x=-220,
y=np.arange(-47.5, 92.5),
line_color=self.f_color,
line_width=line_width)
figure.line(x=220,
y=np.arange(-47.5, 92.5),
line_color=self.f_color,
line_width=line_width)
# # three point arc
figure.arc(x=0,
y=0,
radius=237.5,
start_angle=3.528,
end_angle=-0.3863,
line_color=self.f_color,
line_width=line_width)
return figure
def bdot(self,
dataname,
figurename,
width=1,
color=1,
mode='dot',
set_colormap=True):
"""-----------------------------------------------------------------------------------------
Bokeh plot of dots in the main panel, and colorbar in the legend panel
:param dataname: string, name of a dataframe in self.frame
:param figurename: string, a figure defined in setupBokeh and stored in self.figure
:param width: boolean, scale size of markers by the score
:param color: boolean, scale the color of the markers by the score
:param mode: string, if dot use the circle renderer, otherwise segment renderer
:param set_colormap: boolean, set the colormap based on score range, turn off for second
plot to use the same scale
:return: True
-----------------------------------------------------------------------------------------"""
data = self.frame[dataname]
figure = self.figure[figurename]
legend = self.figure['legend']
window = self.window
threshold = self.threshold
alpha = self.alpha
scoremin, scoremax = self.valueMinMax(data['score'])
if width == 1:
self.scaleColumn('dots', 'score', 'size',
(threshold - 1, scoremax),
(self.mindotsize, self.maxdotsize))
else:
data['size'] = [self.mindotsize for _ in range(len(data['score']))]
if color == 1:
pass
else:
data['score'] = [scoremax for _ in range(len(data['score']))]
if set_colormap:
if color == 1:
cmap = LinearColorMapper(self.palette,
low=max(threshold - 1.0,
scoremin - 1),
high=scoremax)
else:
cmap = LinearColorMapper(self.palette,
low=threshold - 0.1,
high=threshold)
self.cmap = cmap
else:
cmap = self.cmap
source = ColumnDataSource(data)
if mode == 'dot':
figure.circle(source=source,
x='x',
y='y',
size='size',
line_color=transform('score', cmap),
line_alpha=alpha,
fill_color=transform('score', cmap),
fill_alpha=alpha)
else:
# line mode
figure.segment(source=source,
x0='x',
x1='x1',
y0='y',
y1='y1',
line_width='size',
line_color=transform('score', cmap),
alpha=alpha)
# color bar is in a separate window, self.legend, so it doesn't disturb the
# aspect ratio
if color:
color_bar = ColorBar(color_mapper=cmap,
label_standoff=3,
bar_line_color='black',
scale_alpha=alpha,
width=20,
margin=0,
location=(0, 0),
major_tick_in=20,
major_tick_out=5,
major_tick_line_color='black')
legend.add_layout(color_bar, 'left')
return True
def bokeh_draw_court(figure, line_color='gray', line_width=1):
"""Returns a figure with the basketball court lines drawn onto it
This function draws a court based on the x and y-axis values that the NBA
stats API provides for the shot chart data. For example the center of the
hoop is located at the (0,0) coordinate. Twenty-two feet from the left of
the center of the hoop in is represented by the (-220,0) coordinates.
So one foot equals +/-10 units on the x and y-axis.
Parameters
----------
figure : Bokeh figure object
The Axes object to plot the court onto.
line_color : str, optional
The color of the court lines. Can be a a Hex value.
line_width : float, optional
The linewidth the of the court lines in pixels.
Returns
-------
figure : Figure
The Figure object with the court on it.
"""
# hoop
figure.circle(x=0, y=0, radius=7.5, fill_alpha=0,
line_color=line_color, line_width=line_width)
# backboard
figure.line(x=range(-30, 31), y=-12.5, line_color=line_color)
# The paint
# outerbox
figure.rect(x=0, y=47.5, width=160, height=190, fill_alpha=0,
line_color=line_color, line_width=line_width)
# innerbox
# left inner box line
figure.line(x=-60, y=np.arange(-47.5, 143.5), line_color=line_color,
line_width=line_width)
# right inner box line
figure.line(x=60, y=np.arange(-47.5, 143.5), line_color=line_color,
line_width=line_width)
# Restricted Zone
figure.arc(x=0, y=0, radius=40, start_angle=pi, end_angle=0,
line_color=line_color, line_width=line_width)
# top free throw arc
figure.arc(x=0, y=142.5, radius=60, start_angle=pi, end_angle=0,
line_color=line_color)
# bottome free throw arc
figure.arc(x=0, y=142.5, radius=60, start_angle=0, end_angle=pi,
line_color=line_color, line_dash="dashed")
# Three point line
# corner three point lines
figure.line(x=-220, y=np.arange(-47.5, 92.5), line_color=line_color,
line_width=line_width)
figure.line(x=220, y=np.arange(-47.5, 92.5), line_color=line_color,
line_width=line_width)
# # three point arc
figure.arc(x=0, y=0, radius=237.5, start_angle=3.528, end_angle=-0.3863,
line_color=line_color, line_width=line_width)
# add center court
# outer center arc
figure.arc(x=0, y=422.5, radius=60, start_angle=0, end_angle=pi,
line_color=line_color, line_width=line_width)
# inner center arct
figure.arc(x=0, y=422.5, radius=20, start_angle=0, end_angle=pi,
line_color=line_color, line_width=line_width)
# outer lines, consistting of half court lines and out of bounds lines
figure.rect(x=0, y=187.5, width=500, height=470, fill_alpha=0,
line_color=line_color, line_width=line_width)
return figure
def first_limit(H_file, H_fit1_df, figure=None):
for value_v in iterate_on_v:
# Selecting each subset of the dataframe corresponding to the desired v value.
H_subset = H_file[H_file['v_value'] == v_serie[value_v]]
# Shifting to numpy for the fit.
H_np_subset = H_subset.to_numpy()
# Building all the Xs values for the fits. Repetition of the same array, as the X values are all the same.
Xs = H_np_subset[:, 1] # Size values are the 2nd column, index = 1
Xs = 1 / Xs # Inverting the values as the graph shows 1/size
poly_X = np.insert(
Xs, 0,
0) # Adding a 0 to the X set to have the value at this point
# Hard coded indexes to take all the T_values, should be ok as long as I do not change the dataframe structure
H_Ys = H_np_subset[:, 2:np.shape(H_np_subset)[1]]
# Creating a figure for the desired v value.
if (v_serie[value_v] == watch_v and figure != None):
ListY = H_Ys.T.tolist()
for plots in np.arange(0, len(ListY), 1):
figure.circle(Xs,
ListY[plots],
legend_label="All T For v=" + str(watch_v),
line_width=1,
color='black',
size=10,
fill_color='white')
#This is the main loop, populating the array with the fitted values
for T in np.arange(0, len(T_serie), 1):
if len(s_serie
) > 1: # Fit only if there are enough points to do so.
H_coeff_poly = np.polyfit(
Xs, H_Ys[:,
T], fit_order_1) # Fitting a polynom on the data
H_poly_Y = np.polyval(
H_coeff_poly, poly_X
) # Calculating the values for each point and get the value at 0
# The point at X=0 is at the beginning of the array, putting it at the right place in the dataframe.
H_fit1_df.iloc[[value_v], [T]] = H_poly_Y[0]
else: # If only one point, just take the value of the point.
H_fit1_df.iloc[[value_v], [T]] = H_Ys[:, T]
H_poly_Y = H_Ys[:, T]
# Showing the fit for the desired v_value
if (v_serie[value_v] == watch_v and figure != None):
figure.line(
poly_X,
H_poly_Y, # Adding points to check the quality of the fit.
legend_label="Fits",
line_width=2,
color=colors[T])
figure.square(0,
H_poly_Y[0],
line_width=1,
color='black',
size=10,
fill_color='white')
return H_fit1_df
