# TRAINS - Example of manual graphs and statistics reporting
#
import math
import numpy as np
from bokeh.models import ColumnDataSource, GraphRenderer, Oval, StaticLayoutProvider
from bokeh.palettes import Spectral5, Spectral8
from bokeh.plotting import figure, output_file, save
from bokeh.sampledata.autompg import autompg_clean as bokeh_df
from bokeh.sampledata.periodic_table import elements
from bokeh.transform import dodge, factor_cmap
from trains import Task, Logger
def report_html_url(logger, iteration=0):
# type: (Logger, int) -> ()
"""
reporting html from url to debug samples section
:param logger: The task.logger to use for sending the plots
:param iteration: The iteration number of the current reports
"""
logger.report_media("html", "url_html", iteration=iteration, url="https://allegro.ai/docs/index.html")
def report_html_periodic_table(logger, iteration=0):
# type: (Logger, int) -> ()
"""
reporting interactive (html) of periodic table to debug samples section
:param logger: The task.logger to use for sending the plots
:param iteration: The iteration number of the current reports
"""
output_file("periodic.html")
periods = ["I", "II", "III", "IV", "V", "VI", "VII"]
groups = [str(x) for x in range(1, 19)]
autompg_clean = elements.copy()
autompg_clean["atomic mass"] = autompg_clean["atomic mass"].astype(str)
autompg_clean["group"] = autompg_clean["group"].astype(str)
autompg_clean["period"] = [periods[x - 1] for x in autompg_clean.period]
autompg_clean = autompg_clean[autompg_clean.group != "-"]
autompg_clean = autompg_clean[autompg_clean.symbol != "Lr"]
autompg_clean = autompg_clean[autompg_clean.symbol != "Lu"]
cmap = {
"alkali metal": "#a6cee3",
"alkaline earth metal": "#1f78b4",
"metal": "#d93b43",
"halogen": "#999d9a",
"metalloid": "#e08d49",
"noble gas": "#eaeaea",
"nonmetal": "#f1d4Af",
"transition metal": "#599d7A",
}
source = ColumnDataSource(autompg_clean)
p = figure(
plot_width=900,
plot_height=500,
title="Periodic Table (omitting LA and AC Series)",
x_range=groups,
y_range=list(reversed(periods)),
toolbar_location=None,
tools="hover",
)
p.rect(
"group",
"period",
0.95,
0.95,
source=source,
fill_alpha=0.6,
legend_label="metal",
color=factor_cmap(
"metal", palette=list(cmap.values()), factors=list(cmap.keys())
),
)
text_props = {"source": source, "text_align": "left", "text_baseline": "middle"}
x = dodge("group", -0.4, range=p.x_range)
r = p.text(x=x, y="period", text="symbol", **text_props)
r.glyph.text_font_style = "bold"
r = p.text(
x=x, y=dodge("period", 0.3, range=p.y_range), text="atomic number", **text_props
)
r.glyph.text_font_size = "8pt"
r = p.text(
x=x, y=dodge("period", -0.35, range=p.y_range), text="name", **text_props
)
r.glyph.text_font_size = "5pt"
r = p.text(
x=x, y=dodge("period", -0.2, range=p.y_range), text="atomic mass", **text_props
)
r.glyph.text_font_size = "5pt"
p.text(
x=["3", "3"],
y=["VI", "VII"],
text=["LA", "AC"],
text_align="center",
text_baseline="middle",
)
p.hover.tooltips = [
("Name", "@name"),
("Atomic number", "@{atomic number}"),
("Atomic mass", "@{atomic mass}"),
("Type", "@metal"),
("CPK color", "$color[hex, swatch]:CPK"),
("Electronic configuration", "@{electronic configuration}"),
]
p.outline_line_color = None
p.grid.grid_line_color = None
p.axis.axis_line_color = None
p.axis.major_tick_line_color = None
p.axis.major_label_standoff = 0
p.legend.orientation = "horizontal"
p.legend.location = "top_center"
save(p)
logger.report_media("html", "periodic_html", iteration=iteration, local_path="periodic.html")
def report_html_groupby(logger, iteration=0):
# type: (Logger, int) -> ()
"""
reporting bokeh groupby (html) to debug samples section
:param logger: The task.logger to use for sending the plots
:param iteration: The iteration number of the current reports
"""
output_file("bar_pandas_groupby_nested.html")
bokeh_df.cyl = bokeh_df.cyl.astype(str)
bokeh_df.yr = bokeh_df.yr.astype(str)
group = bokeh_df.groupby(by=["cyl", "mfr"])
index_cmap = factor_cmap(
"cyl_mfr", palette=Spectral5, factors=sorted(bokeh_df.cyl.unique()), end=1
)
p = figure(
plot_width=800,
plot_height=300,
title="Mean MPG by # Cylinders and Manufacturer",
x_range=group,
toolbar_location=None,
tooltips=[("MPG", "@mpg_mean"), ("Cyl, Mfr", "@cyl_mfr")],
)
p.vbar(
x="cyl_mfr",
top="mpg_mean",
width=1,
source=group,
line_color="white",
fill_color=index_cmap,
)
p.y_range.start = 0
p.x_range.range_padding = 0.05
p.xgrid.grid_line_color = None
p.xaxis.axis_label = "Manufacturer grouped by # Cylinders"
p.xaxis.major_label_orientation = 1.2
p.outline_line_color = None
save(p)
logger.report_media(
"html",
"pandas_groupby_nested_html",
iteration=iteration,
local_path="bar_pandas_groupby_nested.html",
)
def report_html_graph(logger, iteration=0):
# type: (Logger, int) -> ()
"""
reporting bokeh graph (html) to debug samples section
:param logger: The task.logger to use for sending the plots
:param iteration: The iteration number of the current reports
"""
nodes = 8
node_indices = list(range(nodes))
plot = figure(
title="Graph Layout Demonstration",
x_range=(-1.1, 1.1),
y_range=(-1.1, 1.1),
tools="",
toolbar_location=None,
)
graph = GraphRenderer()
graph.node_renderer.data_source.add(node_indices, "index")
graph.node_renderer.data_source.add(Spectral8, "color")
graph.node_renderer.glyph = Oval(height=0.1, width=0.2, fill_color="color")
graph.edge_renderer.data_source.data = dict(start=[0] * nodes, end=node_indices)
# start of layout code
circ = [i * 2 * math.pi / 8 for i in node_indices]
x = [math.cos(i) for i in circ]
y = [math.sin(i) for i in circ]
graph_layout = dict(zip(node_indices, zip(x, y)))
graph.layout_provider = StaticLayoutProvider(graph_layout=graph_layout)
plot.renderers.append(graph)
output_file("graph.html")
save(plot)
logger.report_media("html", "Graph_html", iteration=iteration, local_path="graph.html")
def report_html_image(logger, iteration=0):
# type: (Logger, int) -> ()
"""
reporting bokeh image (html) to debug samples section
:param logger: The task.logger to use for sending the plots
:param iteration: The iteration number of the current reports
"""
# First html
samples = 500
x = np.linspace(0, 10, samples)
y = np.linspace(0, 10, samples)
xx, yy = np.meshgrid(x, y)
d = np.sin(xx) * np.cos(yy)
p = figure(tooltips=[("x", "$x"), ("y", "$y"), ("value", "@image")])
p.x_range.range_padding = p.y_range.range_padding = 0
# must give a vector of image data for image parameter
p.image(image=[d], x=0, y=0, dw=10, dh=10, palette="Spectral11", level="image")
p.grid.grid_line_width = 0.5
output_file("image.html", title="image.py example")
save(p)
logger.report_media("html", "Spectral_html", iteration=iteration, local_path="image.html")
def main():
# Create the experiment Task
task = Task.init(project_name="examples", task_name="html samples reporting")
print('reporting html files into debug samples section')
# Get the task logger,
# You can also call Task.current_task().get_logger() from anywhere in your code.
logger = task.get_logger()
# report html as debug samples
report_html_image(logger)
report_html_graph(logger)
report_html_groupby(logger)
report_html_periodic_table(logger)
report_html_url(logger)
# force flush reports
# If flush is not called, reports are flushed in the background every couple of seconds,
# and at the end of the process execution
logger.flush()
print('We are done reporting, have a great day :)')
if __name__ == "__main__":
main()