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