def render_bar_chart(
data_barchart: pd.DataFrame,
yscale: str,
plot_width: int,
plot_height: int,
show_yticks: bool,
) -> Figure:
"""
Render a bar chart
"""
colors = [PALETTE[0], PALETTE[2]]
value_type = ["Not Missing", "Missing"]
data = {
"cols": data_barchart.index,
"Not Missing": data_barchart["not missing"],
"Missing": data_barchart["missing"],
}
if show_yticks:
if len(data_barchart) > 10:
plot_width = 28 * len(data_barchart)
fig = Figure(
x_range=data_barchart.index.tolist(),
y_range=[0, 1],
plot_width=plot_width,
plot_height=plot_height,
y_axis_type=yscale,
toolbar_location=None,
tooltips="@cols: @$name{1%} $name",
tools="hover",
)
fig.vbar_stack(
value_type,
x="cols",
width=0.9,
color=colors,
source=data,
legend_label=value_type,
)
fig.legend.location = "top_right"
fig.y_range.start = 0
fig.x_range.range_padding = 0
fig.yaxis.axis_label = "Total Count"
tweak_figure(fig)
relocate_legend(fig, "right")
return fig
def gen_conf_cmatrices(plot_config: Dict, v: pd.DataFrame) -> Figure:
cust_plot_tools = {'x_axis_label': 'Confidence Bucket', **plot_config}
p = Figure(x_range=(v.index.min(), v.index.max()), **cust_plot_tools)
stack_fields = ['tp_ratio', 'tn_ratio', 'fp_ratio', 'fn_ratio']
p.vbar_stack(stackers=stack_fields, x='confidence_bucket', color=dashboard_constants.cust_rg_palette,
source=v, width=1.0)
p = gen_cmatrix_legend(p)
p.grid.minor_grid_line_color = '#eeeeee'
p.xaxis.axis_label_text_font_size = "16px"
p.xaxis.axis_label_text_color = '#003566'
stack_fields.extend(['max_conf_percentile', 'acc'])
p = cmatrix_plot_format(p, stack_fields, dashboard_constants.conf_custom_hover_code)
return p
def gen_temporal_cmatrices(plot_config: Dict, v: pd.DataFrame) -> Figure:
cust_plot_tools = {**plot_config}
v.index = v.index.get_level_values('yweeks').strftime("%b-%d")
v.index.name = 'yweeks'
p = Figure(x_range=v.index.get_level_values('yweeks').tolist(), **cust_plot_tools, css_classes=["cmatrix_fig"])
stack_fields = ['tp_ratio', 'tn_ratio', 'fp_ratio', 'fn_ratio']
p.vbar_stack(stackers=stack_fields, x='yweeks', color=dashboard_constants.cust_rg_palette, source=v, width=1.0)
p = gen_cmatrix_legend(p)
p.grid.minor_grid_line_color = '#eeeeee'
p.xaxis.major_label_orientation = math.pi / 4
p.x_range.range_padding = 0
p.xaxis.major_label_text_font_size = "12px"
p = cmatrix_plot_format(p, stack_fields, dashboard_constants.temporal_custom_hover_code)
return p
def plot_bar_stack(
p: Figure, source: ColumnDataSource, df: pd.DataFrame
) -> List[GlyphRenderer]:
# Plot bar stack.
measurements = list(df["Measurement"].unique())
n_measurements = len(measurements)
color = list((Category20_20 * 2)[:n_measurements])
if "None" in measurements:
color[measurements.index("None")] = "black"
bar_stack = p.vbar_stack(
**BAR_STACK_KWARGS, stackers=measurements, color=color, source=source,
)
stack_hover = HoverTool(
renderers=bar_stack, tooltips=STACK_HOVER_TOOLTIPS,
)
p.add_tools(stack_hover)
# Customize left y-axis range.
p.y_range.start = 0
max_count = bar_stack[0].data_source.data["total"].max() + 1
p.y_range.end = max_count
# Create a legend.
kwargs = LEGEND_KWARGS.copy()
if len(measurements) == 1:
kwargs["location"] = (0, 250)
legend = Legend(
items=[
(measurement, [bar_stack[i]])
for i, measurement in enumerate(measurements)
],
**kwargs,
)
p.add_layout(legend, "right")
return bar_stack
def render_bar_viz(
itmdt: Intermediate,
yscale: str,
plot_width: int,
plot_height: int,
show_yticks: bool,
) -> Figure:
"""
Render a bar chart
"""
# pylint: disable=too-many-arguments
length = itmdt["len_data"]
df = itmdt["data_barchart"]
df = df.copy()
df = df.reset_index()
df.columns = ["col", "values"]
df["val_per"] = df["values"] * length
df["missing"] = length - df["val_per"]
stack_present = df["val_per"].tolist()
stack_missing = df["missing"].tolist()
source = ColumnDataSource(df)
features = source.data["col"].tolist()
colors = [PALETTE[0], PALETTE[2]]
value_type = ["present", "missing"]
data = {
"features": features,
"present": stack_present,
"missing": stack_missing
}
if show_yticks:
if len(df) > 10:
plot_width = 28 * len(df)
fig = Figure(
x_range=features,
plot_width=plot_width,
plot_height=plot_height,
y_axis_type=yscale,
toolbar_location=None,
tooltips="$name @features: @$name",
tools="hover",
)
fig.vbar_stack(
value_type,
x="features",
width=0.9,
color=colors,
source=data,
legend_label=value_type,
)
fig.legend.location = "top_right"
fig.y_range.start = 0
fig.x_range.range_padding = 0.1
tweak_figure(fig)
fig.yaxis.axis_label = "Total Count"
relocate_legend(fig, "right")
return fig
def render_bar_chart(
data: Tuple[np.ndarray, np.ndarray, np.ndarray],
yscale: str,
plot_width: int,
plot_height: int,
) -> Figure:
"""
Render a bar chart for the missing and present values
"""
pres_cnts, null_cnts, cols = data
df = pd.DataFrame({"Present": pres_cnts, "Missing": null_cnts}, index=cols)
if len(df) > 20:
plot_width = 28 * len(df)
fig = Figure(
x_range=list(df.index),
y_range=[0, df["Present"][0] + df["Missing"][0]],
plot_width=plot_width,
plot_height=plot_height,
y_axis_type=yscale,
toolbar_location=None,
tools=[],
title=" ",
)
rend = fig.vbar_stack(
stackers=df.columns,
x="index",
width=0.9,
color=[CATEGORY20[0], CATEGORY20[2]],
source=df,
legend_label=list(df.columns),
)
# hover tool with count and percent
formatter = CustomJSHover(
args=dict(source=ColumnDataSource(df)),
code="""
const columns = Object.keys(source.data)
const cur_bar = special_vars.data_x - 0.5
var ttl_bar = 0
for (let i = 0; i < columns.length; i++) {
if (columns[i] != 'index'){
ttl_bar = ttl_bar + source.data[columns[i]][cur_bar]
}
}
const cur_val = source.data[special_vars.name][cur_bar]
return (cur_val/ttl_bar * 100).toFixed(2)+'%';
""",
)
for i, val in enumerate(df.columns):
hover = HoverTool(
tooltips=[
("Column", "@index"),
(f"{val} count", "@$name"),
(f"{val} percent", "@{%s}{custom}" % rend[i].name),
],
formatters={"@{%s}" % rend[i].name: formatter},
renderers=[rend[i]],
)
fig.add_tools(hover)
fig.yaxis.axis_label = "Row Count"
tweak_figure(fig)
relocate_legend(fig, "left")
fig.frame_width = plot_width
return fig
