Usage

Use the Command Line Tool

colorteller benchmark -h "#8de4d3" -h "#344b46" -h "#74ee65" -h "#238910" -h "#a6c363" -h "#509d99" -wbc True -t test_colorteller_cmd

• -h specifies a color in hex format;
• -t specifies the folder to hold all the results (charts, metrics json, etc). It should be a folder.;
• -wbc is True will create benchmark metric charts;

Use in Python Code

Create a ColorTeller Object

from colorteller.teller import ColorTeller

hex_strings = ["#8de4d3", "#344b46", "#74ee65", "#238910", "#a6c363", "#509d99"]

ct = teller.ColorTeller(hex_strings=hex_strings)

To retrieve the properties of the color palette, please refer to colorteller.teller.

Create Benchmarks

from colorteller.teller import ColorTeller
from colorteller.utils import benchmark

hex_strings = ["#8de4d3", "#344b46", "#74ee65", "#238910", "#a6c363", "#509d99"]

ct = teller.ColorTeller(hex_strings=hex_strings)
c = teller.Colors(colorteller=ct)

m = c.metrics(
    methods=[
        benchmark.PerceptualDistanceBenchmark,
        benchmark.LightnessBenchmark
    ]
)

Visualizations

Metric Visualizations

from colorteller import teller
from colorteller.utils import benchmark
from colorteller.visualize import BenchmarkCharts, ApplicationCharts

hex_strings = ["#8de4d3", "#344b46", "#74ee65", "#238910", "#a6c363", "#509d99"]

ct = teller.ColorTeller(hex_strings=hex_strings)

c = teller.Colors(colorteller=ct)

m = c.metrics(
    methods=[benchmark.PerceptualDistanceBenchmark, benchmark.LightnessBenchmark]
)

charts = BenchmarkCharts(metrics=m, save_folder=".")

charts.distance_matrix(show=True)
charts.noticable_matrix(show=True)

Demo Figures Using the Color Palette

from colorteller import teller
from colorteller.utils import benchmark
from colorteller.visualize import BenchmarkCharts, ApplicationCharts

hex_strings = ["#8de4d3", "#344b46", "#74ee65", "#238910", "#a6c363", "#509d99"]

ct = teller.ColorTeller(hex_strings=hex_strings)

c = teller.Colors(colorteller=ct)

ac = ApplicationCharts(colors=c, save_folder=".")

ac.charts(save_to=True)

# One could also create specific charts using the following
# ac.bar_chart(show=True)
# ac.line_chart(show=True)
# ac.scatter_chart(show=True)
# ac.donut_chart(show=True)