Colormaps

The Colormap API is a key feature of the Evo platform, providing a mechanism to create colour mappings and associate them to geoscience data via a colormap.

colormaps in the Evo platform serve as a powerful tool for data exploration and analysis. colormaps contain a range of colours that map colours to data values, simplifying the identification of patterns and trends in the data. By assigning specific colours to important data values, these values can be emphasized for quick and effective interpretation, leading to more informed decision-making. Additionally, a colormap can be used to underscore unusual data values by assigning these values distinctive colours, aiding in pinpointing potential anomalies that could be significant.

Applying the same colormap across datasets within a workspace allows organizations to adopt a common language for visual communication. This shared colour coding enables consistency in data interpretation and visualization, and facilitates comparison of datasets in a standardized manner.

The Colormap API supports three types of colour mappings:

Colormap Type	Description
Continuous	Used for numerical data that varies smoothly. Requires a minimum of two colours and corresponding attribute and gradient controls.
Discrete	Used for numerical data that falls within specific ranges. Requires endpoint definitions and corresponding colours.
Category	Used for non-numerical data. Requires a mapping between categories and colours.

Note: You can visit the Colormaps API OpenAPI schema for a detailed description of how to interact with the API.

Colormap API colour format

Colours in the Colormap API are always defined in RGB order and are arrays of three integer values ranging from 0 to 255:

{
  "colors": [
  [255, 0, 0],
  [0, 255, 0],
  [0, 0, 255],
  ]
}

Colormap types

Continuous

A continuous colormap is used for numerical data that changes gradually. These require a minimum of two colours in the colors array and corresponding attribute and gradient controls. Each colour in the colormap represents a range of data values, and the colours in the colors field transition smoothly from one to another across the range.

Here is an example of a continuous colormap defined in JSON:

{
    "name": "Example Continuous Colormap",
    "colors": [
    [0, 0, 255],
    [255, 0, 0]
    ],
    "attribute_controls": [0, 1],
    "gradient_controls": [0, 1],
    "dtype": "continuous"
}

In this example, the continuous colormap transitions from the colours blue to red. The attribute controls and gradient controls are both set to [0, 1], indicating a linear transition from the colour blue at the lower end of the data range to the colour red at the higher end.

Value	Colour	Gradient Bar	Colour
0.20	Blue	##########----------------------------------------	Red
0.40	Blue	####################------------------------------	Red
0.60	Blue	##############################--------------------	Red
0.80	Blue	########################################----------	Red
1.00	Blue	##################################################	Red

As seen above, colours transition smoothly between the colours in the colors array.

Note: Continuous colormaps must have between 2 and 1024 colors.

Discrete

A discrete colormap is used for numerical data that falls within specific ranges. These require endpoint definitions and corresponding colours to be used within each range. Each colour in the colormap represents a specific range of data values. In this case, colours within the colors array are assigned to distinct data ranges, ensuring clear differentiation between the ranges.

Here is an example of a discrete colormap defined in JSON:

{
  "name": "Example Discrete Colormap",
  "colors": [
    [255, 0, 0],
    [0, 255, 0],
    [0, 0, 255]
  ],
  "end_points": [0.33, 0.66],
  "end_inclusive": [true, false],
  "dtype": "discrete"
}

In this example, the colormap has three colours (red, green, and blue) and two endpoints (0.33 and 0.66). The first endpoint is inclusive, meaning values equal to 0.33 are coloured red. Values greater than 0.33 and less than or equal to 0.66 are coloured green. Values greater than 0.66 are coloured blue.

Color	Inequality	Interval Notation	Interval Description
Red	-∞ < x ≤ 0.33	(-∞, 0.33]	From negative infinity to 0.33 (inclusive)
Green	0.33 < x < 0.66	(0.33, 0.66)	From 0.33 (exclusive) to 0.66 (exclusive)
Blue	0.66 ≤ x < ∞	[0.66, ∞)	From 0.66 (inclusive) to positive infinity

In a discrete colormap, specific ranges of data values are assigned specific colours (e.g., Red for values ≤ 0.33, Green for values > 0.33 and ≤ 0.66, Blue for values > 0.66), as defined by the endpoints and colours in the colors array.

Note: Discrete colormaps can have up to 1024 colors. The end_points and end_inclusive arrays must each have a size of one less than the number of colors in the colors array.

Category

A category colormap is used for non-numerical data. These require a mapping between categories and colours. Each category in a category colormap is assigned a specific colour.

Here is an example of a category colormap defined in JSON:

{
    "name": "Example Category Colormap",
    "colors": [
        [255, 0, 0],
        [0, 255, 0],
        [0, 0, 255]
    ],
    "map": ["Cat1", "Cat2", "Cat3"],
    "dtype": "category"
}

In this example, the category colormap has a list colors which holds colours and a corresponding list of categories (map). Each category in the map is assigned a specific colour from the colors list.

Cat1	Cat2	Cat3
Red	Green	Blue

In a category colormap, each category (e.g., Cat1, Cat2, Cat3) is assigned a specific colour (e.g., Red, Green, Blue). This type of colour mapping allows for clear visual differentiation between categories, making it easier to interpret non-numerical data.

Note: Category colormaps can have up to 16,384 colors. The number of colors must match the number of categories in the map field exactly, as they are mapped in a one-to-one fashion.

Colormap associations

Associations in the Evo platform allow you to link a colormap with geoscience object attributes.

Associations are defined by providing an attribute_id and a colormap_id. This linkage ensures that there is a defined relationship between the attribute and the colormap, which can be utilized by other components of the platform.

Here is an example of an association:

{
    "attribute_id": "00000000-0000-0000-0000-000000000000",
    "colormap_id": "ffffffff-ffff-ffff-ffff-ffffffffffff"
}

Note: The same colormap can be associated with many geoscience object attributes, promoting reuse and ensuring consistent color representation across different geoscience objects. By using a common colormap you can maintain a standardized visual language, making it easier to compare, interpret, and communicate the data.