Add infinity and figure eight target shapes #190
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #190 +/- ##
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+ Coverage 98.42% 98.44% +0.01%
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Files 43 43
Lines 1775 1795 +20
Branches 358 356 -2
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+ Hits 1747 1767 +20
Misses 25 25
Partials 3 3
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stefmolin
changed the title
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Thanks for the PR, @MauriceDeVr! We are off to a good start.
| def __str__(self) -> str: | ||
| return 'infinity' | ||
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We only need this if the name is different than the lowercased class name.
| def __str__(self) -> str: | |
| return 'infinity' |
data-morph/src/data_morph/shapes/bases/shape.py
Lines 25 to 34 in b6bebc9
| # print(shape.points[67]) | ||
| print(shape.distance(*test_point)) |
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| # print(shape.points[67]) | |
| print(shape.distance(*test_point)) |
| Notes | ||
| ----- | ||
| The formula for the infinity shape is directly taken from Lemniscate of | ||
| Bernoulli equation. |
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This feels more like a see also section. Something like this, but figure out a good description:
| Notes | |
| ----- | |
| The formula for the infinity shape is directly taken from Lemniscate of | |
| Bernoulli equation. | |
| See Also | |
| -------- | |
| _LemniscateBernoulli : Write a description here |
| Notes | ||
| ----- | ||
| Implements the Lemniscate of Bernoulli Equation with a transform | ||
| to draw a figure eight shape. | ||
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| See Base class for implementation specifice details. |
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Let's do a see also section here as well, but also link to the Infinity class.
| super().__init__( | ||
| *np.stack( | ||
| [ | ||
| transformed_x * scale_factor + x_shift, | ||
| transformed_y * scale_factor + y_shift, | ||
| ], | ||
| axis=1, | ||
| ) | ||
| ) |
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The shapes both have a gap. Let's make it a closed shape:
| x_shift = sum(x_bounds) / 2 | ||
| y_shift = sum(y_bounds) / 2 | ||
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| t = np.linspace(-3, 3, num=2000) |
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Using 2,000 points is a lot, the algorithm needs to calculate the distance to each point. Can we reduce this? For example, the heart only uses 80.
| @@ -131,6 +132,150 @@ def __init__(self, dataset: Dataset) -> None: | |||
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| class _LemniscateBernoulli(PointCollection): | |||
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Let's merge this with the Infinity class (calling it Infinity). The docs have a broken link with this because they ignore anything prefixed with _, and this class has all the functionality of the Infinity class already.
| x = (np.sqrt(2) * np.cos(t)) / (1 + np.square(np.sin(t))) | ||
| y = (np.sqrt(2) * np.cos(t) * np.sin(t)) / (1 + np.square(np.sin(t))) | ||
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| scale_factor = (x_bounds[1] - x_shift) * 0.75 |
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Why not use the y information here? Maybe pick one using the data? With the sheep for example, it seems like the figure eight is being drawn too tall, so we should probably take the minimum of the x and y scale factors and use that.
Try plotting a dataset and the shape on top of each other and see how that looks.
Fixes: #179
Fixes: #178
Changes