@@ -45,7 +45,7 @@ the underlying dynamics and must be tested against known reference data to ensur
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accuracy.
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` blobmodel ` addresses this need by providing a framework for generating synthetic
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- datasets resulting from a superposition of uncorrelated pulses [ @militello_two-dimensional_2018, @losada_tde_2025] :
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+ datasets resulting from a superposition of uncorrelated pulses [ @militello_two-dimensional_2018; @losada_tde_2025] :
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$$
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\Phi(x,y,t) = \sum_{k=1}^{K} a_k \varphi\left( \frac{x-v_k(t-t_k)}{\ell_{x, k}}, \frac{(y-y_k)-w_k(t-t_k)}{\ell_{y, k}}\right) ,
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$$
@@ -55,14 +55,13 @@ Additionally, each pulse may be tilted an angle given by an additional random va
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$\theta_k$ with respect to its centre.
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The framework allows an explicit definition of all relevant process parameters, including:
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- * All pulse parameters if defined as degenerate random variables.
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- * All distribution functions of the pulse parameters otherwise.
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- * Optionally, a drainage term $\tau_ \shortparallel$ that models an exponential decay in the pulse amplitude.
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- * Spatial and temporal resolution.
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- * Degree of pulse overlap.
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- * Signal length.
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- For more details visit [ blobmodel's documentation] ( https://blobmodel.readthedocs.io/en/latest/ )
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+ - All pulse parameters if defined as degenerate random variables.
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+ - All distribution functions of the pulse parameters otherwise.
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+ - Optionally, a drainage term $\tau_ \shortparallel$ that models an exponential decay in the pulse amplitude.
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+ - Spatial and temporal resolution.
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+ - Degree of pulse overlap.
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+ - Signal length.
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This allows researchers to systematically test and benchmark
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tracking algorithms and velocity estimation techniques in a controlled setting.
@@ -72,6 +71,8 @@ formation of moving structures in one or two-dimensional space. By offering an o
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and easily accessible tool, blobmodel supports the development and validation of
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analysis methods used in experimental and computational research.
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+ For more details visit [ blobmodel's documentation] ( https://blobmodel.readthedocs.io/en/latest/ ) .
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+
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The package has been used to generate synthetic data to study and compare the robustness of
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velocity estimation techniques on coarse-grained imaging data [ @losada_three-point_2024] .
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