Note

Click here to download the full example code

Examples in 2D

This section contains several examples on how to generate 2D data with pyclugen. To run the examples we first need to import the clugen() function:

import numpy as np
from pyclugen import clugen

To plot these examples we use the plot_examples_2d function:

from plot_functions import plot_examples_2d

Manipulating the direction of cluster-supporting lines

Using the direction parameter

seed = 123

e001 = clugen(2, 4, 2000, [1, 0], 0, [10, 10], 10, 1.5, 0.5, rng=seed)
e002 = clugen(2, 4, 200, [1, 1], 0, [10, 10], 10, 1.5, 0.5, rng=seed)
e003 = clugen(2, 4, 200, [0, 1], 0, [10, 10], 10, 1.5, 0.5, rng=seed)

plot_examples_2d(
    e001, "e001: direction = [1, 0]",
    e002, "e002: direction = [1, 1]",
    e003, "e003: direction = [0, 1]")

Changing the angle_disp parameter and using a custom angle_deltas_fn function

seed = 321

# Custom angle_deltas function: arbitrarily rotate some clusters by 90 degrees
def angdel_90_fn(nclu, astd, rng):
    return rng.choice([0, np.pi / 2], size=nclu)

e004 = clugen(2, 6, 500, [1, 0], 0, [10, 10], 10, 1.5, 0.5, rng=seed)
e005 = clugen(2, 6, 500, [1, 0], np.pi / 8, [10, 10], 10, 1.5, 0.5, rng=seed)
e006 = clugen(2, 6, 500, [1, 0], 0, [10, 10], 10, 1.5, 0.5, rng=seed,
    angle_deltas_fn=angdel_90_fn)

plot_examples_2d(
    e004, "e004: angle_disp = 0",
    e005, "e005: angle_disp = π/8",
    e006, "e006: custom angle_deltas function")

Manipulating the length of cluster-supporting lines

Using the llength parameter

seed = 567

e007 = clugen(2, 5, 800, [1, 0], np.pi / 10, [10, 10],  0, 0, 0.5, rng=seed,
    point_dist_fn="n")
e008 = clugen(2, 5, 800, [1, 0], np.pi / 10, [10, 10], 10, 0, 0.5, rng=seed,
    point_dist_fn="n")
e009 = clugen(2, 5, 800, [1, 0], np.pi / 10, [10, 10], 30, 0, 0.5, rng=seed,
    point_dist_fn="n")

plot_examples_2d(
    e007, "e007: llength = 0",
    e008, "e008: llength = 10",
    e009, "e009: llength = 30")

Changing the llength_disp parameter and using a custom llengths_fn function

seed = 567

# Custom llengths function: line lengths grow for each new cluster
def llen_grow_fn(nclu, llen, llenstd, rng):
    return llen * np.arange(nclu) + rng.normal(scale=llenstd, size=nclu)

e010 = clugen(2, 5, 800, [1, 0], np.pi / 10, [10, 10], 15,  0.0, 0.5, rng=seed,
    point_dist_fn="n")
e011 = clugen(2, 5, 800, [1, 0], np.pi / 10, [10, 10], 15, 10.0, 0.5, rng=seed,
    point_dist_fn="n")
e012 = clugen(2, 5, 800, [1, 0], np.pi / 10, [10, 10], 10,  0.1, 0.5, rng=seed,
    llengths_fn=llen_grow_fn, point_dist_fn="n")

plot_examples_2d(
    e010, "e010: llength_disp = 0.0",
    e011, "e011: llength_disp = 5.0",
    e012, "e012: custom llengths function")

Manipulating relative cluster positions

Using the cluster_sep parameter

seed = 21

e013 = clugen(2, 8, 1000, [1, 1], np.pi / 4, [10, 10], 10, 2, 2.5, rng=seed)
e014 = clugen(2, 8, 1000, [1, 1], np.pi / 4, [30, 10], 10, 2, 2.5, rng=seed)
e015 = clugen(2, 8, 1000, [1, 1], np.pi / 4, [10, 30], 10, 2, 2.5, rng=seed)

plt = plot_examples_2d(
    e013, "e013: cluster_sep = [10, 10]",
    e014, "e014: cluster_sep = [30, 10]",
    e015, "e015: cluster_sep = [10, 30]")

Changing the cluster_offset parameter and using a custom clucenters_fn function

seed = 21

# Custom clucenters function: places clusters in a diagonal
def centers_diag_fn(nclu, csep, coff, rng):
    return np.ones((nclu, len(csep))) * np.arange(1, nclu + 1)[:, None] * np.max(csep) + coff

e016 = clugen(2, 8, 1000, [1, 1], np.pi / 4, [10, 10], 10, 2, 2.5, rng=seed)
e017 = clugen(2, 8, 1000, [1, 1], np.pi / 4, [10, 10], 10, 2, 2.5, rng=seed,
    cluster_offset=[20, -20])
e018 = clugen(2, 8, 1000, [1, 1], np.pi / 4, [10, 10], 10, 2, 2.5, rng=seed,
    cluster_offset=[-50, -50], clucenters_fn=centers_diag_fn)

plt = plot_examples_2d(
    e016, "e016: default",
    e017, "e017: cluster_offset = [20, -20]",
    e018, "e018: custom clucenters function")

Lateral dispersion and placement of point projections on the line

Normal projection placement (default): proj_dist_fn = "norm"

seed = 654

e019 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 0.0, rng=seed)
e020 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 1.0, rng=seed)
e021 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 3.0, rng=seed)

plt = plot_examples_2d(
    e019, "e019: lateral_disp = 0",
    e020, "e020: lateral_disp = 1",
    e021, "e021: lateral_disp = 3")

Uniform projection placement: proj_dist_fn = "unif"

seed = 654

e022 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 0.0, rng=seed,
    proj_dist_fn="unif")
e023 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 1.0, rng=seed,
    proj_dist_fn="unif")
e024 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 3.0, rng=seed,
    proj_dist_fn="unif")

plt = plot_examples_2d(
    e022, "e022: lateral_disp = 0",
    e023, "e023: lateral_disp = 1",
    e024, "e024: lateral_disp = 3")

Custom projection placement using the Laplace distribution

# Custom proj_dist_fn: point projections placed using the Laplace distribution
def proj_laplace(len, n, rng):
    return rng.laplace(scale=len / 6, size=n)

e025 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 0.0, rng=seed,
    proj_dist_fn=proj_laplace)
e026 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 1.0, rng=seed,
    proj_dist_fn=proj_laplace)
e027 = clugen(2, 4, 1000, [1, 0], np.pi / 2, [20, 20], 13, 2, 3.0, rng=seed,
    proj_dist_fn=proj_laplace)

plt = plot_examples_2d(
    e025, "e025: lateral_disp = 0",
    e026, "e026: lateral_disp = 1",
    e027, "e027: lateral_disp = 3")

Controlling final point positions from their projections on the cluster-supporting line

Points on hyperplane orthogonal to cluster-supporting line (default): point_dist_fn = "n-1"

seed = 1357

# Custom proj_dist_fn: point projections placed using the Laplace distribution
def proj_laplace(len, n, rng):
    return rng.laplace(scale=len / 6, size=n)

e028 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed)
e029 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    proj_dist_fn="unif")
e030 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    proj_dist_fn=proj_laplace)

plt = plot_examples_2d(
    e028, "e028: proj_dist_fn=\"norm\" (default)",
    e029, "e029: proj_dist_fn=\"unif\"",
    e030, "e030: custom proj_dist_fn (Laplace)")

Points around projection on cluster-supporting line: point_dist_fn = "n"

seed = 1357

# Custom proj_dist_fn: point projections placed using the Laplace distribution
def proj_laplace(len, n, rng):
    return rng.laplace(scale=len / 6, size=n)

e031 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    point_dist_fn="n")
e032 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    point_dist_fn="n", proj_dist_fn="unif")
e033 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    point_dist_fn="n", proj_dist_fn=proj_laplace)

plt = plot_examples_2d(
    e031, "e031: proj_dist_fn=\"norm\" (default)",
    e032, "e032: proj_dist_fn=\"unif\"",
    e033, "e033: custom proj_dist_fn (Laplace)")

Custom point placement using the exponential distribution

For this example we require the clupoints_n_1_template() helper function:

from pyclugen import clupoints_n_1_template

seed = 1357

# Custom point_dist_fn: final points placed using the Exponential distribution
def clupoints_n_1_exp(projs, lat_std, len, clu_dir, clu_ctr, rng):
    def dist_exp(npts, lstd, rg):
        return lstd * rg.exponential(scale=2 / lstd, size=npts)
    return clupoints_n_1_template(projs, lat_std, clu_dir, dist_exp, rng=rng)

# Custom proj_dist_fn: point projections placed using the Laplace distribution
def proj_laplace(len, n, rng):
    return rng.laplace(scale=len / 6, size=n)

e034 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    point_dist_fn=clupoints_n_1_exp)
e035 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    point_dist_fn=clupoints_n_1_exp, proj_dist_fn="unif")
e036 = clugen(2, 5, 1500, [1, 0], np.pi / 3, [20, 20], 12, 3, 1.0, rng=seed,
    point_dist_fn=clupoints_n_1_exp, proj_dist_fn=proj_laplace)

plt = plot_examples_2d(
    e034, "e034: proj_dist_fn=\"norm\" (default)",
    e035, "e035: proj_dist_fn=\"unif\"",
    e036, "e036: custom proj_dist_fn (Laplace)")

Manipulating cluster sizes

seed = 963

# Custom clusizes_fn (e038): cluster sizes determined via the uniform distribution,
# no correction for total points
def clusizes_unif(nclu, npts, ae, rng):
    return rng.integers(low=1, high=2 * npts / nclu + 1, size=nclu)

# Custom clusizes_fn (e039): clusters all have the same size, no correction for total points
def clusizes_equal(nclu, npts, ae, rng):
    return (npts // nclu) * np.ones(nclu, dtype=int)

# Custom clucenters_fn (all): yields fixed positions for the clusters
def centers_fixed(nclu, csep, coff, rng):
    return np.array([[-csep[0], -csep[1]], [csep[0], -csep[1]], [-csep[0], csep[1]], [csep[0], csep[1]]])

e037 = clugen(2, 4, 1500, [1, 1], np.pi, [20, 20], 0, 0, 5, rng=seed,
    point_dist_fn="n", clucenters_fn=centers_fixed)
e038 = clugen(2, 4, 1500, [1, 1], np.pi, [20, 20], 0, 0, 5, rng=seed,
    point_dist_fn="n", clucenters_fn=centers_fixed, clusizes_fn=clusizes_unif)
e039 = clugen(2, 4, 1500, [1, 1], np.pi, [20, 20], 0, 0, 5, rng=seed,
    point_dist_fn="n", clucenters_fn=centers_fixed, clusizes_fn=clusizes_equal)

plt = plot_examples_2d(
    e037, "e037: normal dist. (default)",
    e038, "e038: unif. dist. (custom)",
    e039, "e039: equal size (custom)")

Direct specification of optional parameters

seed = 123

e040 = clugen(2, 4, 1000, [-1, 1], 0, [0, 0], 0, 0, 0.2, rng=seed,
    proj_dist_fn="unif", point_dist_fn="n", clusizes_fn=[50, 200, 500, 2000],
    llengths_fn=[0, 2, 4, 6], clucenters_fn=[[-5, -5], [-2.5, -2.5], [0, 0], [2.5, 2.5]])

e041 = clugen(2, 5, 1000, [[1, 1], [1, 0], [1, 0], [0, 1], [0, 1]],
    0, [0, 0], 0, 0, 0.2, rng=seed,
    proj_dist_fn="unif", point_dist_fn="n",
    clusizes_fn=[200, 500, 500, 500, 500], llengths_fn=[0, 5, 5, 5, 5],
    clucenters_fn=[[0, 0], [0, 5], [0, -5], [5, 0], [-5, 0]])

e042 = clugen(2, 5, 1000, [[0, 1], [0.25, 0.75], [0.5, 0.5], [0.75, 0.25], [1, 0]],
    0, [0, 0], 5, 0, 0.2, rng=seed,
    proj_dist_fn="unif", point_dist_fn="n", clusizes_fn=[500, 500, 500, 500, 500],
    clucenters_fn=[[-5, 0], [-3, -0.3], [-1, -0.8], [1, -1.6], [3, -2.5]])

plt = plot_examples_2d(
    e040, "e040: direct params 1",
    e041, "e041: direct params 2",
    e042, "e042: direct params 3")

Total running time of the script: ( 0 minutes 11.459 seconds)

Download Python source code: plot_2_2d_examples.py

Download Jupyter notebook: plot_2_2d_examples.ipynb

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