Doubled barbell

%matplotlib inline

# Not really required
import sys
sys.path.insert(0, '../../..')

from pyLDLE2 import datasets
from pyLDLE2 import buml_, util_

matplotlib.get_backend() =  module://matplotlib_inline.backend_inline

save_dir_root = '../data/pyLDLE2/doubled_barbell/'

X, labelsMat, ddX = datasets.Datasets().barbell()

X.shape =  (10227, 2)

# The supplied options would override the default options
buml_obj = buml_.BUML(local_opts={'algo':'LDLE', 'N': 200, 'tau': 90},
                      intermed_opts={'eta_min':5, 'algo':'best'},
                      vis_opts={'c': labelsMat[:,0], 'save_dir': save_dir_root},
                      verbose=True, debug=True)

local_opts['k_nn0'] = 700 is created.
Options provided:
local_opts:
{
    "Atilde_method": "LDLE_1",
    "N": 200,
    "U_method": "k_nn",
    "algo": "LDLE",
    "alpha": 1,
    "debug": true,
    "delta": 0.9,
    "gl_type": "unnorm",
    "k": 28,
    "k_nn": 49,
    "k_nn0": 700,
    "k_tune": 7,
    "lambda1_decay": 0.75,
    "lambda1_init": 8,
    "lambda1_min": 0.001,
    "max_iter": 300,
    "max_sparsity": 0.9,
    "metric": "euclidean",
    "n_proc": 32,
    "p": 0.99,
    "power": 5,
    "pp_n_thresh": 32,
    "radius": 0.5,
    "reg": 0.0,
    "scale_by": "gamma",
    "tau": 90,
    "to_postprocess": true,
    "verbose": true
}
intermed_opts:
{
    "algo": "best",
    "debug": true,
    "eta_max": 25,
    "eta_min": 5,
    "len_S_thresh": 256,
    "local_algo": "LDLE",
    "metric": "euclidean",
    "n_proc": 32,
    "n_times": 4,
    "verbose": true
}
global_opts:
{
    "add_dim": false,
    "align_transform": "rigid",
    "align_w_parent_only": true,
    "alpha": 0.3,
    "beta": {
        "align": null,
        "repel": 1
    },
    "color_tear": true,
    "compute_error": false,
    "debug": true,
    "eps": 1e-08,
    "err_tol": 0.0001,
    "far_off_points_type": "reuse_fixed",
    "init_algo_name": "procrustes",
    "k": 28,
    "max_internal_iter": 100,
    "max_iter": 20,
    "metric": "euclidean",
    "n_proc": 32,
    "n_repel": 0,
    "nu": 3,
    "patience": 5,
    "refine_algo_name": "rgd",
    "repel_by": 0.0,
    "to_tear": true,
    "verbose": true,
    "vis_before_init": false
}

buml_obj.fit(X=X, ddX=ddX)

Doubling manifold.
No. of points on the boundary = 764

/home/dhruv/anaconda3/lib/python3.9/site-packages/sklearn/neighbors/_base.py:234: EfficiencyWarning: Precomputed sparse input was not sorted by row values. Use the function sklearn.neighbors.sort_graph_by_row_values to sort the input by row values, with warn_when_not_sorted=False to remove this warning.
  warnings.warn(

Done.
##############################
Time elapsed from last time log: 41.5 seconds
Total time elapsed: 41.5 seconds
##############################
Computing local views using LDLE
Constructing unnorm graph Laplacian + its eigendecomposition.
Done.
##############################
Time elapsed from last time log: 40.0 seconds
Total time elapsed: 40.0 seconds
##############################
Computing Atilde: Inner Prod of Grad of EigFuncs.
FEM for Atilde.
Atilde: 0 points processed...
Atilde: 4922 points processed...
Atilde: 9844 points processed...
Atilde: 14766 points processed...
Atilde: 19688 points processed...
Atilde: all points processed...
Done.
##############################
Time elapsed from last time log: 27.8 seconds
Total time elapsed: 67.8 seconds
##############################
Computing LDLE.
local_param: all 19690 points processed...
max distortion is 113.043904
Done.
##############################
Time elapsed from last time log: 5.2 seconds
Total time elapsed: 73.4 seconds
##############################
Posprocessing local parameterizations.
#Param replaced: 16656, max distortion: 14.282789
#Param replaced: 3335, max distortion: 14.102668
#Param replaced: 180, max distortion: 14.102668
#Param replaced: 10, max distortion: 14.102668
#Param replaced: 1, max distortion: 14.102668
#Param replaced: 0, max distortion: 14.102668
Max local distortion after postprocessing: 14.102668125100376
Done.
##############################
Time elapsed from last time log: 12.8 seconds
Total time elapsed: 86.2 seconds
##############################
Halving objects.
Done.
##############################
Time elapsed from last time log: 10.1 seconds
Total time elapsed: 101.4 seconds
##############################
Max local distortion = 12.482168183225866
Constructing intermediate views.
eta = 2.
#non-empty views with sz < 2 = 10227
#nodes in views with sz < 2 = 10227

/home/dhruv/codebase/pyLDLE2/docs/ldle_nbks/doubled_manifolds/../../../pyLDLE2/intermed_views_.py:122: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
  neigh_ind = np.array(neigh_ind)

Costs computed when eta = 2.
##############################
Time elapsed from last time log: 9.7 seconds
Total time elapsed: 10.5 seconds
##############################
ctr=7712, total_len_S=45601, avg_len_S=5.913
Remaining #nodes in views with sz < 2 = 0
Done with eta = 2.
##############################
Time elapsed from last time log: 179.6 seconds
Total time elapsed: 190.1 seconds
##############################
eta = 3.
#non-empty views with sz < 3 = 737
#nodes in views with sz < 3 = 1474
Costs computed when eta = 3.
##############################
Time elapsed from last time log: 5.7 seconds
Total time elapsed: 195.8 seconds
##############################
ctr=1226, total_len_S=21523, avg_len_S=17.555
Remaining #nodes in views with sz < 3 = 0
Done with eta = 3.
##############################
Time elapsed from last time log: 19.5 seconds
Total time elapsed: 215.4 seconds
##############################
eta = 4.
#non-empty views with sz < 4 = 459
#nodes in views with sz < 4 = 1377
Costs computed when eta = 4.
##############################
Time elapsed from last time log: 5.5 seconds
Total time elapsed: 220.9 seconds
##############################
ctr=1181, total_len_S=29976, avg_len_S=25.382
Remaining #nodes in views with sz < 4 = 0
Done with eta = 4.
##############################
Time elapsed from last time log: 25.9 seconds
Total time elapsed: 246.7 seconds
##############################
eta = 5.
#non-empty views with sz < 5 = 295
#nodes in views with sz < 5 = 1180
Costs computed when eta = 5.
##############################
Time elapsed from last time log: 7.5 seconds
Total time elapsed: 254.3 seconds
##############################
ctr=1031, total_len_S=32074, avg_len_S=31.110
Remaining #nodes in views with sz < 5 = 0
Done with eta = 5.
##############################
Time elapsed from last time log: 34.5 seconds
Total time elapsed: 288.8 seconds
##############################
Pruning and cleaning up.
Done.
##############################
Time elapsed from last time log: 1.7 seconds
Total time elapsed: 290.5 seconds
##############################
After clustering, max distortion is 15.704694
Using rigid transforms for alignment.
Computing laterations scores for overlaps b/w intermed views
Done
##############################
Time elapsed from last time log: 7.1 seconds
Total time elapsed: 7.1 seconds
##############################
Computing a lateration.
Seq of intermediate views and their predecessors computed.
No. of connected components = 1
Done.
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 7.1 seconds
##############################
Computing initial embedding using: procrustes algorithm
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 7.1 seconds
##############################
Initial alignment of 316 views completed
Initial alignment of 632 views completed
Initial alignment of 948 views completed
Initial alignment of 1264 views completed
Embedding initialized.
##############################
Time elapsed from last time log: 1.9 seconds
Total time elapsed: 9.0 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 0
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 16.9 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 15.5 seconds
Total time elapsed: 32.4 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 1
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 36.6 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 14.2 seconds
Total time elapsed: 50.8 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 2
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 53.4 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 14.7 seconds
Total time elapsed: 68.1 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 3
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 69.6 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 13.6 seconds
Total time elapsed: 83.1 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 4
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 84.9 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 13.5 seconds
Total time elapsed: 98.4 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 5
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 99.9 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 15.6 seconds
Total time elapsed: 115.5 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 6
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 117.1 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 13.3 seconds
Total time elapsed: 130.4 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 7
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 132.5 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 13.2 seconds
Total time elapsed: 145.7 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 8
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 147.2 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 16.7 seconds
Total time elapsed: 163.9 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 9
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 165.5 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 12.7 seconds
Total time elapsed: 178.3 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 10
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 179.7 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 13.1 seconds
Total time elapsed: 192.8 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 11
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 194.3 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 15.3 seconds
Total time elapsed: 209.7 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 12
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 211.9 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 13.1 seconds
Total time elapsed: 225.0 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 13
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 226.3 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 13.5 seconds
Total time elapsed: 239.9 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 14
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 241.2 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 11.5 seconds
Total time elapsed: 252.7 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 15
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 254.1 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 11.6 seconds
Total time elapsed: 265.7 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 16
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 266.9 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 11.3 seconds
Total time elapsed: 278.1 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 17
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 279.5 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 11.1 seconds
Total time elapsed: 290.5 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 18
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 292.0 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 11.5 seconds
Total time elapsed: 303.5 seconds
##############################

Refining with rgd algorithm for 100 iterations.
Refinement iteration: 19
##############################
Time elapsed from last time log: 0.0 seconds
Total time elapsed: 304.7 seconds
##############################
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Descent starts
Done.
##############################
Time elapsed from last time log: 11.2 seconds
Total time elapsed: 315.9 seconds
##############################
Computing error.
min and max weights: 1.0 1.0
Computing Pseudoinverse of a matrix of L of size 10227 + 1266 multiplied with B
Computing svd
Done
Alignment error: 1.130367
##############################
Time elapsed from last time log: 4.5 seconds
Total time elapsed: 320.5 seconds
##############################

array([[-0.20815434, -1.38056597],
       [-0.19768424, -1.38399708],
       [-0.19105738, -1.38372242],
       ...,
       [ 0.08417931,  0.70909419],
       [ 0.09127498,  0.70620604],
       [ 0.09849001,  0.70241038]])

buml_obj.GlobalViews.vis_embedding(buml_obj.GlobalViews.y_final, buml_obj.vis, buml_obj.vis_opts,
                                   buml_obj.GlobalViews.color_of_pts_on_tear_final,
                                   title='Final global embedding', )

util_.save(save_dir_root, 'ldle.dat', [X, labelsMat, buml_obj])