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Revise README with mermaid flowcharts #762

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@ndem0 ndem0 commented Jan 7, 2026 •
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Updated the README to reflect PINA modules structure and added flowcharts for steps to follow.

Description

This PR replaces the static PNG diagram in the README with an equivalent Mermaid (link) diagram.

The goal is to make the architecture diagram easier to maintain and update over time, avoiding the need to regenerate image assets for small documentation changes. The new Mermaid diagram mirrors the original structure and module hierarchy and is fully compatible with GitHub rendering.

Checklist

  • Code follows the project’s Code Style Guidelines
  • Tests have been added or updated
  • Documentation has been updated if necessary
  • Pull request is linked to an open issue

@ndem0
Revise README with mermaid flowcharts
bd885b4 
Updated the README to reflect PINA modules structure and added flowcharts for steps to follow.
@ndem0 ndem0 requested a review from a team as a code owner January 7, 2026 09:53
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github-actions bot commented Jan 7, 2026 •
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Code Coverage Summary

Filename                                                                  Stmts    Miss  Cover    Missing
----------------------------------------------------------------------  -------  ------  -------  ----------------------------------------------------------------------------------------------
__init__.py                                                                   7       0  100.00%
graph.py                                                                    114      11  90.35%   99-100, 112, 124, 126, 142, 144, 166, 169, 182, 271
label_tensor.py                                                             251      24  90.44%   81, 121, 148, 165, 177, 182, 188-193, 273, 280, 332, 348, 444-447, 490, 537, 629, 664-673, 710
operator.py                                                                  72       2  97.22%   269, 465
trainer.py                                                                   86       5  94.19%   210-219, 308, 329, 333
type_checker.py                                                              22       0  100.00%
utils.py                                                                     73       7  90.41%   59, 75, 141, 178, 181, 184, 268
adaptive_function/__init__.py                                                 3       0  100.00%
adaptive_function/adaptive_function.py                                       55       0  100.00%
adaptive_function/adaptive_function_interface.py                             51       6  88.24%   98, 141, 148-151
callback/__init__.py                                                          7       0  100.00%
callback/optim/switch_optimizer.py                                           23       0  100.00%
callback/optim/switch_scheduler.py                                           21       0  100.00%
callback/processing/metric_tracker.py                                        24       3  87.50%   37-38, 68
callback/processing/normalizer_data_callback.py                              68       1  98.53%   141
callback/processing/pina_progress_bar.py                                     26       2  92.31%   90, 93
callback/refinement/__init__.py                                               3       0  100.00%
callback/refinement/r3_refinement.py                                         26       1  96.15%   102
callback/refinement/refinement_interface.py                                  50       5  90.00%   32, 59, 67, 72, 78
condition/__init__.py                                                         7       0  100.00%
condition/condition.py                                                       19       1  94.74%   141
condition/condition_interface.py                                             37       4  89.19%   32, 76, 95, 125
condition/data_condition.py                                                  26       1  96.15%   78
condition/domain_equation_condition.py                                       19       0  100.00%
condition/input_equation_condition.py                                        43       1  97.67%   157
condition/input_target_condition.py                                          44       1  97.73%   172
data/__init__.py                                                              3       0  100.00%
data/data_module.py                                                         201      22  89.05%   41-52, 132, 172, 193, 232, 313-317, 323-327, 399, 466, 547, 638, 640
data/dataset.py                                                              82       7  91.46%   42, 123-126, 256, 293
domain/__init__.py                                                           11       0  100.00%
domain/base_domain.py                                                        64       0  100.00%
domain/base_operation.py                                                     45       4  91.11%   63, 106, 129, 139
domain/cartesian_domain.py                                                   54       1  98.15%   68
domain/difference.py                                                         27       0  100.00%
domain/domain_interface.py                                                   25       0  100.00%
domain/ellipsoid_domain.py                                                   81       4  95.06%   98, 108-109, 253
domain/exclusion.py                                                          35       1  97.14%   107
domain/intersection.py                                                       34       1  97.06%   97
domain/operation_interface.py                                                 9       0  100.00%
domain/simplex_domain.py                                                     83       5  93.98%   212, 226, 237, 249, 288
domain/union.py                                                              24       0  100.00%
equation/__init__.py                                                          4       0  100.00%
equation/equation.py                                                         16       1  93.75%   59
equation/equation_factory.py                                                112       1  99.11%   178
equation/equation_interface.py                                               14       1  92.86%   51
equation/system_equation.py                                                  21       0  100.00%
loss/__init__.py                                                              9       0  100.00%
loss/linear_weighting.py                                                     14       0  100.00%
loss/loss_interface.py                                                       17       2  88.24%   45, 51
loss/lp_loss.py                                                              15       0  100.00%
loss/ntk_weighting.py                                                        18       0  100.00%
loss/power_loss.py                                                           15       0  100.00%
loss/scalar_weighting.py                                                     16       0  100.00%
loss/self_adaptive_weighting.py                                              12       0  100.00%
loss/weighting_interface.py                                                  29       3  89.66%   35, 41-42
model/__init__.py                                                            14       0  100.00%
model/average_neural_operator.py                                             31       2  93.55%   73, 82
model/deeponet.py                                                            85      13  84.71%   179-182, 201, 232, 271, 281, 291, 301, 311, 321, 476, 486
model/equivariant_graph_neural_operator.py                                   51       1  98.04%   217
model/feed_forward.py                                                        89      11  87.64%   58, 195, 200, 278-292
model/fourier_neural_operator.py                                             78      10  87.18%   96-100, 110, 155-159, 218, 220, 242, 342
model/graph_neural_operator.py                                               40       2  95.00%   58, 60
model/kernel_neural_operator.py                                              34       6  82.35%   83-84, 103-104, 123-124
model/low_rank_neural_operator.py                                            27       2  92.59%   89, 98
model/multi_feed_forward.py                                                  12       5  58.33%   25-31
model/pirate_network.py                                                      27       1  96.30%   118
model/sindy.py                                                               21       0  100.00%
model/spline.py                                                             124       6  95.16%   133, 156, 164, 236, 450, 475
model/spline_surface.py                                                      68      12  82.35%   151-152, 187-190, 200, 213-218, 258
model/block/__init__.py                                                      13       0  100.00%
model/block/average_neural_operator_block.py                                 12       0  100.00%
model/block/convolution.py                                                   64      13  79.69%   77, 81, 85, 91, 97, 111, 114, 151, 161, 171, 181, 191, 201
model/block/convolution_2d.py                                               146      27  81.51%   155, 162, 282, 314, 379-433, 456
model/block/embedding.py                                                     48       7  85.42%   93, 143-146, 155, 168
model/block/fourier_block.py                                                 31       0  100.00%
model/block/gno_block.py                                                     22       4  81.82%   73-77, 87
model/block/integral.py                                                      18       4  77.78%   22-25, 71
model/block/low_rank_block.py                                                24       0  100.00%
model/block/orthogonal.py                                                    37       0  100.00%
model/block/pirate_network_block.py                                          25       1  96.00%   89
model/block/pod_block.py                                                     75      10  86.67%   56-59, 71, 84, 114, 151-156, 191, 216
model/block/rbf_block.py                                                    179      25  86.03%   18, 42, 53, 64, 75, 86, 97, 223, 280, 282, 298, 301, 329, 335, 363, 367, 511-524
model/block/residual.py                                                      46       0  100.00%
model/block/spectral.py                                                      83       4  95.18%   132, 140, 262, 270
model/block/stride.py                                                        28       7  75.00%   55, 58, 61, 67, 72-74
model/block/utils_convolution.py                                             22       3  86.36%   58-60
model/block/message_passing/__init__.py                                       6       0  100.00%
model/block/message_passing/deep_tensor_network_block.py                     21       0  100.00%
model/block/message_passing/en_equivariant_network_block.py                  47       1  97.87%   164
model/block/message_passing/equivariant_graph_neural_operator_block.py       36       0  100.00%
model/block/message_passing/interaction_network_block.py                     23       0  100.00%
model/block/message_passing/radial_field_network_block.py                    20       0  100.00%
optim/__init__.py                                                             5       0  100.00%
optim/optimizer_interface.py                                                  7       0  100.00%
optim/scheduler_interface.py                                                  7       0  100.00%
optim/torch_optimizer.py                                                     14       0  100.00%
optim/torch_scheduler.py                                                     19       2  89.47%   5-6
problem/__init__.py                                                           6       0  100.00%
problem/abstract_problem.py                                                 117      12  89.74%   39-40, 59-70, 149, 161, 179, 253, 257, 286
problem/inverse_problem.py                                                   22       0  100.00%
problem/parametric_problem.py                                                 8       1  87.50%   29
problem/spatial_problem.py                                                    8       0  100.00%
problem/time_dependent_problem.py                                             8       0  100.00%
problem/zoo/__init__.py                                                       9       0  100.00%
problem/zoo/acoustic_wave.py                                                 26       7  73.08%   26-27, 91-95
problem/zoo/advection.py                                                     23       4  82.61%   20, 74-76
problem/zoo/allen_cahn.py                                                    23       3  86.96%   20-22
problem/zoo/diffusion_reaction.py                                            32       5  84.38%   103-113
problem/zoo/helmholtz.py                                                     22       4  81.82%   54, 73-77
problem/zoo/inverse_poisson_2d_square.py                                     48       3  93.75%   45-51
problem/zoo/poisson_2d_square.py                                             16       3  81.25%   56-61
problem/zoo/supervised_problem.py                                            11       0  100.00%
solver/__init__.py                                                            6       0  100.00%
solver/garom.py                                                             107       2  98.13%   129-130
solver/solver.py                                                            186      10  94.62%   191, 214, 286, 289-290, 348, 430, 513, 554, 560
solver/ensemble_solver/__init__.py                                            4       0  100.00%
solver/ensemble_solver/ensemble_pinn.py                                      23       1  95.65%   104
solver/ensemble_solver/ensemble_solver_interface.py                          27       0  100.00%
solver/ensemble_solver/ensemble_supervised.py                                 9       0  100.00%
solver/physics_informed_solver/__init__.py                                    8       0  100.00%
solver/physics_informed_solver/causal_pinn.py                                47       3  93.62%   157, 166-167
solver/physics_informed_solver/competitive_pinn.py                           58       0  100.00%
solver/physics_informed_solver/gradient_pinn.py                              17       0  100.00%
solver/physics_informed_solver/pinn.py                                       18       0  100.00%
solver/physics_informed_solver/pinn_interface.py                             53       2  96.23%   164, 220
solver/physics_informed_solver/rba_pinn.py                                   74       1  98.65%   324
solver/physics_informed_solver/self_adaptive_pinn.py                        104       1  99.04%   392
solver/supervised_solver/__init__.py                                          4       0  100.00%
solver/supervised_solver/reduced_order_model.py                              24       1  95.83%   137
solver/supervised_solver/supervised.py                                        7       0  100.00%
solver/supervised_solver/supervised_solver_interface.py                      25       1  96.00%   90
TOTAL                                                                      5226     371  92.90%

Results for commit: 3209ce9

Minimum allowed coverage is 80.123%

♻️ This comment has been updated with latest results

GiovanniCanali
GiovanniCanali requested changes Jan 7, 2026
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Very nice feature!

Unfortunately, the links in the diagram do not properly represent the structure in PINA. For instance, pina.optim does not depend upon pina.solver. The vast majority of modules depend directly on pina. Is there a way to make this without having a diagram which is too wide?

README.md Outdated
direction LR
PROB["<h2>pina.problem</h2> Module for defining problems via base class inheritance"]
MODEL["<h2>pina.model</h2> Module for built-in PyTorch models full architectures"]
SOLVER["<h2>pina.solve</h2>r Module for built-in solvers and abstract interfaces"]
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Missing "r" in pina.solver

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ndem0 commented Jan 7, 2026

Very nice feature!

Unfortunately, the links in the diagram do not properly represent the structure in PINA. For instance, pina.optim does not depend upon pina.solver. The vast majority of modules depend directly on pina. Is there a way to make this without having a diagram which is too wide?

Yeah, I just tried to make a diagramm similar to the API image, but the structure should be a little bit different. We can also have "invisible" edges if needed. My only focus here is changing static to dynamic!

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