Modify pina.__init__.py and rm useless .py files

* rm meta.py, plotter.py, writer.py
* modify __init__ file
* modify tests due to __init__ import

tests/test_optimizer.py

@@ -1,6 +1,6 @@
 import torch
 import pytest
-from pina import TorchOptimizer
+from pina.optim import TorchOptimizer
 
 opt_list = [
     torch.optim.Adam, torch.optim.AdamW, torch.optim.SGD, torch.optim.RMSprop

tests/test_plotter.py

@@ -1,75 +0,0 @@
-from pina.domain import CartesianDomain
-from pina import Condition, Plotter
-from matplotlib.testing.decorators import image_comparison
-import matplotlib.pyplot as plt
-from pina.problem import SpatialProblem
-from pina.equation import FixedValue
-
-"""
-
-!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
-TODO : Fix the tests once the Plotter class is updated
-!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
-
-class FooProblem1D(SpatialProblem):
-
-    # assign output/ spatial and temporal variables
-    output_variables = ['u']
-    spatial_domain = CartesianDomain({'x' : [-1, 1]})
-
-    # problem condition statement
-    conditions = {
-        'D': Condition(location=CartesianDomain({'x': [-1, 1]}), equation=FixedValue(0.)),
-    }
-
-class FooProblem2D(SpatialProblem):
-
-    # assign output/ spatial and temporal variables
-    output_variables = ['u']
-    spatial_domain = CartesianDomain({'x' : [-1, 1], 'y': [-1, 1]})
-
-    # problem condition statement
-    conditions = {
-        'D': Condition(location=CartesianDomain({'x' : [-1, 1], 'y': [-1, 1]}), equation=FixedValue(0.)),
-    }
-
-class FooProblem3D(SpatialProblem):
-
-    # assign output/ spatial and temporal variables
-    output_variables = ['u']
-    spatial_domain = CartesianDomain({'x' : [-1, 1], 'y': [-1, 1], 'z':[-1,1]})
-
-    # problem condition statement
-    conditions = {
-        'D': Condition(location=CartesianDomain({'x' : [-1, 1], 'y': [-1, 1], 'z':[-1,1]}), equation=FixedValue(0.)),
-    }
-
-
-
-def test_constructor():
-    Plotter()
-
-def test_plot_samples_1d():
-    problem = FooProblem1D()
-    problem.discretise_domain(n=10, mode='grid', variables = 'x', locations=['D'])
-    pl = Plotter()
-    pl.plot_samples(problem=problem, filename='fig.png')
-    import os
-    os.remove('fig.png')
-
-def test_plot_samples_2d():
-    problem = FooProblem2D()
-    problem.discretise_domain(n=10, mode='grid', variables = ['x', 'y'], locations=['D'])
-    pl = Plotter()
-    pl.plot_samples(problem=problem, filename='fig.png')
-    import os
-    os.remove('fig.png')
-
-def test_plot_samples_3d():
-    problem = FooProblem3D()
-    problem.discretise_domain(n=10, mode='grid', variables = ['x', 'y', 'z'], locations=['D'])
-    pl = Plotter()
-    pl.plot_samples(problem=problem, filename='fig.png')
-    import os
-    os.remove('fig.png')
-"""

tests/test_problem_zoo/test_supervised_problem.py

@@ -2,7 +2,7 @@ import torch
 from pina.problem import AbstractProblem
 from pina.condition import InputOutputPointsCondition
 from pina.problem.zoo.supervised_problem import SupervisedProblem
-from pina import RadiusGraph
+from pina.graph import RadiusGraph
 
 def test_constructor():
     input_ = torch.rand((100,10))

tests/test_scheduler.py

@@ -1,7 +1,7 @@
 
 import torch
 import pytest
-from pina import TorchOptimizer, TorchScheduler
+from pina.optim import TorchOptimizer, TorchScheduler
 
 opt_list = [
     torch.optim.Adam,