Add test and CI

.travis.yml

@@ -0,0 +1,14 @@
+language: python
+
+python:
+  - "3.6"
+
+install:
+  - pip3 install .
+
+script:
+  - cd test
+  - pytest --cov ddtruss
+
+after_success:
+  - codecov

README.md

@@ -7,9 +7,7 @@
 
 This repository provides a Python implementation of the data-driven solver for truss structures described in [Kirchdoerfer, T., & Ortiz, M. (2016). Data-driven computational mechanics. Computer Methods in Applied Mechanics and Engineering, 304, 81-101](https://www.sciencedirect.com/science/article/pii/S0045782516300238).
 
-<p align="center">
-  <img src="https://user-images.githubusercontent.com/4027283/63096980-9561cb00-bf6f-11e9-88a7-d07081138f19.png" width="800">
-</p>
+![](https://user-images.githubusercontent.com/4027283/63096980-9561cb00-bf6f-11e9-88a7-d07081138f19.png)
 
 Some notebook examples can be found in `examples`.
 

ddtruss/solver.py

@@ -36,7 +36,7 @@ def solve(self, A=1, U_dict={}, F_dict={}, n_iterations=100, E_num=None):
 
         Args
         ----
-        A : float
+        A : float or ndarray, shape (n_lines, )
             Cross section area
         U_dict : dict
             Prescribed displacement ``{point_id: (Ux, Uy), ...}``

test/test_truss.py

@@ -0,0 +1,39 @@
+import numpy as np
+import pytest
+
+from ddtruss import Truss, DataDrivenSolver
+
+points = np.array([[0, 0], [1, 0], [0.5, 0.5], [2, 1]])
+lines = np.array([[0, 2], [1, 2], [1, 3], [2, 3]], dtype=int)
+
+truss = Truss(points, lines)
+
+E = 1.962e11
+A = [2e-4, 2e-4, 1e-4, 1e-4]
+U_dict = {0: [0, 0], 1: [0, 0]}
+F_dict = {3: [0, -9.81e3]}
+
+u_ref = np.array(
+    [0, 0, 0, 0, 2.65165043e-4, 8.83883476e-5, 3.47902545e-3, -5.60034579e-3]
+)
+
+
+def test_truss():
+    u, *_ = truss.solve(A=A, E=E, U_dict=U_dict, F_dict=F_dict)
+    assert np.allclose(u, u_ref)
+
+
+@pytest.mark.parametrize(
+    "n_data", [5000, 10000]
+)
+def test_data_driven_solver(n_data):
+    ddsolver = DataDrivenSolver(truss)
+
+    eps_max = 1.1e-3
+    eps = np.linspace(-eps_max, eps_max, n_data)
+    sig = E * eps
+    material_data = np.hstack([eps.reshape((-1, 1)), sig.reshape((-1, 1))])
+    ddsolver.load_material_data(material_data)
+
+    u, *_ = ddsolver.solve(A=A, U_dict=U_dict, F_dict=F_dict)
+    assert np.allclose(u, u_ref, rtol=1e-2)