Add tests

Makefile

@@ -1,4 +1,3 @@
-
 install: 
 	source ./script_install.sh
 
@@ -11,9 +10,15 @@ fftma:
 binaries: 
 	./script_fortran.sh
 
-test: binaries
+test: binaries fftma
 	cd tests/integration && python3 -m unittest test.py
 
 perf: binaries
 	cd tests/performance && python3 generation.py
 	cd tests/performance && python3 connectivity.py
+
+test-gen: fftma
+	cd tests/stages/generation && python3 -m unittest test.py
+
+time-gen: fftma
+	cd tests/performance/generation && python3 time.py $(N)

README.md

@@ -18,18 +18,32 @@ make binaries
 make run
 ```
 
-## Correr los casos de prueba
+## Pruebas de integración
 
 ```
 make test
 ```
 
+## Pruebas unitarias
+
+### Generacion
+
+```
+make test-gen
+```
+
 ## Correr las pruebas de performance
 
 ```
 make perf
 ```
 
+### Obtener tiempos de generacion
+
+```
+make time-gen N=<tamaño>
+```
+
 ## Instalar el binario FFTMA
 
 ```
@@ -43,5 +57,3 @@ El sistema actualmente se encuentra migrado a Python3 por lo que no se recomiend
 ```
 ./script_install_py2.sh
 ```
-
-

fftma_module/gen/example.py

@@ -0,0 +1,34 @@
+from FFTMA import gen
+import numpy as np
+import sys
+
+def generate(n):
+    nx, ny, nz = n,n,n
+    dx, dy, dz = 1.0, 1.0, 1.0
+    seed= 1548762 #rdi(10000,99999)
+    var=1
+    vario=2
+    alpha=1
+    lcx=2
+    lcy=4
+    lcz=16
+    ap1x=1
+    ap1y=0
+    ap1z=0
+    ap2x=0
+    ap2y=1
+    ap2z=0
+
+    v1 = (var, vario, alpha, lcx, lcy, lcz, ap1x, ap1y, ap1z, ap2x, ap2y, ap2z)
+    variograms = [v1]
+
+    mean=15.3245987
+    variance=3.5682389
+    typ=3
+
+    k=gen(nx, ny, nz, dx, dy, dz, seed, variograms, mean, variance, typ)
+    np.save(f"out_{n}.npy",k)
+
+if __name__ == '__main__':
+    N=int(sys.argv[1])
+    generate(N)

fftma_module/gen/include/geostat.h

@@ -422,7 +422,7 @@ float gammp(float a, float x);
 /*and unit variance, using ran1(idum) as the source */
 /*of uniform deviates                               */
 /*idum: seed                                        */
-double gasdev(long* idum, long* idum2, long* iy, long* iv, int* iset);
+double gasdev(long* idum, long* idum2, long* iy, long* iv);
 
 /*gaussian covariance value for lag h*/
 double gaussian(double h);

fftma_module/gen/lib_src/generate.c

@@ -33,7 +33,7 @@ void generate(long* seed, int n, struct realization_mod* realization)
 
     /*Gaussian white noise generation*/
     for (i = 0; i < n; i++)
-        (*realization).vector[i] = gasdev(seed, &idum2, &iy, iv, &iset);
+        (*realization).vector[i] = gasdev(seed, &idum2, &iy, iv);
 
     free(iv);
 }

fftma_module/gen/lib_src/geostat.h

@@ -423,7 +423,7 @@ float gammp(float a, float x);
 /*and unit variance, using ran1(idum) as the source */
 /*of uniform deviates                               */
 /*idum: seed                                        */
-double gasdev(long* idum, long* idum2, long* iy, long* iv, int* iset);
+double gasdev(long* idum, long* idum2, long* iy, long* iv);
 
 /*gaussian covariance value for lag h*/
 double gaussian(double h);

fftma_module/gen/mem_profile.py

@@ -0,0 +1,16 @@
+from sympy import N
+from example import generate
+
+from memory_profiler import memory_usage
+
+from memory_profiler import memory_usage
+import sys
+
+if __name__ == '__main__':
+    N=int(sys.argv[1])
+     
+    def run_gen():
+        generate(N)
+
+    mem_usage = memory_usage(run_gen)
+    print('Maximum memory usage: %s' % max(mem_usage))

fftma_module/gen/setup.py

@@ -1,9 +1,10 @@
 from distutils.core import setup, Extension
 
+import numpy
 
 module_FFTMA = Extension(
     "FFTMA",
-    include_dirs=["./include"],
+    include_dirs=["./include", numpy.get_include()],
     extra_compile_args=["-g", "-std=c99", "-Wall", "-Wconversion", "-Wtype-limits", "-pedantic"],
     sources=[
         "moduleFFTMA.c",

fftma_module/gen/test.py

@@ -1,36 +0,0 @@
-from FFTMA import gen
-import numpy as np
-import gc
-
-N=512
-
-nx, ny, nz = N,N,N
-dx, dy, dz = 1.0, 1.0, 1.0
-seed= 1548762 #rdi(10000,99999)
-var=1
-vario=2
-alpha=1
-lcx=2
-lcy=4
-lcz=16
-ap1x=1
-ap1y=0
-ap1z=0
-ap2x=0
-ap2y=1
-ap2z=0
-
-v1 = (var, vario, alpha, lcx, lcy, lcz, ap1x, ap1y, ap1z, ap2x, ap2y, ap2z)
-variograms = [v1]
-
-mean=15.3245987
-variance=3.5682389
-typ=3
-
-for i in range(2):
-    k=gen(nx, ny, nz, dx, dy, dz, seed, variograms, mean, variance, typ)
-
-    np.save(f"out_{i}.npy",k)
-
-    del k
-    gc.collect()

tests/performance/generation/time.py

@@ -0,0 +1,56 @@
+import numpy as np
+#from tests.utils.gen_sample import generate
+
+import sys
+
+from FFTMA import gen
+import time
+
+def generate(N):
+    start_time = time.time()
+    nx, ny, nz = N,N,N
+    dx, dy, dz = 1.0, 1.0, 1.0
+    seed= 1548762 #rdi(10000,99999)
+    var=1
+    vario=2
+    alpha=1
+    lcx=2
+    lcy=4
+    lcz=16
+    ap1x=1
+    ap1y=0
+    ap1z=0
+    ap2x=0
+    ap2y=1
+    ap2z=0
+
+    v1 = (var, vario, alpha, lcx, lcy, lcz, ap1x, ap1y, ap1z, ap2x, ap2y, ap2z)
+    variograms = [v1]
+
+    mean=15.3245987
+    variance=3.5682389
+    typ=3
+
+    k = gen(nx, ny, nz, dx, dy, dz, seed, variograms, mean, variance, typ)
+
+    duration = time.time() - start_time
+    return k, duration
+
+N=int(sys.argv[1])
+SAMPLE_SIZE=100
+
+def time_measurement(n, sample_size):
+    sample = []
+
+    print(f"SAMPLE_SIZE = {SAMPLE_SIZE}")
+    for i in range(sample_size):
+        _, duration = generate(n)
+        print(i)
+        sample.append(duration)
+    
+    npsample = np.array(sample)
+
+    print(f"AVG: {np.mean(npsample)} seconds")
+    print(f"MEDIAN: {np.median(npsample)} seconds")
+
+time_measurement(N, SAMPLE_SIZE)

tests/stages/generation/test.py

@@ -0,0 +1,53 @@
+from FFTMA import gen
+import numpy as np
+import unittest
+import time
+
+def generate(N):
+    start_time = time.time()
+    nx, ny, nz = N,N,N
+    dx, dy, dz = 1.0, 1.0, 1.0
+    seed= 1548762 #rdi(10000,99999)
+    var=1
+    vario=2
+    alpha=1
+    lcx=2
+    lcy=4
+    lcz=16
+    ap1x=1
+    ap1y=0
+    ap1z=0
+    ap2x=0
+    ap2y=1
+    ap2z=0
+
+    v1 = (var, vario, alpha, lcx, lcy, lcz, ap1x, ap1y, ap1z, ap2x, ap2y, ap2z)
+    variograms = [v1]
+
+    mean=15.3245987
+    variance=3.5682389
+    typ=3
+
+    k = gen(nx, ny, nz, dx, dy, dz, seed, variograms, mean, variance, typ)
+
+    print(f"Generation with N = {N} time = {time.time() - start_time}s")
+    return k
+
+
+def test(N):
+    k = generate(N)
+    k_correct = np.load(f"out_{N}.npy")
+    return np.allclose(k, k_correct, rtol=1e-10, atol=1e-10)
+
+class TestGeneration(unittest.TestCase):
+    def test_8(self):
+        self.assertTrue(test(8))
+
+    def test_16(self):
+        self.assertTrue(test(16))
+
+    def test_32(self):
+        self.assertTrue(test(32))
+
+    def test_64(self):
+        self.assertTrue(test(64))

tests/utils/gen_sample.py

@@ -0,0 +1,32 @@
+from FFTMA import gen
+import time
+
+def generate(N):
+    start_time = time.time()
+    nx, ny, nz = N,N,N
+    dx, dy, dz = 1.0, 1.0, 1.0
+    seed= 1548762 #rdi(10000,99999)
+    var=1
+    vario=2
+    alpha=1
+    lcx=2
+    lcy=4
+    lcz=16
+    ap1x=1
+    ap1y=0
+    ap1z=0
+    ap2x=0
+    ap2y=1
+    ap2z=0
+
+    v1 = (var, vario, alpha, lcx, lcy, lcz, ap1x, ap1y, ap1z, ap2x, ap2y, ap2z)
+    variograms = [v1]
+
+    mean=15.3245987
+    variance=3.5682389
+    typ=3
+
+    k = gen(nx, ny, nz, dx, dy, dz, seed, variograms, mean, variance, typ)
+
+    duration = time.time() - start_time
+    return k, duration