diff --git a/phantoms/brain/data/ballistic_snr200.bval b/phantoms/brain/data/ballistic_snr200.bval
new file mode 100644
index 0000000..f0b9947
--- /dev/null
+++ b/phantoms/brain/data/ballistic_snr200.bval
@@ -0,0 +1 @@
+0 10 20 30 40 50 60 70 80 90 100 120 140 160 180 200 10 20 30 40 50 60 70 80 90 100 120 140 160 180 200
\ No newline at end of file
diff --git a/phantoms/brain/data/ballistic_snr200.cval b/phantoms/brain/data/ballistic_snr200.cval
new file mode 100644
index 0000000..4e00317
--- /dev/null
+++ b/phantoms/brain/data/ballistic_snr200.cval
@@ -0,0 +1 @@
+0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.471 0.666 0.816 0.942 1.054 1.154 1.247 1.333 1.414 1.490 1.632 1.763 1.885 1.999 2.107 
\ No newline at end of file
diff --git a/phantoms/brain/data/ballistic_snr200.nii.gz b/phantoms/brain/data/ballistic_snr200.nii.gz
new file mode 100644
index 0000000..a48d087
--- /dev/null
+++ b/phantoms/brain/data/ballistic_snr200.nii.gz
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+version https://git-lfs.github.com/spec/v1
+oid sha256:59e2381e64ac5443fcb2d2bfd065780dc6804b126c370ab13c3a72e0076ffae4
+size 76022310
diff --git a/phantoms/brain/data/diffusive_snr200.bval b/phantoms/brain/data/diffusive_snr200.bval
new file mode 100644
index 0000000..9e2729c
--- /dev/null
+++ b/phantoms/brain/data/diffusive_snr200.bval
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+0 10 20 30 40 80 110 140 170 200 300 400 500 600 700 800 900
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diff --git a/phantoms/brain/data/diffusive_snr200.nii.gz b/phantoms/brain/data/diffusive_snr200.nii.gz
new file mode 100644
index 0000000..d5cacf4
--- /dev/null
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+version https://git-lfs.github.com/spec/v1
+oid sha256:6916d0f70b2c5f9ec6e2f2376c49cbf1a81cc55339e354462ffcdf944634eea1
+size 41666269
diff --git a/tests/IVIMmodels/data/__init__.py b/tests/IVIMmodels/data/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/IVIMmodels/data/test_GenerateData.py b/tests/IVIMmodels/data/test_GenerateData.py
new file mode 100644
index 0000000..9e65849
--- /dev/null
+++ b/tests/IVIMmodels/data/test_GenerateData.py
@@ -0,0 +1,71 @@
+import numpy as np
+import numpy.testing as npt
+import pytest
+#import torch
+
+from utilities.data_simulation.GenerateData import GenerateData
+
+#run using python -m pytest from the root folder
+
+test_monoexponential_data = [
+    pytest.param(0, np.linspace(0, 1000, 11), id='0'),
+    pytest.param(0.1, np.linspace(0, 1000, 11), id='0.1'),
+    pytest.param(0.2, np.linspace(0, 1000, 11), id='0.2'),
+    pytest.param(0.3, np.linspace(0, 1000, 11), id='0.3'),
+    pytest.param(0.4, np.linspace(0, 1000, 11), id='0.4'),
+    pytest.param(0.5, np.linspace(0, 1000, 11), id='0.5'),
+    pytest.param(0.8, np.linspace(0, 1000, 11), id='0.8'),
+    pytest.param(1, np.linspace(0, 1000, 11), id='1'),
+]
+@pytest.mark.parametrize("D, bvals", test_monoexponential_data)
+def test_monoexponential(D, bvals):
+    gd = GenerateData()
+    gd_signal = gd.exponential_signal(D, bvals)
+    testing_signal = np.exp(-D * np.asarray(bvals, dtype='float64'))
+    npt.assert_allclose(gd_signal, testing_signal)
+    assert(gd_signal[0] >= testing_signal[0])
+
+test_ivim_data = [
+    pytest.param(0.01, 0.0, 1, 1, np.linspace(0, 1000, 11), None, False),
+    pytest.param(0.01, 0.1, 0.05, 1, np.linspace(0, 1000, 11), None, False),
+    pytest.param(0.05, 0.2, 0.1, 1, np.linspace(0, 800, 11), None, False),
+    pytest.param(0.04, 0.15, 0.25, 1.5, np.linspace(0, 1000, 2), 10, True),
+    pytest.param(0.1, 0.5, 0.5, 0.5, np.linspace(0, 1500, 5), 100, True),
+    pytest.param(0.01, 0.2, 0.1, 1, np.linspace(10, 1500, 11), 100, False),
+    pytest.param(0.1, 0.15, 0.05, 1, np.linspace(10, 1000, 8), 5, False)
+]
+@pytest.mark.parametrize('D, Dp, f, S0, bvals, snr, rician_noise', test_ivim_data)
+def test_ivim(D, Dp, f, S0, bvals, snr, rician_noise):
+    gd = GenerateData()
+    gd_signal = gd.ivim_signal(D, Dp, f, S0, bvals, snr, rician_noise)
+    testing_signal = S0 * ((1 - f) * np.exp(-D * bvals) + f * np.exp(-Dp * bvals))
+    atol = 0.0
+    if snr is not None:
+        atol = 4 / snr
+    npt.assert_allclose(gd_signal, testing_signal, atol=atol)
+
+
+test_linear_data = [
+    pytest.param(0, np.linspace(0, 1000, 11), 0, id='0'),
+    pytest.param(0.1, np.linspace(0, 1000, 11), 10, id='0.1'),
+    pytest.param(0.2, np.linspace(0, 1000, 11), -10, id='0.2'),
+    pytest.param(0.3, np.linspace(0, 1000, 11), 0, id='0.3'),
+    pytest.param(0.4, np.linspace(0, 1000, 11), 0, id='0.4'),
+    pytest.param(0.5, np.linspace(0, 1000, 11), 0, id='0.5'),
+    pytest.param(0.8, np.linspace(0, 1000, 11), 0, id='0.8'),
+    pytest.param(1, np.linspace(0, 1000, 11), 0, id='1'),
+]
+@pytest.mark.parametrize("D, bvals, offset", test_linear_data)
+def test_linear(D, bvals, offset):
+    gd = GenerateData()
+    gd_signal = gd.linear_signal(D, bvals, offset)
+    testing_signal = -D * np.asarray(bvals, dtype='float64')
+    testing_signal += offset
+    npt.assert_allclose(gd_signal, testing_signal)
+    assert(gd_signal[0] >= testing_signal[0])
+        
+    gd_exponential = gd.exponential_signal(D, bvals)
+    gd_log_exponential = np.log(gd_exponential) + offset
+    real_mask = np.isfinite(gd_log_exponential)
+    
+    npt.assert_allclose(gd_log_exponential[real_mask], gd_signal[real_mask])