diff --git a/assumptions_check.py b/assumptions_check.py
new file mode 100644
index 0000000..e17586e
--- /dev/null
+++ b/assumptions_check.py
@@ -0,0 +1,94 @@
+import sys
+
+import numpy as np
+import matplotlib.pyplot as plt
+from numpy.polynomial.chebyshev import chebfit, chebval
+
+from disk_perf_test_tool.tests.io_results_loader import load_data, filter_data
+
+
+def linearity_plot(plt, data, types):
+    fields = 'blocksize_b', 'iops_mediana', 'iops_stddev'
+
+    names = {}
+    for tp1 in ('rand', 'seq'):
+        for oper in ('read', 'write'):
+            for sync in ('sync', 'direct', 'async'):
+                sq = (tp1, oper, sync)
+                name = "{0} {1} {2}".format(*sq)
+                names["".join(word[0] for word in sq)] = name
+
+    for tp in types:
+        filtered_data = filter_data('linearity_test_' + tp, fields)
+        x = []
+        y = []
+        e = []
+
+        for sz, med, dev in sorted(filtered_data(data)):
+            iotime_ms = 1000. // med
+            iotime_max = 1000. // (med - dev * 3)
+
+            x.append(sz / 1024)
+            y.append(iotime_ms)
+            e.append(iotime_max - iotime_ms)
+
+        plt.errorbar(x, y, e, linestyle='None', marker=names[tp])
+    plt.legend(loc=2)
+
+
+def th_plot(data, tt):
+    fields = 'concurence', 'iops_mediana', 'lat_mediana'
+    conc_4k = filter_data('concurrence_test_' + tt, fields, blocksize='4k')
+    filtered_data = sorted(list(conc_4k(data)))
+
+    x, iops, lat = zip(*filtered_data)
+
+    _, ax1 = plt.subplots()
+
+    xnew = np.linspace(min(x), max(x), 50)
+    # plt.plot(xnew, power_smooth, 'b-', label='iops')
+    ax1.plot(x, iops, 'b*')
+
+    for degree in (3,):
+        c = chebfit(x, iops, degree)
+        vals = chebval(xnew, c)
+        ax1.plot(xnew, vals, 'g--')
+
+    # ax1.set_xlabel('thread count')
+    # ax1.set_ylabel('iops')
+
+    # ax2 = ax1.twinx()
+    # lat = [i / 1000 for i in lat]
+    # ax2.plot(x, lat, 'r*')
+
+    # tck = splrep(x, lat, s=0.0)
+    # power_smooth = splev(xnew, tck)
+    # ax2.plot(xnew, power_smooth, 'r-', label='lat')
+
+    # xp = xnew[0]
+    # yp = power_smooth[0]
+    # for _x, _y in zip(xnew[1:], power_smooth[1:]):
+    #     if _y >= 100:
+    #         xres = (_y - 100.) / (_y - yp) * (_x - xp) + xp
+    #         ax2.plot([xres, xres], [min(power_smooth), max(power_smooth)], 'g--')
+    #         break
+    #     xp = _x
+    #     yp = _y
+
+    # ax2.plot([min(x), max(x)], [20, 20], 'g--')
+    # ax2.plot([min(x), max(x)], [100, 100], 'g--')
+
+    # ax2.set_ylabel("lat ms")
+    # plt.legend(loc=2)
+
+
+def main(argv):
+    data = list(load_data(open(argv[1]).read()))
+    # linearity_plot(data)
+    th_plot(data, 'rws')
+    # th_plot(data, 'rrs')
+    plt.show()
+
+
+if __name__ == "__main__":
+    exit(main(sys.argv))