bandwidth
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4 changed files with 21 additions and 1 deletions
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@ -13,6 +13,26 @@ plt.scatter(X, Y_CPY, color="b", marker="x", label="RISCV COPY")
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plt.scatter(X, YA_MEM, color="r", label="ARM MEM")
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plt.scatter(X, YA_CPY, color="r",marker="x", label="ARM COPY")
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x = np.array(X).reshape(-1, 1)
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y = np.array(Y_MEM).reshape(-1, 1)
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y2 = np.array(YA_MEM).reshape(-1, 1)
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reg = LinearRegression().fit(x, y)
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reg2 = LinearRegression().fit(x, y2)
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print("score obtenu : " + str(reg.score(x, y)))
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print("score obtenu : " + str(reg2.score(x, y2)))
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print("attente à zéro : {}".format(reg.intercept_))
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print("attente à zéro : {}".format(reg2.intercept_))
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x_lin = [0, max(X)]
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y_lin = [reg.predict(np.array([0]).reshape(-1, 1)), reg.predict(np.array([x_lin[1]]).reshape(-1, 1))]
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y_lin2 = [reg2.predict(np.array([0]).reshape(-1, 1)), reg2.predict(np.array([x_lin[1]]).reshape(-1, 1))]
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y_lin = [y_lin[0][0][0], y_lin[1][0][0]]
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y_lin2 = [y_lin2[0][0][0], y_lin2[1][0][0]]
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plt.plot(x_lin, y_lin, color = "b", label="RegLin score : {:.4f}".format(reg.score(x, y)))
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plt.plot(x_lin, y_lin2, color = "r", label="RegLin score : {:.4f}".format(reg2.score(x, y2)))
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plt.xlim([0, 1024])
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plt.ylim([50, 32000])
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plt.legend()
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@ -1,3 +1,3 @@
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Quartus_Version = Version 22.1std.0 Build 915 10/25/2022 SC Standard Edition
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Version_Index = 553882368
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Creation_Time = Thu Mar 9 10:59:19 2023
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Creation_Time = Thu Mar 9 16:31:59 2023
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