fixed bug that caused the price of gflop to actually be the price of flop
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bc29b1186e
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6e35053852
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@ -83,6 +83,7 @@ def get_computer_value_over_time(inventory, computer_id, time_value, flops_price
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computer_flops = inventory.get_computer_dflops(computer_id)
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computer_flops = inventory.get_computer_dflops(computer_id)
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computer_flops_over_time = np.where(time_value < purchase_time, 0.0, computer_flops)
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computer_flops_over_time = np.where(time_value < purchase_time, 0.0, computer_flops)
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computer_value_over_time = computer_flops_over_time * flops_price_over_time
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computer_value_over_time = computer_flops_over_time * flops_price_over_time
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return computer_value_over_time
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return computer_value_over_time
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# def stackplot(ax, x_signal, y_signals):
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# def stackplot(ax, x_signal, y_signals):
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@ -215,10 +216,10 @@ def draw_dp_gflops_price_over_time_over_time_graph(inventory, from_date, to_date
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"""
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"""
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time_value = matplotlib.dates.drange(dstart=from_date, dend=to_date, delta=datetime.timedelta(days=1))
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time_value = matplotlib.dates.drange(dstart=from_date, dend=to_date, delta=datetime.timedelta(days=1))
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flops_price_over_time = get_flops_price_over_time(inventory, time_value)
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gflops_price_over_time = get_flops_price_over_time(inventory, time_value) * 1.0e9
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fig, ax = plt.subplots()
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fig, ax = plt.subplots()
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ax.set_yscale('log')
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ax.set_yscale('log')
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ax.plot(time_value, flops_price_over_time)
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ax.plot(time_value, gflops_price_over_time)
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ax.set_xlabel('time')
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ax.set_xlabel('time')
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ax.set_ylabel(u'double precision flops price (€/gflops)')
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ax.set_ylabel(u'double precision flops price (€/gflops)')
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ax.set_title('gflops_price_over_time')
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ax.set_title('gflops_price_over_time')
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