@@ -931,11 +931,7 @@ def npv(rate, values):
931931 net present value:
932932
933933 >>> rate, cashflows = 0.08, [-40_000, 5_000, 8_000, 12_000, 30_000]
934- <<<<<<< HEAD
935- >>> round(npf.npv(rate, cashflows), 5)
936- =======
937934 >>> np.round(npf.npv(rate, cashflows), 5)
938- >>>>>>> 3311612dc27bf4d7df10e7cc5b7222bf51113728
939935 3065.22267
940936
941937 It may be preferable to split the projected cashflow into an initial
@@ -1065,7 +1061,6 @@ def mirr(values, finance_rate, reinvest_rate, *, raise_exceptions=False):
10651061 Finally, let's explore the situation where all cash flows are positive,
10661062 and the `raise_exceptions` parameter is set to True.
10671063
1068- <<<<<<< HEAD
10691064 >>> npf.mirr([
10701065 ... 100, 50, 60, 70],
10711066 ... 0.10, 0.12,
@@ -1075,12 +1070,6 @@ def mirr(values, finance_rate, reinvest_rate, *, raise_exceptions=False):
10751070 ...
10761071 numpy_financial._financial.NoRealSolutionError: No real solution exists for MIRR since
10771072 all cashflows are of the same sign.
1078- =======
1079- >>> npf.mirr([100, 50, 60, 70], 0.10, 0.12, raise_exceptions=True)
1080- Traceback (most recent call last):
1081- ...
1082- numpy_financial._financial.NoRealSolutionError: No real solution exists for MIRR since all cashflows are of the same sign.
1083- >>>>>>> 3311612dc27bf4d7df10e7cc5b7222bf51113728
10841073 """
10851074 values = np .asarray (values )
10861075 n = values .size
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