RuntimeWarning: invalid value encountered in log

I become this expression:
RuntimeWarning: invalid value encountered in log

while trying this:

def fct(a, b, c, d):

    global u1

    global u2

    if np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0):

        return a, c, u1, u2



    u1, u2 = np.log(0.6*c), (math.e**d)**0.5

    F = np.log(a**2) + 6*[math.e**(-b)]/u1 + 3/u2

    print( F )

any idea??

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

asked Nov 14 '18 at 12:39

Plop

104

Specify the a,b,c,d parameters' values too, this function gave the message above, pls, to be able to help you

– Geeocode
Nov 14 '18 at 12:55

This condition np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0) is exactly the case where none of the operations after the if block would fail. That means that, as the code is now, if you reach those operations at least one of them will fail. Maybe those should go within the if block?

– jdehesa
Nov 14 '18 at 13:11

Please move your edit from answers to question deleting your answer and editing your question, as it is the common on the SO-n and I'm trying to prevent you from getting downvotes to your "answer".

– Geeocode
Nov 14 '18 at 14:06

add a comment |

I become this expression:
RuntimeWarning: invalid value encountered in log

while trying this:

def fct(a, b, c, d):

    global u1

    global u2

    if np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0):

        return a, c, u1, u2



    u1, u2 = np.log(0.6*c), (math.e**d)**0.5

    F = np.log(a**2) + 6*[math.e**(-b)]/u1 + 3/u2

    print( F )

any idea??

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

asked Nov 14 '18 at 12:39

Plop

104

Specify the a,b,c,d parameters' values too, this function gave the message above, pls, to be able to help you

– Geeocode
Nov 14 '18 at 12:55

This condition np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0) is exactly the case where none of the operations after the if block would fail. That means that, as the code is now, if you reach those operations at least one of them will fail. Maybe those should go within the if block?

– jdehesa
Nov 14 '18 at 13:11

Please move your edit from answers to question deleting your answer and editing your question, as it is the common on the SO-n and I'm trying to prevent you from getting downvotes to your "answer".

– Geeocode
Nov 14 '18 at 14:06

add a comment |

I become this expression:
RuntimeWarning: invalid value encountered in log

while trying this:

def fct(a, b, c, d):

    global u1

    global u2

    if np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0):

        return a, c, u1, u2



    u1, u2 = np.log(0.6*c), (math.e**d)**0.5

    F = np.log(a**2) + 6*[math.e**(-b)]/u1 + 3/u2

    print( F )

any idea??

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

asked Nov 14 '18 at 12:39

Plop

104

I become this expression:
RuntimeWarning: invalid value encountered in log

while trying this:

def fct(a, b, c, d):

    global u1

    global u2

    if np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0):

        return a, c, u1, u2



    u1, u2 = np.log(0.6*c), (math.e**d)**0.5

    F = np.log(a**2) + 6*[math.e**(-b)]/u1 + 3/u2

    print( F )

any idea??

python numpy logging

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

asked Nov 14 '18 at 12:39

Plop

104

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

asked Nov 14 '18 at 12:39

Plop

104

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

edited Nov 14 '18 at 13:09

Carlos Gonzalez

429511

asked Nov 14 '18 at 12:39

Plop

104

asked Nov 14 '18 at 12:39

Plop

104

asked Nov 14 '18 at 12:39

Plop

104

Specify the a,b,c,d parameters' values too, this function gave the message above, pls, to be able to help you

– Geeocode
Nov 14 '18 at 12:55

This condition np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0) is exactly the case where none of the operations after the if block would fail. That means that, as the code is now, if you reach those operations at least one of them will fail. Maybe those should go within the if block?

– jdehesa
Nov 14 '18 at 13:11

Please move your edit from answers to question deleting your answer and editing your question, as it is the common on the SO-n and I'm trying to prevent you from getting downvotes to your "answer".

– Geeocode
Nov 14 '18 at 14:06

add a comment |

Specify the a,b,c,d parameters' values too, this function gave the message above, pls, to be able to help you

– Geeocode
Nov 14 '18 at 12:55

This condition np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0) is exactly the case where none of the operations after the if block would fail. That means that, as the code is now, if you reach those operations at least one of them will fail. Maybe those should go within the if block?

– jdehesa
Nov 14 '18 at 13:11

Please move your edit from answers to question deleting your answer and editing your question, as it is the common on the SO-n and I'm trying to prevent you from getting downvotes to your "answer".

– Geeocode
Nov 14 '18 at 14:06

Specify the a,b,c,d parameters' values too, this function gave the message above, pls, to be able to help you

– Geeocode
Nov 14 '18 at 12:55

This condition np.all(c > 0) and np.all(a > 0) and np.all(u1 != 0) and np.all(u2 != 0) is exactly the case where none of the operations after the if block would fail. That means that, as the code is now, if you reach those operations at least one of them will fail. Maybe those should go within the if block?

– jdehesa
Nov 14 '18 at 13:11

Please move your edit from answers to question deleting your answer and editing your question, as it is the common on the SO-n and I'm trying to prevent you from getting downvotes to your "answer".

– Geeocode
Nov 14 '18 at 14:06

add a comment |

1 Answer
1

active

oldest

votes

This error message can emerge at two expression your code contains:

np.log(0.6*c) and np.log(a**2)

in the for loop with:

np.random.normal()

you will get random numbers at this distribution, whose values will be negative numbers.

That's why np.log() will drop up the error message:

RuntimeWarning: invalid value encountered in log

Example:

np.random.normal(10,4,100)

Out:

array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967!!!!!,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 !!!!!!!! ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])

Stepping into your function inside of np.log()

c = np.array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])



print(np.log(0.6*c))

Out:

[1.5744293  2.16326705 1.87774385 2.08263134 0.683042   2.30047974

 1.85392487 0.8868894  1.83977989    nan!!!! 2.07727203 0.90828911

 1.97948987 1.83373484 1.48988563 2.00427818 1.70883942 1.89896326

 1.9868364  2.03069579 1.73374247 2.03691412 1.6896455  1.05494996

 2.06415373 2.03171923 1.30645371 1.46116503 0.9515167  1.70033691

 1.63207021 2.01165063 1.16586138 1.23004771 2.09415483 1.98309906

 0.78420515 1.12907599 1.66252576 2.01870777 2.20533276 0.67237842

 1.77790089 2.25472861 1.25280091 1.16210379 1.66527617 2.07081933

 1.40460207 1.64934404 1.44376192 2.11044202 2.23423935 1.82511354

 1.5339539  1.91185638 1.93742888 1.43961306 1.85300085 1.94625801

 1.94949438 1.86721233 1.12101435 2.23745876 1.74408784 1.90670008

 1.90718784 1.52823552 2.03194439 1.79137243 2.09322197 1.53507929

 1.6583943  2.05583165 1.40131649 2.05687444 1.85708328 2.22101297

 2.24080525   nan!!!!! 0.29364465 1.90650203 0.96574761 1.18643181

 2.2264023  2.17754854 2.16475684 0.79863852 1.10485699 1.14704071

 2.28359159 1.44716024 1.40789551 2.17652834 1.62127664 2.04443742

 1.43739808 1.52110397 1.45579155 2.49300123]

/untitled0.py:37: RuntimeWarning: invalid value encountered in log

edited Nov 14 '18 at 14:17

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

add a comment |

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1 Answer
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1 Answer
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This error message can emerge at two expression your code contains:

np.log(0.6*c) and np.log(a**2)

in the for loop with:

np.random.normal()

you will get random numbers at this distribution, whose values will be negative numbers.

That's why np.log() will drop up the error message:

RuntimeWarning: invalid value encountered in log

Example:

np.random.normal(10,4,100)

Out:

array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967!!!!!,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 !!!!!!!! ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])

Stepping into your function inside of np.log()

c = np.array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])



print(np.log(0.6*c))

Out:

[1.5744293  2.16326705 1.87774385 2.08263134 0.683042   2.30047974

 1.85392487 0.8868894  1.83977989    nan!!!! 2.07727203 0.90828911

 1.97948987 1.83373484 1.48988563 2.00427818 1.70883942 1.89896326

 1.9868364  2.03069579 1.73374247 2.03691412 1.6896455  1.05494996

 2.06415373 2.03171923 1.30645371 1.46116503 0.9515167  1.70033691

 1.63207021 2.01165063 1.16586138 1.23004771 2.09415483 1.98309906

 0.78420515 1.12907599 1.66252576 2.01870777 2.20533276 0.67237842

 1.77790089 2.25472861 1.25280091 1.16210379 1.66527617 2.07081933

 1.40460207 1.64934404 1.44376192 2.11044202 2.23423935 1.82511354

 1.5339539  1.91185638 1.93742888 1.43961306 1.85300085 1.94625801

 1.94949438 1.86721233 1.12101435 2.23745876 1.74408784 1.90670008

 1.90718784 1.52823552 2.03194439 1.79137243 2.09322197 1.53507929

 1.6583943  2.05583165 1.40131649 2.05687444 1.85708328 2.22101297

 2.24080525   nan!!!!! 0.29364465 1.90650203 0.96574761 1.18643181

 2.2264023  2.17754854 2.16475684 0.79863852 1.10485699 1.14704071

 2.28359159 1.44716024 1.40789551 2.17652834 1.62127664 2.04443742

 1.43739808 1.52110397 1.45579155 2.49300123]

/untitled0.py:37: RuntimeWarning: invalid value encountered in log

edited Nov 14 '18 at 14:17

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

add a comment |

This error message can emerge at two expression your code contains:

np.log(0.6*c) and np.log(a**2)

in the for loop with:

np.random.normal()

you will get random numbers at this distribution, whose values will be negative numbers.

That's why np.log() will drop up the error message:

RuntimeWarning: invalid value encountered in log

Example:

np.random.normal(10,4,100)

Out:

array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967!!!!!,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 !!!!!!!! ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])

Stepping into your function inside of np.log()

c = np.array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])



print(np.log(0.6*c))

Out:

[1.5744293  2.16326705 1.87774385 2.08263134 0.683042   2.30047974

 1.85392487 0.8868894  1.83977989    nan!!!! 2.07727203 0.90828911

 1.97948987 1.83373484 1.48988563 2.00427818 1.70883942 1.89896326

 1.9868364  2.03069579 1.73374247 2.03691412 1.6896455  1.05494996

 2.06415373 2.03171923 1.30645371 1.46116503 0.9515167  1.70033691

 1.63207021 2.01165063 1.16586138 1.23004771 2.09415483 1.98309906

 0.78420515 1.12907599 1.66252576 2.01870777 2.20533276 0.67237842

 1.77790089 2.25472861 1.25280091 1.16210379 1.66527617 2.07081933

 1.40460207 1.64934404 1.44376192 2.11044202 2.23423935 1.82511354

 1.5339539  1.91185638 1.93742888 1.43961306 1.85300085 1.94625801

 1.94949438 1.86721233 1.12101435 2.23745876 1.74408784 1.90670008

 1.90718784 1.52823552 2.03194439 1.79137243 2.09322197 1.53507929

 1.6583943  2.05583165 1.40131649 2.05687444 1.85708328 2.22101297

 2.24080525   nan!!!!! 0.29364465 1.90650203 0.96574761 1.18643181

 2.2264023  2.17754854 2.16475684 0.79863852 1.10485699 1.14704071

 2.28359159 1.44716024 1.40789551 2.17652834 1.62127664 2.04443742

 1.43739808 1.52110397 1.45579155 2.49300123]

/untitled0.py:37: RuntimeWarning: invalid value encountered in log

edited Nov 14 '18 at 14:17

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

add a comment |

This error message can emerge at two expression your code contains:

np.log(0.6*c) and np.log(a**2)

in the for loop with:

np.random.normal()

you will get random numbers at this distribution, whose values will be negative numbers.

That's why np.log() will drop up the error message:

RuntimeWarning: invalid value encountered in log

Example:

np.random.normal(10,4,100)

Out:

array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967!!!!!,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 !!!!!!!! ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])

Stepping into your function inside of np.log()

c = np.array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])



print(np.log(0.6*c))

Out:

[1.5744293  2.16326705 1.87774385 2.08263134 0.683042   2.30047974

 1.85392487 0.8868894  1.83977989    nan!!!! 2.07727203 0.90828911

 1.97948987 1.83373484 1.48988563 2.00427818 1.70883942 1.89896326

 1.9868364  2.03069579 1.73374247 2.03691412 1.6896455  1.05494996

 2.06415373 2.03171923 1.30645371 1.46116503 0.9515167  1.70033691

 1.63207021 2.01165063 1.16586138 1.23004771 2.09415483 1.98309906

 0.78420515 1.12907599 1.66252576 2.01870777 2.20533276 0.67237842

 1.77790089 2.25472861 1.25280091 1.16210379 1.66527617 2.07081933

 1.40460207 1.64934404 1.44376192 2.11044202 2.23423935 1.82511354

 1.5339539  1.91185638 1.93742888 1.43961306 1.85300085 1.94625801

 1.94949438 1.86721233 1.12101435 2.23745876 1.74408784 1.90670008

 1.90718784 1.52823552 2.03194439 1.79137243 2.09322197 1.53507929

 1.6583943  2.05583165 1.40131649 2.05687444 1.85708328 2.22101297

 2.24080525   nan!!!!! 0.29364465 1.90650203 0.96574761 1.18643181

 2.2264023  2.17754854 2.16475684 0.79863852 1.10485699 1.14704071

 2.28359159 1.44716024 1.40789551 2.17652834 1.62127664 2.04443742

 1.43739808 1.52110397 1.45579155 2.49300123]

/untitled0.py:37: RuntimeWarning: invalid value encountered in log

edited Nov 14 '18 at 14:17

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

This error message can emerge at two expression your code contains:

np.log(0.6*c) and np.log(a**2)

in the for loop with:

np.random.normal()

you will get random numbers at this distribution, whose values will be negative numbers.

That's why np.log() will drop up the error message:

RuntimeWarning: invalid value encountered in log

Example:

np.random.normal(10,4,100)

Out:

array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967!!!!!,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 !!!!!!!! ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])

Stepping into your function inside of np.log()

c = np.array([ 8.04664247, 14.4991884 , 10.89789303, 13.37593183,  3.29981902,

       16.6316143 , 10.64138342,  4.0459445 , 10.49192082, -3.04538967,

       13.30443781,  4.13345961, 12.06508196, 10.4286879 ,  7.39431349,

       12.36789249,  9.20424736, 11.13161087, 12.15404482, 12.69897663,

        9.43633904, 12.77818913,  9.02926639,  4.78638573, 13.13104605,

       12.71197993,  6.1550897 ,  7.18496505,  4.3160573 ,  9.12631992,

        8.52408627, 12.45941119,  5.34780934,  5.7023213 , 13.53096085,

       12.1087058 ,  3.65110834,  5.15466232,  8.78768562, 12.54764999,

       15.12211713,  3.26481809,  9.8623701 , 15.88784306,  5.83355467,

        5.32775214,  8.81188865, 13.21886467,  6.78984216,  8.67260897,

        7.06100605, 13.75314668, 15.56562533, 10.33916552,  7.72745465,

       11.27606127, 11.56813697,  7.03177164, 10.63155512, 11.67072579,

       11.70855769, 10.78372397,  5.11327436, 15.61581808,  9.53446815,

       11.21806808, 11.2235412 ,  7.68339223, 12.71484256,  9.99613038,

       13.51834424,  7.73615596,  8.75145457, 13.02222188,  6.76757021,

       13.03580839, 10.67504642, 15.36110384, 15.66816384, -0.0952157 ,

        2.23551198, 11.21584659,  4.37791786,  5.45895529, 15.44411348,

       14.7077441 , 14.52080519,  3.70418827,  5.03132122,  5.24810117,

       16.35309566,  7.08504246,  6.81224092, 14.69274684,  8.43257572,

       12.87468578,  7.01621364,  7.62879265,  7.14646032, 20.16254855])



print(np.log(0.6*c))

Out:

[1.5744293  2.16326705 1.87774385 2.08263134 0.683042   2.30047974

 1.85392487 0.8868894  1.83977989    nan!!!! 2.07727203 0.90828911

 1.97948987 1.83373484 1.48988563 2.00427818 1.70883942 1.89896326

 1.9868364  2.03069579 1.73374247 2.03691412 1.6896455  1.05494996

 2.06415373 2.03171923 1.30645371 1.46116503 0.9515167  1.70033691

 1.63207021 2.01165063 1.16586138 1.23004771 2.09415483 1.98309906

 0.78420515 1.12907599 1.66252576 2.01870777 2.20533276 0.67237842

 1.77790089 2.25472861 1.25280091 1.16210379 1.66527617 2.07081933

 1.40460207 1.64934404 1.44376192 2.11044202 2.23423935 1.82511354

 1.5339539  1.91185638 1.93742888 1.43961306 1.85300085 1.94625801

 1.94949438 1.86721233 1.12101435 2.23745876 1.74408784 1.90670008

 1.90718784 1.52823552 2.03194439 1.79137243 2.09322197 1.53507929

 1.6583943  2.05583165 1.40131649 2.05687444 1.85708328 2.22101297

 2.24080525   nan!!!!! 0.29364465 1.90650203 0.96574761 1.18643181

 2.2264023  2.17754854 2.16475684 0.79863852 1.10485699 1.14704071

 2.28359159 1.44716024 1.40789551 2.17652834 1.62127664 2.04443742

 1.43739808 1.52110397 1.45579155 2.49300123]

/untitled0.py:37: RuntimeWarning: invalid value encountered in log

edited Nov 14 '18 at 14:17

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

edited Nov 14 '18 at 14:17

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

answered Nov 14 '18 at 13:11

Geeocode

2,3181820

add a comment |

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