How to use binned_statistic_2d with Non-monotonic boundary?

I'm using Lambert projection which means if longitude is monotonic then latitude is non-monotonic.

It's difficult to using binned_statistic_2d like this:

from scipy import stats

x = [-118,-117.8,-117.7,-80,-70]

y = [18.1,18,18,17.8,18]

lon = [-118.09100342, -117.987854, -117.88466644, -117.78141785, -117.67811584, -72.32189178, -72.21858215, -72.11533356, -72.012146, -71.90899658]

lat = [17.94124222, 17.96657181, 17.99184036, 18.01698875, 18.04202652,

18.04202652, 18.01698875, 17.99184036, 17.96657181, 17.94124222]

binx = lon

biny = lat

ret = stats.binned_statistic_2d(x, y, None, 'count', bins=[binx,biny])

Error:

ValueError: bins must be monotonically increasing or decreasing

How to deal with this issue?

My solution

Use zip to get boundaries of every grid;

Add condition to make sure the order is correct

for row in np.arange(lon_b.shape[0]-1):

k = 0

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,:]),iter(lat_b[row,:])]*2):

    # Because binned_statistic_2d need bin_* increase monotonically

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic



        k += 2



k = 1

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,1:]),iter(lat_b[row,1:])]*2):

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic                    

    k += 2

edited Nov 23 '18 at 12:07

asked Nov 22 '18 at 3:11

Xin Zhang

64211

add a comment |

I'm using Lambert projection which means if longitude is monotonic then latitude is non-monotonic.

It's difficult to using binned_statistic_2d like this:

from scipy import stats

x = [-118,-117.8,-117.7,-80,-70]

y = [18.1,18,18,17.8,18]

lon = [-118.09100342, -117.987854, -117.88466644, -117.78141785, -117.67811584, -72.32189178, -72.21858215, -72.11533356, -72.012146, -71.90899658]

lat = [17.94124222, 17.96657181, 17.99184036, 18.01698875, 18.04202652,

18.04202652, 18.01698875, 17.99184036, 17.96657181, 17.94124222]

binx = lon

biny = lat

ret = stats.binned_statistic_2d(x, y, None, 'count', bins=[binx,biny])

Error:

ValueError: bins must be monotonically increasing or decreasing

How to deal with this issue?

My solution

Use zip to get boundaries of every grid;

Add condition to make sure the order is correct

for row in np.arange(lon_b.shape[0]-1):

k = 0

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,:]),iter(lat_b[row,:])]*2):

    # Because binned_statistic_2d need bin_* increase monotonically

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic



        k += 2



k = 1

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,1:]),iter(lat_b[row,1:])]*2):

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic                    

    k += 2

edited Nov 23 '18 at 12:07

asked Nov 22 '18 at 3:11

Xin Zhang

64211

add a comment |

I'm using Lambert projection which means if longitude is monotonic then latitude is non-monotonic.

It's difficult to using binned_statistic_2d like this:

from scipy import stats

x = [-118,-117.8,-117.7,-80,-70]

y = [18.1,18,18,17.8,18]

lon = [-118.09100342, -117.987854, -117.88466644, -117.78141785, -117.67811584, -72.32189178, -72.21858215, -72.11533356, -72.012146, -71.90899658]

lat = [17.94124222, 17.96657181, 17.99184036, 18.01698875, 18.04202652,

18.04202652, 18.01698875, 17.99184036, 17.96657181, 17.94124222]

binx = lon

biny = lat

ret = stats.binned_statistic_2d(x, y, None, 'count', bins=[binx,biny])

Error:

ValueError: bins must be monotonically increasing or decreasing

How to deal with this issue?

My solution

Use zip to get boundaries of every grid;

Add condition to make sure the order is correct

for row in np.arange(lon_b.shape[0]-1):

k = 0

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,:]),iter(lat_b[row,:])]*2):

    # Because binned_statistic_2d need bin_* increase monotonically

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic



        k += 2



k = 1

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,1:]),iter(lat_b[row,1:])]*2):

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic                    

    k += 2

edited Nov 23 '18 at 12:07

asked Nov 22 '18 at 3:11

Xin Zhang

64211

I'm using Lambert projection which means if longitude is monotonic then latitude is non-monotonic.

It's difficult to using binned_statistic_2d like this:

from scipy import stats

x = [-118,-117.8,-117.7,-80,-70]

y = [18.1,18,18,17.8,18]

lon = [-118.09100342, -117.987854, -117.88466644, -117.78141785, -117.67811584, -72.32189178, -72.21858215, -72.11533356, -72.012146, -71.90899658]

lat = [17.94124222, 17.96657181, 17.99184036, 18.01698875, 18.04202652,

18.04202652, 18.01698875, 17.99184036, 17.96657181, 17.94124222]

binx = lon

biny = lat

ret = stats.binned_statistic_2d(x, y, None, 'count', bins=[binx,biny])

Error:

ValueError: bins must be monotonically increasing or decreasing

How to deal with this issue?

My solution

Use zip to get boundaries of every grid;

Add condition to make sure the order is correct

for row in np.arange(lon_b.shape[0]-1):

k = 0

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,:]),iter(lat_b[row,:])]*2):

    # Because binned_statistic_2d need bin_* increase monotonically

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic



        k += 2



k = 1

for lon_1,lat_1,lon_2,lat_2 in zip(*[iter(lon_b[row,1:]),iter(lat_b[row,1:])]*2):

    if lat_1 < lat_2:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_1,lat_2],[lon_1,lon_2]]).statistic

    else:

        CG_bin[row,k] = stats.binned_statistic_2d(lon_CG, lat_CG, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic

        IC_bin[row,k] = stats.binned_statistic_2d(lon_IC, lat_IC, None, 

                'count', bins=[[lat_2,lat_1],[lon_1,lon_2]]).statistic                    

    k += 2

python scipy interpolation histogram2d

edited Nov 23 '18 at 12:07

asked Nov 22 '18 at 3:11

Xin Zhang

64211

edited Nov 23 '18 at 12:07

asked Nov 22 '18 at 3:11

Xin Zhang

64211

edited Nov 23 '18 at 12:07

asked Nov 22 '18 at 3:11

Xin Zhang

64211

asked Nov 22 '18 at 3:11

Xin Zhang

64211

asked Nov 22 '18 at 3:11

Xin Zhang

64211

add a comment |

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How to use binned_statistic_2d with Non-monotonic boundary?

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