matplotlib polar streamplot vs quiver












0














I try to plot streamline then I see wrong result.
I check streamline with quiver then I get right result.
I use same data for both. Why plots is so different?



fig = plt.figure()
axs = plt.axes(polar=True)
axs.set_theta_zero_location("N")
axs.set_theta_direction(-1)
YL, ZL = zip(*list(zip(YLr,ZLr))/np.linalg.norm(list(zip(YLr,ZLr)),axis=1, keepdims=True))
YLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),YL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
ZLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),ZL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
r = izogn_i
phi = a_izogn_rad_i
r, phi = np.meshgrid(r, phi)
axs.streamplot(phi.transpose(), r.transpose(),ZLi, YLi, color='red',density=1, linewidth=0.5)
axs.quiver(phi.transpose(), r.transpose(), ZLi, YLi,units='xy',scale=10., zorder=3, color='blue',width=0.007, headwidth=3., headlength=4.)
axs.set_ylim([min(izogn_i), max(izogn_i)])
fig.show();


Sample plot



my data:
https://cloud.mail.ru/public/HzJX/YFc1cLGGR










share|improve this question



























    0














    I try to plot streamline then I see wrong result.
    I check streamline with quiver then I get right result.
    I use same data for both. Why plots is so different?



    fig = plt.figure()
    axs = plt.axes(polar=True)
    axs.set_theta_zero_location("N")
    axs.set_theta_direction(-1)
    YL, ZL = zip(*list(zip(YLr,ZLr))/np.linalg.norm(list(zip(YLr,ZLr)),axis=1, keepdims=True))
    YLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),YL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
    ZLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),ZL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
    r = izogn_i
    phi = a_izogn_rad_i
    r, phi = np.meshgrid(r, phi)
    axs.streamplot(phi.transpose(), r.transpose(),ZLi, YLi, color='red',density=1, linewidth=0.5)
    axs.quiver(phi.transpose(), r.transpose(), ZLi, YLi,units='xy',scale=10., zorder=3, color='blue',width=0.007, headwidth=3., headlength=4.)
    axs.set_ylim([min(izogn_i), max(izogn_i)])
    fig.show();


    Sample plot



    my data:
    https://cloud.mail.ru/public/HzJX/YFc1cLGGR










    share|improve this question

























      0












      0








      0







      I try to plot streamline then I see wrong result.
      I check streamline with quiver then I get right result.
      I use same data for both. Why plots is so different?



      fig = plt.figure()
      axs = plt.axes(polar=True)
      axs.set_theta_zero_location("N")
      axs.set_theta_direction(-1)
      YL, ZL = zip(*list(zip(YLr,ZLr))/np.linalg.norm(list(zip(YLr,ZLr)),axis=1, keepdims=True))
      YLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),YL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
      ZLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),ZL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
      r = izogn_i
      phi = a_izogn_rad_i
      r, phi = np.meshgrid(r, phi)
      axs.streamplot(phi.transpose(), r.transpose(),ZLi, YLi, color='red',density=1, linewidth=0.5)
      axs.quiver(phi.transpose(), r.transpose(), ZLi, YLi,units='xy',scale=10., zorder=3, color='blue',width=0.007, headwidth=3., headlength=4.)
      axs.set_ylim([min(izogn_i), max(izogn_i)])
      fig.show();


      Sample plot



      my data:
      https://cloud.mail.ru/public/HzJX/YFc1cLGGR










      share|improve this question













      I try to plot streamline then I see wrong result.
      I check streamline with quiver then I get right result.
      I use same data for both. Why plots is so different?



      fig = plt.figure()
      axs = plt.axes(polar=True)
      axs.set_theta_zero_location("N")
      axs.set_theta_direction(-1)
      YL, ZL = zip(*list(zip(YLr,ZLr))/np.linalg.norm(list(zip(YLr,ZLr)),axis=1, keepdims=True))
      YLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),YL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
      ZLi = scipy.interpolate.griddata(((np.radians(a_izogn), izogn)),ZL,(a_izogn_rad_i[None,:], izogn_i[:,None]),method='cubic')
      r = izogn_i
      phi = a_izogn_rad_i
      r, phi = np.meshgrid(r, phi)
      axs.streamplot(phi.transpose(), r.transpose(),ZLi, YLi, color='red',density=1, linewidth=0.5)
      axs.quiver(phi.transpose(), r.transpose(), ZLi, YLi,units='xy',scale=10., zorder=3, color='blue',width=0.007, headwidth=3., headlength=4.)
      axs.set_ylim([min(izogn_i), max(izogn_i)])
      fig.show();


      Sample plot



      my data:
      https://cloud.mail.ru/public/HzJX/YFc1cLGGR







      python matplotlib






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      asked Nov 13 at 21:03









      Alexey

      204




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          0














          solved. just plot contour in polar, streamline in cartesian






          share|improve this answer





























            0














            plot contour in polar, streamline in cartesian.
            in result you can see:



            enter image description here






            share|improve this answer





















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              2 Answers
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              active

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              2 Answers
              2






              active

              oldest

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              active

              oldest

              votes






              active

              oldest

              votes









              0














              solved. just plot contour in polar, streamline in cartesian






              share|improve this answer


























                0














                solved. just plot contour in polar, streamline in cartesian






                share|improve this answer
























                  0












                  0








                  0






                  solved. just plot contour in polar, streamline in cartesian






                  share|improve this answer












                  solved. just plot contour in polar, streamline in cartesian







                  share|improve this answer












                  share|improve this answer



                  share|improve this answer










                  answered Nov 18 at 20:26









                  Alexey

                  204




                  204

























                      0














                      plot contour in polar, streamline in cartesian.
                      in result you can see:



                      enter image description here






                      share|improve this answer


























                        0














                        plot contour in polar, streamline in cartesian.
                        in result you can see:



                        enter image description here






                        share|improve this answer
























                          0












                          0








                          0






                          plot contour in polar, streamline in cartesian.
                          in result you can see:



                          enter image description here






                          share|improve this answer












                          plot contour in polar, streamline in cartesian.
                          in result you can see:



                          enter image description here







                          share|improve this answer












                          share|improve this answer



                          share|improve this answer










                          answered Nov 20 at 19:35









                          Alexey

                          204




                          204






























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