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imshow() pixelization in matplotlib 2.0.2 but not in 2.0.0 #8723

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imshow() pixelization in matplotlib 2.0.2 but not in 2.0.0#8723

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Release criticalFor bugs that make the library unusable (segfaults, incorrect plots, etc) and major regressions.For bugs that make the library unusable (segfaults, incorrect plots, etc) and major regressions.status: duplicate

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v2.1

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diogoff

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on Jun 6, 2017

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I'm plotting the same image (a numpy float32 array) with imshow(..., interpolation='bilinear') on matplotlib 2.0.0 and 2.0.2.

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On 2.0.0 the image is perfectly smooth. However, on 2.0.2 there are noticeable pixelization effects.

Has imshow() changed between these two versions?

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WeatherGod commented on Jun 6, 2017
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There have been some bugfixes, IIRC, mostly related to the handling of NaNs and masked points. Are there any in your data?
…

On Tue, Jun 6, 2017 at 10:54 AM, diogoff ***@***.***> wrote: I'm plotting the same image (a numpy float32 array) with imshow(..., interpolation='bilinear') on matplotlib 2.0.0 and 2.0.2. See the following figure: [image: matplotlib] <https://cloud.githubusercontent.com/assets/7391155/26835386/20980584-4ad0-11e7-8719-83beec5126d5.png> On 2.0.0 the image is perfectly smooth. However, on 2.0.2 there are noticeable pixelization effects. Has the imshow() routine changed? — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#8723>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AARy-PvqiPeroQYvc-abNuKTIJk7LZINks5sBWhDgaJpZM4Nxdr0> .
WeatherGod commented on Jun 6, 2017
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Another possible source of issues *might* be colormap handling. It would be helpful to have a minimum working example to investigate with.
…

On Tue, Jun 6, 2017 at 11:23 AM, Benjamin Root ***@***.***> wrote: There have been some bugfixes, IIRC, mostly related to the handling of NaNs and masked points. Are there any in your data? On Tue, Jun 6, 2017 at 10:54 AM, diogoff ***@***.***> wrote: > I'm plotting the same image (a numpy float32 array) with imshow(..., > interpolation='bilinear') on matplotlib 2.0.0 and 2.0.2. > > See the following figure: > [image: matplotlib] > <https://cloud.githubusercontent.com/assets/7391155/26835386/20980584-4ad0-11e7-8719-83beec5126d5.png> > > On 2.0.0 the image is perfectly smooth. However, on 2.0.2 there are > noticeable pixelization effects. > > Has the imshow() routine changed? > > — > You are receiving this because you are subscribed to this thread. > Reply to this email directly, view it on GitHub > <#8723>, or mute the > thread > <https://github.com/notifications/unsubscribe-auth/AARy-PvqiPeroQYvc-abNuKTIJk7LZINks5sBWhDgaJpZM4Nxdr0> > . >

Reacted by Paul Hobson

diogoff commented on Jun 6, 2017

diogoff

on Jun 6, 2017

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Here is a MWE:

import matplotlib.pyplot as plt

data = [[ 0.001071,  0.032820,  0.105207,  0.127595,  0.147364,  0.124911,  0.073015,  0.000074, -0.003899, -0.001462],
        [ 0.000787,  0.031720,  0.107091,  0.183722,  0.202479,  0.204296,  0.154234,  0.085757,  0.026941, -0.003271],
        [ 0.001480, -0.000771,  0.016654,  0.214761,  0.278136,  0.304099,  0.246056,  0.169364,  0.085205, -0.001907],
        [ 0.000549, -0.000475,  0.001674,  0.247847,  0.345098,  0.378256,  0.332674,  0.229220,  0.133641,  0.053745],
        [ 0.000000,  0.002675,  0.001689,  0.266309,  0.414319,  0.459767,  0.425990,  0.317280,  0.190170,  0.099265],
        [ 0.000000,  0.001037, -0.002923,  0.254976,  0.408347,  0.529809,  0.532195,  0.406330,  0.272445,  0.163764],
        [ 0.000000,  0.000792, -0.013151,  0.216619,  0.397671,  0.567617,  0.616055,  0.508699,  0.379961,  0.263546],
        [ 0.000000,  0.002062, -0.016293,  0.157240,  0.368229,  0.613702,  0.712611,  0.639131,  0.505910,  0.338813],
        [ 0.000000,  0.001741,  0.003448,  0.100818,  0.333026,  0.611874,  0.787059,  0.773407,  0.644049,  0.450520],
        [ 0.000000, -0.001268, -0.008104,  0.061512,  0.294558,  0.604565,  0.814691,  0.865676,  0.776763,  0.557480],
        [ 0.000000, -0.001105, -0.002768,  0.036252,  0.252868,  0.544436,  0.775150,  0.920004,  0.890915,  0.690601],
        [ 0.000000, -0.001123, -0.003589,  0.028705,  0.194056,  0.471003,  0.728520,  0.921639,  0.969436,  0.773769],
        [ 0.000000, -0.000430, -0.004625,  0.017730,  0.149156,  0.423797,  0.677714,  0.912435,  0.984722,  0.846838],
        [ 0.000000,  0.000000, -0.002619,  0.036928,  0.136544,  0.410567,  0.666038,  0.905706,  0.942078,  0.894590],
        [ 0.000000, -0.000296, -0.003399,  0.050115,  0.189001,  0.451915,  0.696602,  0.869335,  0.893818,  0.826647],
        [ 0.000000,  0.000174, -0.003604,  0.083219,  0.248855,  0.517874,  0.739961,  0.843343,  0.803800,  0.718687],
        [-0.001720,  0.005825,  0.078039,  0.154466,  0.324385,  0.550980,  0.745479,  0.817428,  0.750877,  0.624806],
        [ 0.000719, -0.004020,  0.118178,  0.218264,  0.395383,  0.585784,  0.748400,  0.744401,  0.620376,  0.464464],
        [ 0.003257,  0.066374,  0.142013,  0.270861,  0.458675,  0.621705,  0.691592,  0.590108,  0.491103,  0.346859],
        [ 0.042411,  0.111464,  0.193880,  0.308119,  0.475352,  0.602842,  0.600717,  0.487950,  0.392807,  0.258806]]

plt.imshow(data, vmin=0., vmax=1., interpolation='bilinear')
plt.axis('off')
plt.show()

WeatherGod commented on Jun 6, 2017
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It is almost like it is treating those zeros as masked out, isn't it? attn: @tacaswell
…

On Tue, Jun 6, 2017 at 5:08 PM, diogoff ***@***.***> wrote: Here is a MWE: import matplotlib.pyplot as plt data = [[ 0.001071, 0.032820, 0.105207, 0.127595, 0.147364, 0.124911, 0.073015, 0.000074, -0.003899, -0.001462], [ 0.000787, 0.031720, 0.107091, 0.183722, 0.202479, 0.204296, 0.154234, 0.085757, 0.026941, -0.003271], [ 0.001480, -0.000771, 0.016654, 0.214761, 0.278136, 0.304099, 0.246056, 0.169364, 0.085205, -0.001907], [ 0.000549, -0.000475, 0.001674, 0.247847, 0.345098, 0.378256, 0.332674, 0.229220, 0.133641, 0.053745], [ 0.000000, 0.002675, 0.001689, 0.266309, 0.414319, 0.459767, 0.425990, 0.317280, 0.190170, 0.099265], [ 0.000000, 0.001037, -0.002923, 0.254976, 0.408347, 0.529809, 0.532195, 0.406330, 0.272445, 0.163764], [ 0.000000, 0.000792, -0.013151, 0.216619, 0.397671, 0.567617, 0.616055, 0.508699, 0.379961, 0.263546], [ 0.000000, 0.002062, -0.016293, 0.157240, 0.368229, 0.613702, 0.712611, 0.639131, 0.505910, 0.338813], [ 0.000000, 0.001741, 0.003448, 0.100818, 0.333026, 0.611874, 0.787059, 0.773407, 0.644049, 0.450520], [ 0.000000, -0.001268, -0.008104, 0.061512, 0.294558, 0.604565, 0.814691, 0.865676, 0.776763, 0.557480], [ 0.000000, -0.001105, -0.002768, 0.036252, 0.252868, 0.544436, 0.775150, 0.920004, 0.890915, 0.690601], [ 0.000000, -0.001123, -0.003589, 0.028705, 0.194056, 0.471003, 0.728520, 0.921639, 0.969436, 0.773769], [ 0.000000, -0.000430, -0.004625, 0.017730, 0.149156, 0.423797, 0.677714, 0.912435, 0.984722, 0.846838], [ 0.000000, 0.000000, -0.002619, 0.036928, 0.136544, 0.410567, 0.666038, 0.905706, 0.942078, 0.894590], [ 0.000000, -0.000296, -0.003399, 0.050115, 0.189001, 0.451915, 0.696602, 0.869335, 0.893818, 0.826647], [ 0.000000, 0.000174, -0.003604, 0.083219, 0.248855, 0.517874, 0.739961, 0.843343, 0.803800, 0.718687], [-0.001720, 0.005825, 0.078039, 0.154466, 0.324385, 0.550980, 0.745479, 0.817428, 0.750877, 0.624806], [ 0.000719, -0.004020, 0.118178, 0.218264, 0.395383, 0.585784, 0.748400, 0.744401, 0.620376, 0.464464], [ 0.003257, 0.066374, 0.142013, 0.270861, 0.458675, 0.621705, 0.691592, 0.590108, 0.491103, 0.346859], [ 0.042411, 0.111464, 0.193880, 0.308119, 0.475352, 0.602842, 0.600717, 0.487950, 0.392807, 0.258806]] plt.imshow(data, vmin=0., vmax=1., interpolation='bilinear') plt.axis('off') plt.show() [image: matplotlib] <https://user-images.githubusercontent.com/7391155/26851969-802a9fb4-4b04-11e7-8d29-4d49e3df3c30.png> — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#8723 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AARy-Btlf7KfBsDWGii3gi5L-MELxm0Yks5sBb-zgaJpZM4Nxdr0> .
diogoff commented on Jun 6, 2017
diogoff
on Jun 6, 2017
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The pixelization appears around the negative values which are being clipped by vmin=0.
WeatherGod commented on Jun 6, 2017
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you are right. It is the pixels that fall below vmin. There was some recent work around vmin/vmax. maybe that had some unintended consequences?
…

On Tue, Jun 6, 2017 at 5:14 PM, diogoff ***@***.***> wrote: The pixelization appears around the negative values which are being clipped by vmin=0. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#8723 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AARy-D53Gn1CAvCdzYvawoSBkw6yQ4YQks5sBcElgaJpZM4Nxdr0> .
diogoff commented on Jun 6, 2017
diogoff
on Jun 6, 2017
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It seems that when those (negative) pixels are being clipped, the interpolation no longer works as it used to.
Thanks for your help.
WeatherGod commented on Jun 6, 2017
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Possible culprit: #8024
…

On Tue, Jun 6, 2017 at 5:22 PM, diogoff ***@***.***> wrote: It seems that when those (negative) pixels are being clipped, the interpolation no longer works as it used to. Thanks for your help. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#8723 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AARy-NkZqs3thlZAIm4n-tE0ITMSxu_Qks5sBcL-gaJpZM4Nxdr0> .
dstansby commented on Jun 15, 2017
dstansby
on Jun 15, 2017
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Yep, this bisects to 1a7c4ef
tacaswell commented on Jun 17, 2017
tacaswell
on Jun 17, 2017
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This is a duplicate of #8631 which has a proposed solution in the comments.
tacaswell
added this to the This milestone has been deleted milestone on Jun 17, 2017
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added
Release criticalFor bugs that make the library unusable (segfaults, incorrect plots, etc) and major regressions.For bugs that make the library unusable (segfaults, incorrect plots, etc) and major regressions.

status: duplicate
on Jun 17, 2017
tacaswell
self-assigned this
on Jul 25, 2017
tacaswell commented on Aug 31, 2017
tacaswell
on Aug 31, 2017
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Closed by #8966
tacaswell
closed this as completed on Aug 31, 2017

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imshow() pixelization in matplotlib 2.0.2 but not in 2.0.0 #8723

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WeatherGod commented on Jun 6, 2017

WeatherGod commented on Jun 6, 2017

diogoff commented on Jun 6, 2017

WeatherGod commented on Jun 6, 2017

diogoff commented on Jun 6, 2017

WeatherGod commented on Jun 6, 2017

diogoff commented on Jun 6, 2017

WeatherGod commented on Jun 6, 2017

dstansby commented on Jun 15, 2017

tacaswell commented on Jun 17, 2017

tacaswell commented on Aug 31, 2017

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