Plot smooth line with PyPlot

Question

I ve got the following simple script that plots a graph   import matplotlib pyplot as plt import numpy as np  T   np array  6  7  8  9  10  11  12   power   np array  1 53E 03  5 92E 02  2 04E 02  7 24E 01  2 72E 01  1 10E 01  4 70E 00    plt plot T power  plt show     As it is now  the line goes straight from point to point which looks ok  but could be better in my opinion  What I want is to smooth the line between the points  In Gnuplot I would have plotted with smooth cplines   Is there an easy way to do this in PyPlot  I ve found some tutorials  but they all seem rather complex

User · Answer

For this example spline works well  but if the function is not smooth inherently and you want to have smoothed version you can also try   from scipy ndimage filters import gaussian filter1d  ysmoothed   gaussian filter1d y  sigma 2  plt plot x  ysmoothed  plt show     if you increase sigma you can get a more smoothed function   Proceed with caution with this one  It modifies the original values and may not be what you want

User · Answer

Here is a simple solution for dates  from scipy interpolate import make interp spline import numpy as np import matplotlib pyplot as plt import matplotlib dates as dates from datetime import datetime  data         datetime 2016  9  26  0  0   26060  datetime 2016  9  27  0  0   23243      datetime 2016  9  28  0  0   22534  datetime 2016  9  29  0  0   22841      datetime 2016  9  30  0  0   22441  datetime 2016  10  1  0  0   23248     create data date np   np array list data keys     value np   np array list data values     date num   dates date2num date np    smooth date num smooth   np linspace date num min    date num max    100   spl   make interp spline date num  value np  k 3  value np smooth   spl date num smooth    print plt plot date np  value np  plt plot dates num2date date num smooth   value np smooth  plt show

User · Answer

See the scipy interpolate documentation for some examples      The following example demonstrates its use  for linear and cubic spline interpolation    gt  gt  gt  from scipy interpolate import interp1d   gt  gt  gt  x   np linspace 0  10  num 11  endpoint True   gt  gt  gt  y   np cos -x  2 9 0   gt  gt  gt  f   interp1d x  y   gt  gt  gt  f2   interp1d x  y  kind  cubic     gt  gt  gt  xnew   np linspace 0  10  num 41  endpoint True   gt  gt  gt  import matplotlib pyplot as plt  gt  gt  gt  plt plot x  y   o   xnew  f xnew    -   xnew  f2 xnew    --    gt  gt  gt  plt legend   data    linear    cubic    loc  best    gt  gt  gt  plt show

User · Answer

I presume you mean curve-fitting and not anti-aliasing from the context of your question   PyPlot doesn t have any built-in support for this  but you can easily implement some basic curve-fitting yourself  like the code seen here  or if you re using GuiQwt it has a curve fitting module    You could probably also steal the code from SciPy to do this as well

User · Answer

You could use scipy interpolate spline to smooth out your data yourself   from scipy interpolate import spline    300 represents number of points to make between T min and T max xnew   np linspace T min    T max    300     power smooth   spline T  power  xnew   plt plot xnew power smooth  plt show          spline is deprecated in scipy 0 19 0  use BSpline class instead    Switching from spline to BSpline isn t a straightforward copy paste and requires a little tweaking   from scipy interpolate import make interp spline  BSpline    300 represents number of points to make between T min and T max xnew   np linspace T min    T max    300    spl   make interp spline T  power  k 3     type  BSpline power smooth   spl xnew   plt plot xnew  power smooth  plt show       Before    After

[python] Plot smooth line with PyPlot

Examples related to python

Examples related to matplotlib

Examples related to plot

Examples related to smoothing