Downsampling the number of entries in a list (without interpolation)

I have a Python list with a number of entries, which I need to downsample using either:

• A maximum number of rows. For example, limiting a list of 1234 entries to 1000.
• A proportion of the original rows. For example, making the list 1/3 its original length.

(I need to be able to do both ways, but only one is used at a time).

I believe that for the maximum number of rows I can just calculate the proportion needed and pass that to the proportional downsizer:

def downsample_to_max(self, rows, max_rows):
        return downsample_to_proportion开发者_JS百科(rows, max_rows / float(len(rows)))

...so I really only need one downsampling function. Any hints, please?

EDIT: The list contains objects, not numeric values so I do not need to interpolate. Dropping objects is fine.

SOLUTION:

def downsample_to_proportion(self, rows, proportion):

    counter = 0.0
    last_counter = None
    results = []

    for row in rows:

        counter += proportion

        if int(counter) != last_counter:
            results.append(row)
            last_counter = int(counter)

    return results

Thanks.

You can use islice from itertools:

from itertools import islice

def downsample_to_proportion(rows, proportion=1):
    return list(islice(rows, 0, len(rows), int(1/proportion)))

Usage:

x = range(1,10)
print downsample_to_proportion(x, 0.3)
# [1, 4, 7]

Instead of islice() + list() it is more efficient to use slice syntax directly if the input is already a sequence type:

def downsample_to_proportion(rows, proportion):
    return rows[::int(1 / proportion)]

This solution might be a bit overkill for the original poster, but I thought I would share the code that I've been using to solve this and similar problems.

It's a bit lengthy (about 90 lines), but if you often have this need, want an easy-to-use oneliner, and need a pure-Python dependency free environment then I reckon it might be of use.

Basically, the only thing you have to do is pass your list to the function and tell it what length you want your new list to be, and the function will either:

• downsize your list by dropping items if the new length is smaller, much like the previous answers already suggested.
• stretch/upscale your list (the opposite of downsizing) if the new length is larger, with the added option that you can decide whether to:
  • linearly interpolate bw the known values (automatically chosen if list contains ints or floats)
  • duplicate each value so they occupy a proportional size of the new list (automatically chosen if the list contains non-numbers)
  • pull the original values apart and leave gaps in between

Everything is collected inside one function so if you need it just copy and paste it to your script and you can start using it right away.

For instance you might say:

origlist = [0,None,None,30,None,50,60,70,None,None,100]
resizedlist = ResizeList(testlist, 21)
print(resizedlist)

and get

[0, 5.00000000001, 9.9999999999900009, 15.0, 20.000000000010001, 24.999999999989999, 30, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0, 70, 75.000000000010004, 79.999999999989996, 85.0, 90.000000000010004, 94.999999999989996, 100]

Note that minor inaccuracies will occur due to floating point limitations. Also, I wrote this for Python 2.x, so to use it on Python 3.x just add a single line that says xrange = range.

And here is a nifty trick to interpolate between positioned subitems in a list of lists. So for instance you can easily interpolate between RGB color tuples to create a color gradient of x nr of steps. Assuming a list of RGB color tuples of 3 and a desired GRADIENTLENGTH variable you do this with:

crosssections = zip(*rgbtuples)
grad_crosssections = ( ResizeList(spectrum,GRADIENTLENGTH) for spectrum in crosssections )
rgb_gradient = [list(each) for each in zip(*grad_crosssections)]

It probably could need quite a few optimizations, I had to do quite a bit of experimentation. If you feel you can improve it feel free to edit my post. Here is the code:

def ResizeList(rows, newlength, stretchmethod="not specified", gapvalue=None):
    """
    Resizes (up or down) and returns a new list of a given size, based on an input list.
    - rows: the input list, which can contain any type of value or item (except if using the interpolate stretchmethod which requires floats or ints only)
    - newlength: the new length of the output list (if this is the same as the input list then the original list will be returned immediately)
    - stretchmethod: if the list is being stretched, this decides how to do it. Valid values are:
      - 'interpolate'
        - linearly interpolate between the known values (automatically chosen if list contains ints or floats)
      - 'duplicate'
        - duplicate each value so they occupy a proportional size of the new list (automatically chosen if the list contains non-numbers)
      - 'spread'
        - drags the original values apart and leaves gaps as defined by the gapvalue option
    - gapvalue: a value that will be used as gaps to fill in between the original values when using the 'spread' stretchmethod
    """
    #return input as is if no difference in length
    if newlength == len(rows):
        return rows
    #set auto stretchmode
    if stretchmethod == "not specified":
        if isinstance(rows[0], (int,float)):
            stretchmethod = "interpolate"
        else:
            stretchmethod = "duplicate"
    #reduce newlength 
    newlength -= 1
    #assign first value
    outlist = [rows[0]]
    writinggapsflag = False
    if rows[1] == gapvalue:
        writinggapsflag = True
    relspreadindexgen = (index/float(len(rows)-1) for index in xrange(1,len(rows))) #warning a little hacky by skipping first index cus is assigned auto
    relspreadindex = next(relspreadindexgen)
    spreadflag = False
    gapcount = 0
    for outlistindex in xrange(1, newlength):
        #relative positions
        rel = outlistindex/float(newlength)
        relindex = (len(rows)-1) * rel
        basenr,decimals = str(relindex).split(".")
        relbwindex = float("0."+decimals)
        #determine equivalent value
        if stretchmethod=="interpolate":
            #test for gap
            maybecurrelval = rows[int(relindex)]
            maybenextrelval = rows[int(relindex)+1]
            if maybecurrelval == gapvalue:
                #found gapvalue, so skipping and waiting for valid value to interpolate and add to outlist
                gapcount += 1
                continue
            #test whether to interpolate for previous gaps
            if gapcount > 0:
                #found a valid value after skipping gapvalues so this is where it interpolates all of them from last valid value to this one
                startvalue = outlist[-1]
                endindex = int(relindex)
                endvalue = rows[endindex]
                gapstointerpolate = gapcount 
                allinterpolatedgaps = Resize([startvalue,endvalue],gapstointerpolate+3)
                outlist.extend(allinterpolatedgaps[1:-1])
                gapcount = 0
                writinggapsflag = False
            #interpolate value
            currelval = rows[int(relindex)]
            lookahead = 1
            nextrelval = rows[int(relindex)+lookahead]
            if nextrelval == gapvalue:
                if writinggapsflag:
                    continue
                relbwval = currelval
                writinggapsflag = True
            else:
                relbwval = currelval + (nextrelval - currelval) * relbwindex #basenr pluss interindex percent interpolation of diff to next item
        elif stretchmethod=="duplicate":
            relbwval = rows[int(round(relindex))] #no interpolation possible, so just copy each time
        elif stretchmethod=="spread":
            if rel >= relspreadindex:
                spreadindex = int(len(rows)*relspreadindex)
                relbwval = rows[spreadindex] #spread values further apart so as to leave gaps in between
                relspreadindex = next(relspreadindexgen)
            else:
                relbwval = gapvalue
        #assign each value
        outlist.append(relbwval)
    #assign last value
    if gapcount > 0:
        #this last value also has to interpolate for previous gaps       
        startvalue = outlist[-1]
        endvalue = rows[-1]
        gapstointerpolate = gapcount 
        allinterpolatedgaps = Resize([startvalue,endvalue],gapstointerpolate+3)
        outlist.extend(allinterpolatedgaps[1:-1])
        outlist.append(rows[-1])
        gapcount = 0
        writinggapsflag = False
    else:
        outlist.append(rows[-1])
    return outlist

Keep a counter, which you increment by the second value. Floor it each time, and yield the value at that index.

Can't random.choices() solve your problem? More examples are available here

With reference to answer from Ignacio Vazquez-Abrams:

Print 3 numbers from the 7 available:

msg_cache = [1, 2, 3, 4, 5, 6]
msg_n = 3
inc = len(msg_cache) / msg_n
inc_total = 0
for _ in range(0, msg_n):
    msg_downsampled = msg_cache[math.floor(inc_total)]
    print(msg_downsampled)
    inc_total += inc

Output:

0
2
4

Useful for down-sampling many log messages to a smaller subset.