From: John Hunter <jdh2358@gm...>  20101004 20:40:27

On Mon, Oct 4, 2010 at 3:37 PM, Tony S Yu <tsyu80@...> wrote: > Thanks! I'll give both imshow and pcolor a try. Most likely I'll use pcolor, since lighter bins would completely disappear without faceting (... or maybe that's a good thing). The barcode demo shows something similar with a binary color map for imshow http://matplotlib.sourceforge.net/examples/pylab_examples/barcode_demo.html JDH 
From: Tony S Yu <tsyu80@gm...>  20101001 01:45:00

I'd like to make something in between a box plot [1] and a histogram. Each histogram would be represented by a single, tall, rectangular patch (like the box in a box plot), and the patch would be subdivided by the bin edges of the histogram. The face color of each subpatch would replace the bar height in the histogram. If any of that actually made sense: * Does this type of plot have a name? * Is there an easy way to do this in Matplotlib? * If there isn't an easy way, what would be a good starting point? Initial ideas: 1) Use pcolor or imshow and embed this axes in a larger axes, 2) represent the subpatches as a PolyCollection. Thoughts? Tony [1] e.g. http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo.html 
From: Benjamin Root <ben.root@ou...>  20101001 13:41:02
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On Thu, Sep 30, 2010 at 8:44 PM, Tony S Yu <tsyu80@...> wrote: > I'd like to make something in between a box plot [1] and a histogram. Each > histogram would be represented by a single, tall, rectangular patch (like > the box in a box plot), and the patch would be subdivided by the bin edges > of the histogram. The face color of each subpatch would replace the bar > height in the histogram. > > If any of that actually made sense: > > * Does this type of plot have a name? > > * Is there an easy way to do this in Matplotlib? > > * If there isn't an easy way, what would be a good starting point? Initial > ideas: 1) Use pcolor or imshow and embed this axes in a larger axes, 2) > represent the subpatches as a PolyCollection. > > Thoughts? > Tony > > [1] e.g. > http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo.html > Tony, I am not quite sure I understand. Are you looking for error bars on the histogram, maybe? http://matplotlib.sourceforge.net/users/screenshots.html#barcharts Or maybe something more like this: http://matplotlib.sourceforge.net/examples/pylab_examples/bar_stacked.html Or maybe something else in the gallery is more like what you want: http://matplotlib.sourceforge.net/gallery.html Ben Root 
From: Tony S Yu <tsyu80@gm...>  20101001 14:47:53
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On Oct 1, 2010, at 9:40 AM, Benjamin Root wrote: > On Thu, Sep 30, 2010 at 8:44 PM, Tony S Yu <tsyu80@...> wrote: > I'd like to make something in between a box plot [1] and a histogram. Each histogram would be represented by a single, tall, rectangular patch (like the box in a box plot), and the patch would be subdivided by the bin edges of the histogram. The face color of each subpatch would replace the bar height in the histogram. > > If any of that actually made sense: > > * Does this type of plot have a name? > > * Is there an easy way to do this in Matplotlib? > > * If there isn't an easy way, what would be a good starting point? Initial ideas: 1) Use pcolor or imshow and embed this axes in a larger axes, 2) represent the subpatches as a PolyCollection. > > Thoughts? > Tony > > [1] e.g. http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo.html > > Tony, > > I am not quite sure I understand. [snip] > Or maybe something else in the gallery is more like what you want: > > http://matplotlib.sourceforge.net/gallery.html > > Ben Root > I've checked the gallery, but I don't see anything that appears similar. In any case, I ended up hacking together something that works. I've attached an image of what I had in mind (created with the code at the very bottom of this reply). I ended up using mpl Rectangle objects and stringing them together using a PatchCollection. Maybe there's a more efficient way to do this, but this approach worked wellenough. Best, Tony """ First attempt at a histogram strip chart (made up name). ifmain block taken from [1] except that I've replaced uniform distributions with normal distributions. [1] http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo3.html """ import numpy as np import matplotlib.pyplot as plt from matplotlib import collections NORM_TYPES = dict(max=max, sum=sum) class BinCollection(collections.PatchCollection): def __init__(self, hist, bin_edges, x=0, width=1, cmap=plt.cm.gray_r, norm_type='max', **kwargs): yy = (bin_edges[:1] + bin_edges[1:])/2. heights = np.diff(bin_edges) bins = [plt.Rectangle((x, y), width, h) for y, h in zip(yy, heights)] norm = NORM_TYPES[norm_type] fc = cmap(np.asarray(hist, dtype=float)/norm(hist)) super(BinCollection, self).__init__(bins, facecolors=fc, **kwargs) def histstrip(x, positions=None, widths=None, ax=None): if ax is None: ax = plt.gca() if positions is None: positions = range(1, len(x) + 1) if widths is None: widths = np.min(np.diff(positions)) / 2. * np.ones(len(positions)) for data, x_pos, w in zip(x, positions, widths): x_pos = w/2. hist, bin_edges = np.histogram(data) bins = BinCollection(hist, bin_edges, width=w, x=x_pos) ax.add_collection(bins, autolim=True) ax.set_xticks(positions) ax.autoscale_view() if __name__ == '__main__': import matplotlib.pyplot as plt import numpy as np np.random.seed(2) inc = 0.1 e1 = np.random.normal(0,1, size=(500,)) e2 = np.random.normal(0,1, size=(500,)) e3 = np.random.normal(0,1 + inc, size=(500,)) e4 = np.random.normal(0,1 + 2*inc, size=(500,)) treatments = [e1,e2,e3,e4] fig, ax = plt.subplots() pos = np.array(range(len(treatments)))+1 histstrip(treatments, ax=ax) ax.set_xlabel('treatment') ax.set_ylabel('response') fig.subplots_adjust(right=0.99,top=0.99) plt.show() 
From: Benjamin Root <ben.root@ou...>  20101003 16:12:54
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On Fri, Oct 1, 2010 at 9:47 AM, Tony S Yu <tsyu80@...> wrote: > > On Oct 1, 2010, at 9:40 AM, Benjamin Root wrote: > > On Thu, Sep 30, 2010 at 8:44 PM, Tony S Yu <tsyu80@...> wrote: > >> I'd like to make something in between a box plot [1] and a histogram. Each >> histogram would be represented by a single, tall, rectangular patch (like >> the box in a box plot), and the patch would be subdivided by the bin edges >> of the histogram. The face color of each subpatch would replace the bar >> height in the histogram. >> >> If any of that actually made sense: >> >> * Does this type of plot have a name? >> >> * Is there an easy way to do this in Matplotlib? >> >> * If there isn't an easy way, what would be a good starting point? Initial >> ideas: 1) Use pcolor or imshow and embed this axes in a larger axes, 2) >> represent the subpatches as a PolyCollection. >> >> Thoughts? >> Tony >> >> [1] e.g. >> http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo.html >> > > Tony, > > I am not quite sure I understand. > > > [snip] > > Or maybe something else in the gallery is more like what you want: > > http://matplotlib.sourceforge.net/gallery.html > > Ben Root > > > I've checked the gallery, but I don't see anything that appears similar. In > any case, I ended up hacking together something that works. I've attached an > image of what I had in mind (created with the code at the very bottom of > this reply). > > I ended up using mpl Rectangle objects and stringing them together using a > PatchCollection. Maybe there's a more efficient way to do this, but this > approach worked wellenough. > > Best, > Tony > Actually, that looks kinda cool. If anyone is aware of the name for this kind of plot, maybe we could add a new plotting function? Ben Root 
From: Friedrich Romstedt <friedrichromstedt@gm...>  20101004 20:10:04

> """ > First attempt at a histogram strip chart (made up name). > ifmain block taken from [1] except that I've replaced uniform distributions > with normal distributions. > [1] http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo3.html > """ > import numpy as np > import matplotlib.pyplot as plt > from matplotlib import collections > > NORM_TYPES = dict(max=max, sum=sum) > class BinCollection(collections.PatchCollection): > def __init__(self, hist, bin_edges, x=0, width=1, cmap=plt.cm.gray_r, > norm_type='max', **kwargs): > yy = (bin_edges[:1] + bin_edges[1:])/2. > heights = np.diff(bin_edges) > bins = [plt.Rectangle((x, y), width, h) for y, h in zip(yy, heights)] > norm = NORM_TYPES[norm_type] > fc = cmap(np.asarray(hist, dtype=float)/norm(hist)) > super(BinCollection, self).__init__(bins, facecolors=fc, **kwargs) Is this equivalent to writing collections.PatchCollection.__init__() and what are the advantages of super()? I think you can use axes.pcolor() to replace BinCollection. pcolor() just adds a collection similar to what you do now by hand for you. With appropriate arguments it should do the job. You can also look into pcolorfast() and pcolormesh(). > def histstrip(x, positions=None, widths=None, ax=None): > if ax is None: > ax = plt.gca() > if positions is None: > positions = range(1, len(x) + 1) > if widths is None: > widths = np.min(np.diff(positions)) / 2. * np.ones(len(positions)) > for data, x_pos, w in zip(x, positions, widths): > x_pos = w/2. > hist, bin_edges = np.histogram(data) No other arguments to numpy.histogram() allowed? > bins = BinCollection(hist, bin_edges, width=w, x=x_pos) > ax.add_collection(bins, autolim=True) > ax.set_xticks(positions) > ax.autoscale_view() > if __name__ == '__main__': > import matplotlib.pyplot as plt > import numpy as np > np.random.seed(2) > inc = 0.1 > e1 = np.random.normal(0,1, size=(500,)) > e2 = np.random.normal(0,1, size=(500,)) > e3 = np.random.normal(0,1 + inc, size=(500,)) > e4 = np.random.normal(0,1 + 2*inc, size=(500,)) > treatments = [e1,e2,e3,e4] > fig, ax = plt.subplots() > pos = np.array(range(len(treatments)))+1 > histstrip(treatments, ax=ax) > ax.set_xlabel('treatment') > ax.set_ylabel('response') > fig.subplots_adjust(right=0.99,top=0.99) > plt.show() In my opinion this is too special to be added as a general matplotlib plotting feature. Friedrich 
From: Tony S Yu <tsyu80@gm...>  20101004 20:35:05

On Oct 4, 2010, at 4:09 PM, Friedrich Romstedt wrote: >> """ >> First attempt at a histogram strip chart (made up name). >> ifmain block taken from [1] except that I've replaced uniform distributions >> with normal distributions. >> [1] http://matplotlib.sourceforge.net/examples/pylab_examples/boxplot_demo3.html >> """ >> import numpy as np >> import matplotlib.pyplot as plt >> from matplotlib import collections >> >> NORM_TYPES = dict(max=max, sum=sum) >> class BinCollection(collections.PatchCollection): >> def __init__(self, hist, bin_edges, x=0, width=1, cmap=plt.cm.gray_r, >> norm_type='max', **kwargs): >> yy = (bin_edges[:1] + bin_edges[1:])/2. >> heights = np.diff(bin_edges) >> bins = [plt.Rectangle((x, y), width, h) for y, h in zip(yy, heights)] >> norm = NORM_TYPES[norm_type] >> fc = cmap(np.asarray(hist, dtype=float)/norm(hist)) > >> super(BinCollection, self).__init__(bins, facecolors=fc, **kwargs) > > Is this equivalent to writing collections.PatchCollection.__init__() > and what are the advantages of super()? I believe collections.PatchCollection.__init__() is equivalent. In this instance, I don't think there are advantages (or disadvantages) to using superit's just how I'm used to writing classes. > I think you can use axes.pcolor() to replace BinCollection. pcolor() > just adds a collection similar to what you do now by hand for you. > With appropriate arguments it should do the job. You can also look > into pcolorfast() and pcolormesh(). Yes, you're right. This was actually my main question in the original post; i.e. what plotting function to start with. I'm not really sure how I overlooked pcolor(mesh) as a viable option. Thanks. > >> def histstrip(x, positions=None, widths=None, ax=None): >> if ax is None: >> ax = plt.gca() >> if positions is None: >> positions = range(1, len(x) + 1) >> if widths is None: >> widths = np.min(np.diff(positions)) / 2. * np.ones(len(positions)) >> for data, x_pos, w in zip(x, positions, widths): >> x_pos = w/2. >> hist, bin_edges = np.histogram(data) > > No other arguments to numpy.histogram() allowed? As I mentioned, this was just a function I hacked together. I didn't try to make it general purpose (yet). > > In my opinion this is too special to be added as a general matplotlib > plotting feature. I'd agree that it's pretty specialized; especially since I haven't been able to find any mention of it. I'm still curious if there's a name for this type of plot if anyone out there knows. Best, Tony > > Friedrich 
From: John Hunter <jdh2358@gm...>  20101004 20:30:39

On Thu, Sep 30, 2010 at 8:44 PM, Tony S Yu <tsyu80@...> wrote: > I'd like to make something in between a box plot [1] and a histogram. Each histogram would be represented by a single, tall, rectangular patch (like the box in a box plot), and the patch would be subdivided by the bin edges of the histogram. The face color of each subpatch would replace the bar height in the histogram. > > If any of that actually made sense: > > * Does this type of plot have a name? > > * Is there an easy way to do this in Matplotlib? > > * If there isn't an easy way, what would be a good starting point? Initial ideas: 1) Use pcolor or imshow and embed this axes in a larger axes, 2) represent the subpatches as a PolyCollection. If you don't need faceting (dark edges around the bins), imshow with the extent set would be the easiest way. If you want faceting, pcolor should work as well. 
From: Tony S Yu <tsyu80@gm...>  20101004 20:37:42

On Oct 4, 2010, at 4:30 PM, John Hunter wrote: > On Thu, Sep 30, 2010 at 8:44 PM, Tony S Yu <tsyu80@...> wrote: >> I'd like to make something in between a box plot [1] and a histogram. Each histogram would be represented by a single, tall, rectangular patch (like the box in a box plot), and the patch would be subdivided by the bin edges of the histogram. The face color of each subpatch would replace the bar height in the histogram. >> >> If any of that actually made sense: >> >> * Does this type of plot have a name? >> >> * Is there an easy way to do this in Matplotlib? >> >> * If there isn't an easy way, what would be a good starting point? Initial ideas: 1) Use pcolor or imshow and embed this axes in a larger axes, 2) represent the subpatches as a PolyCollection. > > If you don't need faceting (dark edges around the bins), imshow with > the extent set would be the easiest way. If you want faceting, pcolor > should work as well. Thanks! I'll give both imshow and pcolor a try. Most likely I'll use pcolor, since lighter bins would completely disappear without faceting (... or maybe that's a good thing). Tony 
From: John Hunter <jdh2358@gm...>  20101004 20:40:27

On Mon, Oct 4, 2010 at 3:37 PM, Tony S Yu <tsyu80@...> wrote: > Thanks! I'll give both imshow and pcolor a try. Most likely I'll use pcolor, since lighter bins would completely disappear without faceting (... or maybe that's a good thing). The barcode demo shows something similar with a binary color map for imshow http://matplotlib.sourceforge.net/examples/pylab_examples/barcode_demo.html JDH 