Hello all, I've been trying for days but I can't seem to get the
result I'm looking for. I have a 2d array of type "numpy.ndarray"
which I'd like to plot as a simple color map. I'd like to plot it in
the upper-lefthand corner of the client area in a wxPython frame. The
plotting needs to be a very simple 1:1 ratio, for example if the numpy
array has 400 rows and 500 columns, I would like to plot it so that it
assumes 400x500 pixels in the wxPython frame. I do not need axis ticks
and labels, just the colormap plot itself. I can get my figure to plot
(with tick marks and labels since I haven't figured out how to turn
those off) but I cannot size it properly. I've copied a tutorial
example I found and modify it and through tedious trial and error have
gotten half-way to where I need:
# First attempt to render data to a window:
import matplotlib
matplotlib.use('WXAgg')
from matplotlib import rcParams
import numpy
import matplotlib.cm as cm
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
#from matplotlib.figure import Figure
from wx import *
import DataFileTypes as DFT
class DataFrame(Frame):
def __init__(self):
Frame.__init__(self, None, -1, "Data filename here",
size=DisplaySize())
def displayData(self):
data = None
# Load data into "data" object using my custom IntData(...) class:
try:
data = DFT.INTData("C:\SAR Test files\Tibet2008.int")
except DFT.DataFileError:
print("Error opening data file")
except DFT.ResourceFileError:
print("Error opening resource file")
if data:
# Assume a screen dpi of 96...seems very flakey to me:
ScreenDPI = 96.0
# compute the width and height of figure using this dpi
# and the rows and columns of the data for a 1:1 display ratio:
FigureWidthInInches = (data.numcolumns / ScreenDPI)
FigureHeightInInches = (data.numrows / ScreenDPI)
print(FigureWidthInInches, FigureHeightInInches)
# Instantiate Figure based on these parameters:
self.fig =
matplotlib.figure.Figur((FigureWidthInInches,FigureHeightInInches),
dpi = ScreenDPI)
self.canvas = FigureCanvasWxAgg(self, -1, self.fig)
# Put everything into a sizer:
sizer = BoxSizer(VERTICAL)
#sizer.Add(self.canvas, 1, LEFT | TOP | GROW)
sizer.Add(self.canvas, 0, LEFT | TOP)
self.SetSizer(sizer)
# self.Fit()
a = self.fig.add_axes([0.075, 0.1, 0.75, 0.85])
self.im = a.imshow(data.getNumpyArray(),
interpolation=None, cmap = data.getCustomColorMap())
if __name__ == '__main__':
app = PySimpleApp()
frame = DataFrame()
frame.displayData()
frame.Show()
app.MainLoop()
It displays but the plot is inside the figure i.e. the colormap of the
data is within the figure that I've sized. matplotlib does this by
design, of course, but I cannot figure out how to defeat it. For one
thing, I don't think I'm sizing the figure correctly by setting
(guessing at) the dpi and computing the inches...just seems wrong, but
I can't find any tutorials or examples that show anything that sizes
figures using pixels or screen coords.
I always know the dimensions of my data a priori, so let's assume the
following very simple situation:
- I have a numpy.ndarray of data with 350 rows and 500 columns. How do
I display it in the upper-left hand corner of the frame client with no
tick marks/labels, etc...just the colormap at screen
coords(0,0)->(349,499) (rows,columns)? Could someone post a few lines
to do this? Thanks so much in advance!
-L
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