/usr/lib/python3/dist-packages/ginga/util/plots.py is in python3-ginga 2.6.1-2.
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# plots.py -- Utility functions for plotting.
#
# This is open-source software licensed under a BSD license.
# Please see the file LICENSE.txt for details.
#
import numpy
import matplotlib as mpl
from matplotlib.figure import Figure
# fix issue of negative numbers rendering incorrectly with default font
mpl.rcParams['axes.unicode_minus'] = False
from ginga.util import iqcalc
from ginga.misc import Callback
class Plot(Callback.Callbacks):
def __init__(self, figure=None, logger=None, width=500, height=500):
Callback.Callbacks.__init__(self)
if figure is None:
figure = Figure()
dpi = figure.get_dpi()
if dpi is None or dpi < 0.1:
dpi = 100
wd_in, ht_in = float(width)/dpi, float(height)/dpi
figure.set_size_inches(wd_in, ht_in)
self.fig = figure
if hasattr(self.fig, 'set_tight_layout'):
self.fig.set_tight_layout(True)
self.logger = logger
self.fontsize = 10
self.ax = None
self.logx = False
self.logy = False
self.xdata = []
self.ydata = []
# For callbacks
for name in ('draw-canvas', ):
self.enable_callback(name)
def get_figure(self):
return self.fig
def get_widget(self):
return self.fig.canvas
def add_axis(self, **kwdargs):
self.ax = self.fig.add_subplot(111, **kwdargs)
return self.ax
def get_axis(self):
return self.ax
def set_axis(self, ax):
self.ax = ax
def set_titles(self, xtitle=None, ytitle=None, title=None,
rtitle=None):
if xtitle is not None:
self.ax.set_xlabel(xtitle)
if ytitle is not None:
self.ax.set_ylabel(ytitle)
if title is not None:
self.ax.set_title(title)
if rtitle is not None:
pass
ax = self.ax
for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
ax.get_xticklabels() + ax.get_yticklabels()):
item.set_fontsize(self.fontsize)
def clear(self):
self.logger.debug('clearing canvas...')
self.ax.cla()
self.xdata = []
self.ydata = []
def draw(self):
self.fig.canvas.draw()
self.make_callback('draw-canvas')
def plot(self, xarr, yarr, xtitle=None, ytitle=None, title=None,
rtitle=None, **kwdargs):
if self.ax is None:
self.add_axis()
if self.logx:
self.ax.set_xscale('log')
if self.logy:
self.ax.set_yscale('log')
self.xdata = xarr
self.ydata = yarr
self.set_titles(xtitle=xtitle, ytitle=ytitle, title=title,
rtitle=rtitle)
self.ax.grid(True)
self.ax.plot(xarr, yarr, **kwdargs)
for item in self.ax.get_xticklabels() + self.ax.get_yticklabels():
item.set_fontsize(self.fontsize)
# Make x axis labels a little more readable
lbls = self.ax.xaxis.get_ticklabels()
for lbl in lbls:
lbl.set(rotation=45, horizontalalignment='right')
#self.fig.tight_layout()
self.draw()
def get_data(self):
return self.fig, self.xdata, self.ydata
class HistogramPlot(Plot):
def histogram(self, data, numbins=2048,
xtitle=None, ytitle=None, title=None, rtitle=None):
minval = numpy.nanmin(data)
maxval = numpy.nanmax(data)
substval = (minval + maxval)/2.0
data[numpy.isnan(data)] = substval
dist, bins = numpy.histogram(data, bins=numbins, density=False)
# used with 'steps-post' drawstyle, this gives correct histogram-steps
x = bins
y = numpy.append(dist, dist[-1])
self.clear()
self.plot(x, y, alpha=1.0, linewidth=1.0, linestyle='-',
xtitle=xtitle, ytitle=ytitle, title=title, rtitle=rtitle,
drawstyle='steps-post')
class CutsPlot(Plot):
def cuts(self, data,
xtitle=None, ytitle=None, title=None, rtitle=None,
color=None):
"""data: pixel values along a line.
"""
y = data
x = numpy.arange(len(data))
self.plot(x, y, color=color, drawstyle='steps-mid',
xtitle=xtitle, ytitle=ytitle, title=title, rtitle=rtitle,
alpha=1.0, linewidth=1.0, linestyle='-')
class ContourPlot(Plot):
def __init__(self, *args, **kwargs):
super(ContourPlot, self).__init__(*args, **kwargs)
self.num_contours = 8
self.plot_panx = 0
self.plot_pany = 0
self.plot_zoomlevel = 1.0
self.cmap = "RdYlGn_r"
# decent choices: { bicubic | bilinear | nearest }
self.interpolation = "bilinear"
self.cbar = None
def connect_zoom_callbacks(self):
canvas = self.fig.canvas
connect = canvas.mpl_connect
# These are not ready for prime time...
# connect("motion_notify_event", self.plot_motion_notify)
# connect("button_press_event", self.plot_button_press)
connect("scroll_event", self.plot_scroll)
def _plot_contours(self, x, y, x1, y1, x2, y2, data,
num_contours=None):
# Make a contour plot
if num_contours is None:
num_contours = self.num_contours
if self.ax is None:
self.add_axis()
ht, wd = data.shape
self.ax.set_aspect('equal', adjustable='box')
self.set_titles(title='Contours')
#self.fig.tight_layout()
# Set pan position in contour plot
self.plot_panx = float(x) / wd
self.plot_pany = float(y) / ht
if self.cbar is not None:
self.cbar.remove()
self.ax.cla()
self.ax.set_axis_bgcolor('#303030')
try:
im = self.ax.imshow(data, interpolation=self.interpolation,
origin='lower', cmap=self.cmap)
# Create a contour plot
self.xdata = numpy.arange(x1, x2, 1)
self.ydata = numpy.arange(y1, y2, 1)
colors = [ 'black' ] * num_contours
cs = self.ax.contour(self.xdata, self.ydata, data, num_contours,
colors=colors
#cmap=self.cmap
)
## self.ax.clabel(cs, inline=1, fontsize=10,
## fmt='%5.3f', color='cyan')
# Mark the center of the object
self.ax.plot([x], [y], marker='x', ms=20.0,
color='cyan')
self.cbar = self.fig.colorbar(im, orientation='horizontal',
shrink=0.8, pad=0.07)
# Set the pan and zoom position & redraw
self.plot_panzoom()
except Exception as e:
self.logger.error("Error making contour plot: %s" % (
str(e)))
def plot_contours_data(self, x, y, data, num_contours=None):
ht, wd = data.shape
self._plot_contours(x, y, 0, 0, wd, ht, data,
num_contours=num_contours)
def plot_contours(self, x, y, radius, image, num_contours=None):
img_data, x1, y1, x2, y2 = image.cutout_radius(x, y, radius)
## self._plot_contours(x, y, x1, y1, x2, y2, img_data,
## num_contours=num_contours)
cx, cy = x - x1, y - y1
self.plot_contours_data(cx, cy, img_data,
num_contours=num_contours)
def plot_panzoom(self):
ht, wd = len(self.ydata), len(self.xdata)
x = int(self.plot_panx * wd)
y = int(self.plot_pany * ht)
if self.plot_zoomlevel >= 1.0:
scalefactor = 1.0 / self.plot_zoomlevel
elif self.plot_zoomlevel < -1.0:
scalefactor = - self.plot_zoomlevel
else:
# wierd condition?--reset to 1:1
scalefactor = 1.0
self.plot_zoomlevel = 1.0
xdelta = int(scalefactor * (wd/2.0))
ydelta = int(scalefactor * (ht/2.0))
xlo, xhi = x-xdelta, x+xdelta
# distribute remaining x space from plot
if xlo < 0:
xsh = abs(xlo)
xlo, xhi = 0, min(wd-1, xhi+xsh)
elif xhi >= wd:
xsh = xhi - wd
xlo, xhi = max(0, xlo-xsh), wd-1
self.ax.set_xlim(xlo, xhi)
ylo, yhi = y-ydelta, y+ydelta
# distribute remaining y space from plot
if ylo < 0:
ysh = abs(ylo)
ylo, yhi = 0, min(ht-1, yhi+ysh)
elif yhi >= ht:
ysh = yhi - ht
ylo, yhi = max(0, ylo-ysh), ht-1
self.ax.set_ylim(ylo, yhi)
self.draw()
def plot_zoom(self, val):
self.plot_zoomlevel = val
self.plot_panzoom()
def plot_scroll(self, event):
# Matplotlib only gives us the number of steps of the scroll,
# positive for up and negative for down.
direction = None
if event.step > 0:
#delta = 0.9
self.plot_zoomlevel += 1.0
elif event.step < 0:
#delta = 1.1
self.plot_zoomlevel -= 1.0
self.plot_panzoom()
# x1, x2 = self.ax.get_xlim()
# y1, y2 = self.ax.get_ylim()
# self.ax.set_xlim(x1*delta, x2*delta)
# self.ax.set_ylim(y1*delta, y2*delta)
# self.draw()
return True
def plot_button_press(self, event):
if event.button == 1:
self.plot_x, self.plot_y = event.x, event.y
return True
def plot_motion_notify(self, event):
if event.button == 1:
xdelta = event.x - self.plot_x
#ydelta = event.y - self.plot_y
ydelta = self.plot_y - event.y
self.pan_plot(xdelta, ydelta)
def pan_plot(self, xdelta, ydelta):
x1, x2 = self.ax.get_xlim()
y1, y2 = self.ax.get_ylim()
self.ax.set_xlim(x1+xdelta, x2+xdelta)
self.ax.set_ylim(y1+ydelta, y2+ydelta)
self.draw()
class RadialPlot(Plot):
def plot_radial(self, x, y, radius, image):
img_data, x1, y1, x2, y2 = image.cutout_radius(x, y, radius)
self.ax.cla()
# Make a radial plot
self.ax.set_xlim(-0.1, radius)
self.set_titles(title="Radial plot", xtitle='Radius [pixels]',
ytitle='Pixel Value (ADU)')
self.ax.grid(True)
try:
ht, wd = img_data.shape
off_x, off_y = x1, y1
maxval = numpy.nanmax(img_data)
# create arrays of radius and value
r = []
v = []
for i in range(0, wd):
for j in range(0, ht):
r.append( numpy.sqrt( (off_x + i - x)**2 + (off_y + j - y)**2 ) )
v.append(img_data[j, i])
r, v = numpy.array(r), numpy.array(v)
# compute and plot radial fitting
# note: you might wanna change `deg` here.
coefficients = numpy.polyfit(x=r, y=v, deg=10)
polynomial = numpy.poly1d(coefficients)
x_curve = numpy.linspace(numpy.min(r), numpy.max(r), len(r))
y_curve = polynomial(x_curve)
yerror = 0 # for now, no error bars
self.ax.errorbar(r, v, yerr=yerror, marker='x', ls='none',
color='blue')
self.ax.plot(x_curve, y_curve, '-', color='green', lw=2)
#self.fig.tight_layout()
self.draw()
except Exception as e:
self.logger.error("Error making radial plot: %s" % (
str(e)))
class FWHMPlot(Plot):
def __init__(self, *args, **kwargs):
super(FWHMPlot, self).__init__(*args, **kwargs)
self.iqcalc = iqcalc.IQCalc(self.logger)
def _plot_fwhm_axis(self, arr, iqcalc, skybg, color1, color2, color3):
N = len(arr)
X = numpy.array(list(range(N)))
Y = arr
# subtract sky background
Y = Y - skybg
maxv = Y.max()
# clamp to 0..max
Y = Y.clip(0, maxv)
self.logger.debug("Y=%s" % (str(Y)))
self.ax.plot(X, Y, color=color1, marker='.')
fwhm, mu, sdev, maxv = iqcalc.calc_fwhm(arr)
# Make a little smoother gaussian curve by plotting intermediate
# points
XN = numpy.linspace(0.0, float(N), N*10)
Z = numpy.array([iqcalc.gaussian(x, (mu, sdev, maxv))
for x in XN])
self.ax.plot(XN, Z, color=color1, linestyle=':')
self.ax.axvspan(mu-fwhm/2.0, mu+fwhm/2.0,
facecolor=color3, alpha=0.25)
return (fwhm, mu, sdev, maxv)
def plot_fwhm(self, x, y, radius, image, cutout_data=None, iqcalc=None):
x0, y0, xarr, yarr = image.cutout_cross(x, y, radius)
if iqcalc is None:
iqcalc = self.iqcalc
self.ax.cla()
#self.ax.set_aspect('equal', adjustable='box')
self.set_titles(ytitle='Brightness', xtitle='Pixels',
title='FWHM')
self.ax.grid(True)
# Make a FWHM plot
try:
# get median value from the cutout area
if cutout_data is None:
cutout_data, x1, y1, x2, y2 = image.cutout_radius(x, y, radius)
skybg = numpy.median(cutout_data)
self.logger.debug("cutting x=%d y=%d r=%d med=%f" % (
x, y, radius, skybg))
self.logger.debug("xarr=%s" % (str(xarr)))
fwhm_x, mu, sdev, maxv = self._plot_fwhm_axis(xarr, iqcalc, skybg,
'blue', 'blue', 'skyblue')
self.logger.debug("yarr=%s" % (str(yarr)))
fwhm_y, mu, sdev, maxv = self._plot_fwhm_axis(yarr, iqcalc, skybg,
'green', 'green', 'seagreen')
self.ax.legend(('data x', 'gauss x', 'data y', 'gauss y'),
loc='upper right', shadow=False, fancybox=False,
prop={'size': 8}, labelspacing=0.2)
self.set_titles(title="FWHM X: %.2f Y: %.2f" % (fwhm_x, fwhm_y))
#self.fig.tight_layout()
self.draw()
except Exception as e:
self.logger.error("Error making fwhm plot: %s" % (
str(e)))
class SurfacePlot(Plot):
def __init__(self, *args, **kwargs):
super(SurfacePlot, self).__init__(*args, **kwargs)
self.dx = 21
self.dy = 21
self.floor = None
self.ceiling = None
self.stride = 1
self.cmap = "RdYlGn_r"
def plot_surface(self, x, y, radius, image, cutout_data=None):
Z, x1, y1, x2, y2 = image.cutout_radius(x, y, radius)
X = numpy.arange(x1, x2, 1)
Y = numpy.arange(y1, y2, 1)
X, Y = numpy.meshgrid(X, Y)
try:
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.ticker import LinearLocator, FormatStrFormatter
self.ax = self.fig.gca(projection='3d', axisbg='#808080')
self.ax.set_aspect('equal', adjustable='box')
#self.ax.cla()
self.set_titles(ytitle='Y', xtitle='X',
title='Surface Plot')
self.ax.grid(True)
zmin = numpy.min(Z) if self.floor is None else self.floor
zmax = numpy.max(Z) if self.ceiling is None else self.ceiling
sfc = self.ax.plot_surface(X, Y, Z, rstride=self.stride,
cstride=self.stride,
cmap=self.cmap, linewidth=0,
antialiased=False)
# TODO: need to determine sensible defaults for these based
# on the data
self.ax.zaxis.set_major_locator(LinearLocator(10))
self.ax.zaxis.set_major_formatter(FormatStrFormatter('%.0f'))
self.ax.set_zlim(zmin, zmax)
self.ax.xaxis.set_ticks(numpy.arange(x1, x2, 10))
self.ax.xaxis.set_major_formatter(FormatStrFormatter('%.0f'))
self.ax.yaxis.set_ticks(numpy.arange(y1, y2, 10))
self.ax.yaxis.set_major_formatter(FormatStrFormatter('%.0f'))
self.ax.view_init(elev=20.0, azim=30.0)
self.fig.colorbar(sfc, orientation='horizontal', shrink=0.9,
pad=0.01)
self.draw()
except Exception as e:
self.logger.error("Error making surface plot: %s" % (
str(e)))
#END
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