Noe Brucy
330 lines
12 KiB
Python
330 lines
12 KiB
Python
# coding: utf-8
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import sys
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import os
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import tables
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import numpy as np
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import matplotlib as mpl
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if os.environ.get('DISPLAY','') == '':
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print('No display found. Using non-interactive Agg backend')
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mpl.use('Agg')
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from matplotlib.patches import Polygon
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import pylab as Pfrom scipy.stats import linregress
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import matplotlib.patches as mpatches
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from matplotlib.collections import PatchCollection
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from pp_params import *
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P.rcParams['image.cmap']='plasma'
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P.rcParams['savefig.dpi']=400
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tex_params= {'text.latex.preamble' : [r'\usepackage{amsmath}']}
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P.rcParams.update(tex_params)
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class Plotter:
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"""
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This class loads derived quantities and plot them
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"""
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# Axes information
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_ax_nb = {'x' : 0, 'y' : 1, 'z' : 2} # Number of each axes
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_axes_h = {'x' :'y', 'y' : 'x', 'z' : 'x'} # Associated horizontal axe
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_axes_v = {'x' : 'z', 'y' : 'z', 'z' : 'y'} # Associated vertical axe
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_ax_title = {'x' : r'$x$ (code)', 'y' : r'$y$ (code)', 'z' : r'$z$ (code)'}
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G = 1. # Gravitational constant
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def __init__(self, path_out='.', filename=None, pp_params=Params()):
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self.pp_params = pp_params
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# Determining output directory
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if path_out is None:
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if filename is None:
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self.path_out='.'
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else:
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self.path_out = os.path.dirname(filename)
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else:
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self.path_out = path_out
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# Find HDF5 file
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if filename is None:
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if not pp_params.out.tag == '':
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tag_name = '_' + pp_params.out.tag
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else :
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tag_name = ''
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self.filename = (self.path_out + '/postproc_' +
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tag_name + format(num,'05') + '.h5')
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else:
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self.filename = filename
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def plot_list(self, to_plot_list, axes, overwrite=False):
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self._file_out = tables.open_file(self.filename, mode="r")
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maps = self._file_out.root.maps
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for ax_los in axes:
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for name in to_plot_list:
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name_full = name + '_' + ax_los
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plot_filename = self._find_filename(name_full)
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if overwrite or not os.path.exists(plot_filename):
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self._plot_map(name, ax_los)
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P.savefig(plot_filename)
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else:
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print("Data for {} is already computed, skipping...".format(name_full))
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self._file_out.close()
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def _plot_map(self, name, ax_los):
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P.figure()
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ax_h = self._axes_h[ax_los]
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ax_v = self._axes_v[ax_los]
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im_extent = self._file_out.root.maps._v_attrs.im_extent
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radius = self._file_out.root.maps._v_attrs.radius
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center = self._file_out.root.maps._v_attrs.center
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if (name == 'Q' and not ax_los == 'z') or name == 'levels' or name=='speed':
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return
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dmap = self._file_out.get_node('/maps/{}_{}'.format(name, ax_los)).read()
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if name == 'Q' :
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im = P.imshow(dmap,
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extent=im_extent,
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origin='lower',
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cmap='RdBu',
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norm=mpl.colors.LogNorm(),
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vmin=0.01, vmax=100.)
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elif name == 'jeans_ratio' :
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im = P.imshow(dmap,
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extent=im_extent,
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origin='lower',
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cmap='RdBu',
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norm=mpl.colors.LogNorm(),
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vmin=0.1, vmax=1000.)
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else:
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im = P.imshow(dmap,
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extent=im_extent,
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origin='lower',
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norm=mpl.colors.LogNorm())
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P.locator_params(axis=ax_h, nbins=pp.params.plot.ntick)
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P.locator_params(axis=ax_v, nbins=pp.params.plot.ntick)
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if(self.pp_params.put_title):
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pass
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P.xlabel(self._ax_title[ax_h])
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P.ylabel(self._ax_title[ax_v])
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cbar = P.colorbar(im)
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if name == 'coldens':
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cbar.set_label(r'$\Sigma$ (code)')
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if pp.params.set_lim:
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im.set_clim(0.01, 100)
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# if 'levels' in names:
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# map_level = self._file_out.get_node('/maps/{}_{}'.format('levels', ax_los)).read()
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# # Computing linewidths
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# levels_ar = np.arange(np.min(map_level), np.max(map_level) + 1)
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# lw = np.ones(levels_ar.size) * 2
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# lvl_th = 8 # Level threeshold for reducing linewidths
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# lw[levels_ar >= lvl_th] = lw[levels_ar >= lvl_th]**(lvl_th - levels_ar[levels_ar >= lvl_th])
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# lw[levels_ar < lvl_th] = 1.
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# cont = P.contour(map_level,
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# extent=im_extent,
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# origin='lower',
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# colors='white',
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# linewidths=lw,
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# levels=levels_ar)
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# cont.levels = cont.levels + 1
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# P.clabel(cont,
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# cont.levels[cont.levels < 11],
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# inline=1, fontsize=8., fmt='%1d')
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elif name == 'rho':
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cbar.set_label(r'$\rho$ (code)')
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if 'speed' in names:
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dmap_vh = self._file_out.get_node('/maps/{}{}_{}'.format('v', ax_h, ax_los)).read()
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dmap_vv = self._file_out.get_node('/maps/{}{}_{}'.format('v', ax_v, ax_los)).read()
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vel_red = self.pp_params.plot.vel_red
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map_vh_red = dmap_vh[::vel_red,::vel_red] # take only a subset of velocities
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map_vv_red = dmap_vv[::vel_red,::vel_red]
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nh = map_vh_red.shape[0]
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nv = map_vv_red.shape[1]
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vec_h = (np.arange(nh)*2./nh*radius - radius + center[0] + radius/nh) * lbox
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vec_v = (np.arange(nv)*2./nv*radius - radius + center[1] + radius/nv) * lbox
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hh, vv = np.meshgrid(vec_h,vec_v)
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max_v = np.max(np.sqrt(map_vh_red**2 + map_vv_red**2))
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Q = P.quiver(hh, vv, map_vh_red, map_vv_red, units='width')
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P.quiverkey(Q, 0.7, 0.95, max_v,
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r'$'+str(max_v)[0:4]+'$ (code)', labelpos='E', coordinates='figure')
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elif name == 'T':
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cbar.set_label(r'$T (code)$')
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elif name == 'Q':
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cbar.set_label(r'$Q$')
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elif name == 'jeans':
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cbar.set_label(r'Jeans\'s lenght')
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else:
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cbar.set_label(name)
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def _find_filename(self, name_full):
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num = self._file_out.root._v_attrs.num
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return (self.path_out + '/' + name_full + '_' +
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self.pp_params.out.tag + '_' + format(num,'05') +
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self.pp_params.plot.out_ext)
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class InteractiveGUI:
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"""
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This is a matplotlib interactive session to restrain analysis to a specific area
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"""
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def onbuttonrelease(self, event):
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"""Deal with click events"""
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button = ['left','middle','right']
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toolbar = P.get_current_fig_manager().toolbar
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if toolbar.mode=='zoom rect' and event.inaxes == self.ax_col:
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print("zooming ")
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xlim = self.ax_col.get_xlim()
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ylim = self.ax_col.get_ylim()
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self.reset_mask()
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elif self.add_mask and event.inaxes == self.ax_col:
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self.plot_side()
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P.draw()
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def onbuttonpress(self, event):
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"""Deal with click events"""
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button = ['left','middle','right']
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toolbar = P.get_current_fig_manager().toolbar
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if toolbar.mode!='':
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print("You clicked on something, but toolbar is in mode {:s}.".format(toolbar.mode))
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print(self.add_mask)
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if self.add_mask and toolbar.mode=='' and event.inaxes == self.ax_col:
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ix, iy = event.xdata, event.ydata
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print("Add patch {}, {}".format(ix, iy))
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xlim = self.ax_col.get_xlim()
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ylim = self.ax_col.get_ylim()
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radius = 0.05 * min(abs(xlim[1] - xlim[0]), abs(ylim[1] - ylim[0]))
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circle = mpatches.Circle([ix, iy], radius, color='black', alpha=0.1, ec="none")
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self.circles.append(circle)
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self.ax_col.add_artist(circle)
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self.ax_col.draw_artist(circle)
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self.patch_mask = self.patch_mask | ((self.xx - ix)**2 + (self.yy -iy)**2 < radius**2)
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#self.plot_side()
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def onkeypress(self, event):
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"""whenever a key is pressed"""
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if not event.inaxes:
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return
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if event.key == 't':
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self.add_mask = not self.add_mask
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print("Add mode is {}".format(self.add_mask))
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elif event.key == 'r':
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self.reset_mask()
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def plot_side(self):
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if (self.add_mask):
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mask = (self.patch_mask & self.mask).flatten()
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else:
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mask = self.mask.flatten()
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self.ax_gamma.clear()
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P.sca(self.ax_gamma)
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plot_dcsdrho(self.fluct_maps, mask, tag=self.tag)
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self.ax_pdf.clear()
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P.sca(self.ax_pdf)
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sigma_pdf(self.fluct_maps, mask, tag=self.tag, nb_bin_hist=self.args.pdf_nb_bin)
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def reset_mask(self):
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xlim = self.ax_col.get_xlim()
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ylim = self.ax_col.get_ylim()
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self.mask = (self.xx >= xlim[0]) & (self.xx <= xlim[1]) & (self.yy >= ylim[0]) & (self.yy <= ylim[1])
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self.patch_mask = np.full(self.mask.shape, False)
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for circle in self.circles:
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circle.remove()
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self.circles = []
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self.plot_side()
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P.draw()
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def __init__(self, args, path, num,
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maps_disk=None,
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tag='',
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set_lim=True) :
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"""
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Interactive plotting
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Parameters
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----------
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num output number
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path path of the pipeline output
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"""
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self.args = args
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self.add_mask = False
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self.circles = []
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self.tag = tag
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path_out = path
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# Load maps file
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print("load maps file")
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name_maps = path + '/maps_disk' + '_' + tag + '_' + format(num,'05') + '.save'
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if maps_disk is None:
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if (len(glob.glob(name_maps)) == 0):
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raise IOError('no pickle file for disk maps {}. Run make_image_disk() first'.format(name_maps))
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f = open(name_maps,'r')
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maps_disk = pickle.load(f)
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f.close()
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print("maps file loaded")
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im_extent = maps_disk['im_extent']
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fig = P.figure();
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self.ax_col = P.subplot(1, 2, 1)
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coldens = maps_disk['coldens_z']
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im = self.ax_col.imshow(coldens,
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extent=im_extent,
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origin='lower',
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norm=mpl.colors.LogNorm())
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if set_lim:
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im.set_clim(0.01, 100)
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self.ax_col.set_xlabel(r'$x$')
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self.ax_col.set_ylabel(r'$y$')
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self.xx, self.yy, self.fluct_maps = disk_pdf(path, num, maps_disk, tag=self.tag, force=True, put_title=False, interactive=True)
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coord_flat = zip(self.xx.flatten(), self.yy.flatten())
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self.ax_gamma = P.subplot(2, 2, 2)
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self.ax_pdf = P.subplot(2,2,4)
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xlim = self.ax_col.get_xlim()
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ylim = self.ax_col.get_ylim()
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self.mask = (self.xx >= xlim[0]) & (self.xx <= xlim[1]) & (self.yy >= ylim[0]) & (self.yy <= ylim[1])
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self.patch_mask = np.full(self.mask.shape, False)
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self.plot_side()
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fig.canvas.mpl_connect('button_release_event', self.onbuttonrelease)
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fig.canvas.mpl_connect('button_press_event', self.onbuttonpress)
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fig.canvas.mpl_connect('key_press_event', self.onkeypress)
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P.tight_layout()
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P.show()
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