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mp_plotter.py
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mp_plotter.py
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from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from mp_tools import *
plt.rcParams["font.family"] = 'serif'
##### this code will put in one place all your plotting choices
def mp_scatter(xarr, yarr, xerr=None, yerr=None, xlabel=None, ylabel=None, label=None, title=None, xscale='linear', yscale='linear', facecolor='LightCoral', edgecolor='k', size=None, colorarr=None, colormap=None, alpha=1, zorder=1, plot_legend='y', show_plot='y'):
#### BASIC SCATTER PLOT
plt.figure(figsize=(6,8))
### define your colors
if type(colormap) != type(None):
scatter_cmap = cm.get_cmap(colormap)
else:
scatter_cmap = cm.get_cmap('viridis')
if type(colorarr) != type(None):
norm_colorarr = (colorarr - np.nanmin(colorarr)) / (np.nanmax(colorarr) - np.nanmin(colorarr))
colors = scatter_cmap(norm_colorarr)
plt.scatter(xarr, yarr, color=colors, s=size, edgecolor=edgecolor, alpha=alpha, zorder=zorder, label=None)
else:
plt.scatter(xarr, yarr, color=facecolor, edgecolor=edgecolor, s=size, alpha=alpha, zorder=zorder, label=None)
plt.errorbar(xarr, yarr, xerr=xerr, ecolor='k', alpha=0.5, fmt='none', zorder=0)
plt.errorbar(xarr, yarr, yerr=yerr, ecolor='k', alpha=0.5, fmt='none', zorder=0)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xscale(xscale)
plt.yscale(yscale)
if plot_legend == 'y':
plt.legend()
plt.title(title)
if show_plot == 'y':
plt.show()
def mp_plot(xarr, yarr, xlabel=None, ylabel=None, xscale='linear', yscale='linear', label=None, title=None, color='DodgerBlue', linewidth=1, linestyle='solid', alpha=1, plot_legend='y', show_plot='y'):
plt.plot(xarr, yarr, color=color, linestyle=linestyle, linewidth=linewidth)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xscale(xscale)
plt.yscale(yscale)
plt.title(title)
if plot_legend == 'y':
plt.legend()
if show_plot == 'y':
plt.show()
def mp_hist(vals, nbins=20, bins=None, xscale='linear', title=None, yscale='linear', facecolor='DodgerBlue', edgecolor='k', alpha=0.7, xlabel=None, ylabel=None):
if type(bins) == type(None):
if xscale == 'linear':
bins =np.linspace(np.nanmin(vals), np.nanmax(vals), nbins)
elif xscale == 'log':
bins = np.logspace(np.log10(np.nanmin(vals)), np.log10(np.nanmax(vals)), nbins)
plt.figure(figsize=(6,8))
n,b,e = plt.hist(vals, bins=bins, facecolor=facecolor, edgecolor=edgecolor, alpha=alpha)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xscale(xscale)
plt.yscale(yscale)
plt.title(title)
plt.show()
return n,b,e
def mp_scatter_and_hist(x, y, xlabel=None, ylabel=None, xline=None, yline=None, xscale='log', yscale='log', facecolor='LightCoral'):
# definitions for the axes
left, width = 0.15, 0.60
bottom, height = 0.1, 0.65
spacing = 0.03
rect_scatter = [left, bottom, width, height]
rect_histx = [left, bottom + height + spacing, width, 0.2]
rect_histy = [left + width + spacing, bottom, 0.2, height]
# start with a rectangular Figure
plt.figure(figsize=(8, 8))
ax_scatter = plt.axes(rect_scatter)
ax_scatter.tick_params(direction='in', top=True, right=True)
ax_histx = plt.axes(rect_histx)
ax_histx.tick_params(direction='in', labelbottom=False)
ax_histy = plt.axes(rect_histy)
ax_histy.tick_params(direction='in', labelleft=False)
xmin, xmax = np.nanmin(x), np.nanmax(x)
ymin, ymax = np.nanmin(y), np.nanmax(y)
if xscale == 'log':
ax_scatter.set_xscale('log')
ax_histx.set_xscale('log') ### may need to be ax_histx
ax_scatter.set_xlim(xmin, xmax)
ax_histx.set_xlim(xmin, xmax)
if yscale == 'log':
ax_scatter.set_yscale('log')
ax_histy.set_yscale('log') #### may need to be ax_histy
ax_scatter.set_ylim(ymin, ymax)
ax_histy.set_ylim(ymin, ymax)
# the scatter plot:
ax_scatter.scatter(x, y, facecolor=facecolor, edgecolor='k', s=20, alpha=0.7)
# now determine nice limits by hand:
binwidth = 0.25
#lim = np.ceil(np.abs([x, y]).max() / binwidth) * binwidth
#ax_scatter.set_xlim((-lim, lim))
#ax_scatter.set_ylim((-lim, lim))
ax_scatter.set_xlim(np.nanmin(x), np.nanmax(x))
ax_scatter.set_ylim(np.nanmin(y), np.nanmax(y))
ax_scatter.set_xlabel(xlabel)
ax_scatter.set_ylabel(ylabel)
ax_scatter.tick_params(axis='x', labelsize=16)
ax_scatter.tick_params(axis='y', labelsize=16)
if xline != None:
xline_xvals = np.linspace(xline, xline, 100)
xline_yvals = np.linspace(np.nanmin(y), np.nanmax(y), 100)
ax_scatter.plot(xline_xvals, xline_yvals, c='k', linestyle='--')
if yline != None:
yline_xvals = np.linspace(np.nanmin(x), np.nanmax(x), 100)
yline_yvals = np.linspace(yline, yline, 100)
ax_scatter.plot(yline_xvals, yline_yvals, c='k', linestyle='--')
if xlabel != None:
ax_scatter.set_xlabel(xlabel, fontsize=20)
if ylabel != None:
ax_scatter.set_ylabel(ylabel, fontsize=20)
#bins = np.arange(-lim, lim + binwidth, binwidth)
#bins = 20
#xbins = np.logspace(np.log10(np.nanmin(x)), np.log10(np.nanmax(x)), 20)
#ybins = np.logspace(np.log10(np.nanmin(y)), np.log10(np.nanmax(y)), 20)
#xbins = np.logspace(-3,5,30)
#ybins = np.logspace(-3,5,30)
xbins = np.logspace(np.log10(xmin), np.log10(xmax), 30)
ybins = np.logspace(np.log10(ymin), np.log10(ymax), 30)
ax_histx.hist(x, bins=xbins, facecolor=facecolor, edgecolor='k', alpha=0.7)
ax_histy.hist(y, bins=ybins, orientation='horizontal', facecolor=facecolor, edgecolor='k', alpha=0.7)
ax_histx.tick_params(axis='y', labelsize=16)
ax_histy.tick_params(axis='x', labelsize=16)
#ax_histx.set_xlim(ax_scatter.get_xlim())
#ax_histy.set_ylim(ax_scatter.get_ylim())
plt.show()
def mp_heatmap(xarr, yarr, nbins=[20,20], xbins=None, ybins=None, xscale='linear', title=None, yscale='linear', facecolor='DodgerBlue', edgecolor='k', alpha=0.7, xlabel=None, ylabel=None, colormap='viridis'):
if type(xbins) == type(None) and type(ybins) == type(None):
if xscale == 'linear':
xbins =np.linspace(np.nanmin(xarr), np.nanmax(xarr), nbins[0])
ybins = np.linspace(np.nanmin(yarr), np.nanmax(yarr), nbins[1])
elif xscale == 'log':
xbins = np.logspace(np.log10(np.nanmin(xarr)), np.log10(np.nanmax(xarr)), nbins[0])
ybins = np.logspace(np.log10(np.nanmin(yarr)), np.log10(np.nanmax(yarr)), nbins[1])
plt.figure(figsize=(8,8))
h,xe,ye,im = plt.hist2d(xarr, yarr, bins=[xbins,ybins], cmap=colormap)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.xscale(xscale)
plt.yscale(yscale)
plt.title(title)
plt.show()
return h,xe,ye,im