我正在尝试使用以下代码绘制风玫瑰。它曾经在几个月前工作。
import sys
from windrose import WindroseAxes
from matplotlib import pyplot as plt
import matplotlib.cm as cm
from numpy.random import random
from numpy import arange
import os
import numpy as np
def plot(prefix, spds, dirs):
ws = np.array(spds)
wd = np.array(dirs)
def new_axes():
fig = plt.figure(figsize=(8, 8), dpi=80, facecolor='w', edgecolor='w')
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
return ax, fig
def set_legend(ax):
l = ax.legend(axespad=-0.10, title="m/s", loc=0)
plt.setp(l.get_texts(), fontsize=8)
# windrose like a stacked histogram with normed (displayed in percent) results
ax, fig = new_axes()
ax.bar(wd, ws, normed=True, opening=0.8, edgecolor='white', bins=arange(0,max(ws),5))
set_legend(ax)
tokens = prefix.split("/")[-1].split("_")
if tokens[0] == "Dust":
title = "%s Dust" % tokens[1]
else:
title = tokens[0]
plt.title(title, y=1.08)
fig.savefig("%s-fig1.png" % prefix)
def main(folder="data"):
for filename in filter(lambda x:x.endswith(".csv"), os.listdir(folder)):
path = "%s/%s" % (folder, filename)
plot_path = "%s/plots" % folder
if not os.path.exists(plot_path):
os.mkdir(plot_path)
print path
f = open(path)
f.readline()
directions = []
speeds = []
for line in f:
cols = line.split(",")
direction = cols[5]
speed = cols[6]
try:
direction = int(direction)
speed = int(speed) * 0.44704
except:
continue
directions.append(direction)
speeds.append(speed)
plot("%s/plots/%s" % (folder, filename.split(".")[0]), speeds, directions)
if __name__ == "__main__":
main(sys.argv[1])
但是当我运行它时，我收到了这个错误：
IndexError Traceback (most recent call last)
/Users/Abdulhaleem-Labban/Dropbox/windrose/process.py in <module>()
112
113 if __name__ == "__main__":
--> 114 main(sys.argv[1])
115
IndexError: list index out of range
包含绘制风玫瑰所需数据的文件称为Dust_TabukWI_Wind.csv。这是一个样本：
Tabuk YR-- MO DA HRMN DIR SPD VSB MW
403750 1985 1 1 1125 240 28 0.4 32
403750 1985 1 18 1200 230 34 0.1 33
403750 1985 12 18 600 120 14 6.2 30
403750 1988 11 30 1300 340 34 0.3 32
403750 1992 12 15 900 240 31 0.3 33
403750 1992 12 15 1000 240 29 0.3 33
403750 1992 12 15 1100 240 29 0.6 33
403750 2008 1 29 1100 220 29 0.6 31
403750 2008 1 29 1200 210 34 3.1 30
403750 2008 1 29 1300 210 34 1.9 31
我认为这是具有＆＃34; argv＆＃34;但我该怎么办呢？
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__version__ = '1.4'
__author__ = 'Lionel Roubeyrie'
__mail__ = 'lionel.roubeyrie@gmail.com'
__license__ = 'CeCILL-B'
import matplotlib
import matplotlib.cm as cm
import numpy as np
from matplotlib.patches import Rectangle, Polygon
from matplotlib.ticker import ScalarFormatter, AutoLocator
from matplotlib.text import Text, FontProperties
from matplotlib.projections.polar import PolarAxes
from numpy.lib.twodim_base import histogram2d
import matplotlib.pyplot as plt
from pylab import poly_between
RESOLUTION = 100
ZBASE = -1000 #The starting zorder for all drawing, negative to have the grid on
class WindroseAxes(PolarAxes):
"""
Create a windrose axes
"""
def __init__(self, *args, **kwargs):
"""
See Axes base class for args and kwargs documentation
"""
#Uncomment to have the possibility to change the resolution directly
#when the instance is created
#self.RESOLUTION = kwargs.pop('resolution', 100)
PolarAxes.__init__(self, *args, **kwargs)
self.set_aspect('equal', adjustable='box', anchor='C')
self.radii_angle = 67.5
self.cla()
def cla(self):
"""
Clear the current axes
"""
PolarAxes.cla(self)
self.theta_angles = np.arange(0, 360, 45)
self.theta_labels = ['E', 'N-E', 'N', 'N-W', 'W', 'S-W', 'S', 'S-E']
self.set_thetagrids(angles=self.theta_angles, labels=self.theta_labels)
self._info = {'dir' : list(),
'bins' : list(),
'table' : list()}
self.patches_list = list()
def _colors(self, cmap, n):
'''
Returns a list of n colors based on the colormap cmap
'''
return [cmap(i) for i in np.linspace(0.0, 1.0, n)]
def set_radii_angle(self, **kwargs):
"""
Set the radii labels angle
"""
null = kwargs.pop('labels', None)
angle = kwargs.pop('angle', None)
if angle is None:
angle = self.radii_angle
self.radii_angle = angle
print self.get_rmax()
radii = np.linspace(0.1, self.get_rmax(), 6)
radii_labels = [ "%.1f%%" %r for r in radii ]
radii_labels[0] = "" #Removing label 0
# radii_labels = ["" for r in radii]
null = self.set_rgrids(radii=radii, labels=radii_labels,
angle=self.radii_angle, **kwargs)
def _update(self):
self.set_rmax(rmax=np.max(np.sum(self._info['table'], axis=0)))
self.set_radii_angle(angle=self.radii_angle)
def legend(self, loc='lower left', **kwargs):
"""
Sets the legend location and her properties.
The location codes are
'best' : 0,
'upper right' : 1,
'upper left' : 2,
'lower left' : 3,
'lower right' : 4,
'right' : 5,
'center left' : 6,
'center right' : 7,
'lower center' : 8,
'upper center' : 9,
'center' : 10,
If none of these are suitable, loc can be a 2-tuple giving x,y
in axes coords, ie,
loc = (0, 1) is left top
loc = (0.5, 0.5) is center, center
and so on. The following kwargs are supported:
isaxes=True # whether this is an axes legend
prop = FontProperties(size='smaller') # the font property
pad = 0.2 # the fractional whitespace inside the legend border
shadow # if True, draw a shadow behind legend
labelsep = 0.005 # the vertical space between the legend entries
handlelen = 0.05 # the length of the legend lines
handletextsep = 0.02 # the space between the legend line and legend text
axespad = 0.02 # the border between the axes and legend edge
"""
def get_handles():
handles = list()
for p in self.patches_list:
if isinstance(p, matplotlib.patches.Polygon) or \
isinstance(p, matplotlib.patches.Rectangle):
color = p.get_facecolor()
elif isinstance(p, matplotlib.lines.Line2D):
color = p.get_color()
else:
raise AttributeError("Can't handle patches")
handles.append(Rectangle((0, 0), 0.2, 0.2,
facecolor=color, edgecolor='black'))
return handles
def get_labels():
labels = np.copy(self._info['bins'])
labels = ["[%.1f : %0.1f[" %(labels[i], labels[i+1]) \
for i in range(len(labels)-1)]
return labels
null = kwargs.pop('labels', None)
null = kwargs.pop('handles', None)
handles = get_handles()
labels = get_labels()
self.legend_ = matplotlib.legend.Legend(self, handles, labels,
loc, **kwargs)
return self.legend_
def _init_plot(self, dir, var, **kwargs):
"""
Internal method used by all plotting commands
"""
#self.cla()
null = kwargs.pop('zorder', None)
#Init of the bins array if not set
bins = kwargs.pop('bins', None)
if bins is None:
bins = np.linspace(np.min(var), np.max(var), 6)
if isinstance(bins, int):
#bins = np.linspace(np.min(var), np.max(var), bins)
bins = [0.0,5.0,10.0,15.0,20.0,25.0,30.0,35.0,40.0]
bins = np.asarray(bins)
nbins = len(bins)
#Number of sectors
nsector = kwargs.pop('nsector', None)
if nsector is None:
nsector = 16
#Sets the colors table based on the colormap or the "colors" argument
colors = kwargs.pop('colors', None)
cmap = kwargs.pop('cmap', None)
if colors is not None:
if isinstance(colors, str):
colors = [colors]*nbins
if isinstance(colors, (tuple, list)):
if len(colors) != nbins:
raise ValueError("colors and bins must have same length")
else:
if cmap is None:
cmap = cm.jet
colors = self._colors(cmap, nbins)
#Building the angles list
angles = np.arange(0, -2*np.pi, -2*np.pi/nsector) + np.pi/2
normed = kwargs.pop('normed', False)
blowto = kwargs.pop('blowto', False)
#Set the global information dictionnary
self._info['dir'], self._info['bins'], self._info['table'] = histogram(dir, var, bins, nsector, normed, blowto)
return bins, nbins, nsector, colors, angles, kwargs
def contour(self, dir, var, **kwargs):
"""
Plot a windrose in linear mode. For each var bins, a line will be
draw on the axes, a segment between each sector (center to center).
Each line can be formated (color, width, ...) like with standard plot
pylab command.
Mandatory:
* dir : 1D array - directions the wind blows from, North centred
* var : 1D array - values of the variable to compute. Typically the wind
speeds
Optional:
* nsector: integer - number of sectors used to compute the windrose
table. If not set, nsectors=16, then each sector will be 360/16=22.5°,
and the resulting computed table will be aligned with the cardinals
points.
* bins : 1D array or integer- number of bins, or a sequence of
bins variable. If not set, bins=6, then
bins=linspace(min(var), max(var), 6)
* blowto : bool. If True, the windrose will be pi rotated,
to show where the wind blow to (usefull for pollutant rose).
* colors : string or tuple - one string color ('k' or 'black'), in this
case all bins will be plotted in this color; a tuple of matplotlib
color args (string, float, rgb, etc), different levels will be plotted
in different colors in the order specified.
* cmap : a cm Colormap instance from matplotlib.cm.
- if cmap == None and colors == None, a default Colormap is used.
others kwargs : see help(pylab.plot)
"""
bins, nbins, nsector, colors, angles, kwargs = self._init_plot(dir, var,
**kwargs)
#closing lines
angles = np.hstack((angles, angles[-1]-2*np.pi/nsector))
vals = np.hstack((self._info['table'],
np.reshape(self._info['table'][:,0],
(self._info['table'].shape[0], 1))))
offset = 0
for i in range(nbins):
val = vals[i,:] + offset
offset += vals[i, :]
zorder = ZBASE + nbins - i
patch = self.plot(angles, val, color=colors[i], zorder=zorder,
**kwargs)
self.patches_list.extend(patch)
self._update()
def contourf(self, dir, var, **kwargs):
"""
Plot a windrose in filled mode. For each var bins, a line will be
draw on the axes, a segment between each sector (center to center).
Each line can be formated (color, width, ...) like with standard plot
pylab command.
Mandatory:
* dir : 1D array - directions the wind blows from, North centred
* var : 1D array - values of the variable to compute. Typically the wind
speeds
Optional:
* nsector: integer - number of sectors used to compute the windrose
table. If not set, nsectors=16, then each sector will be 360/16=22.5°,
and the resulting computed table will be aligned with the cardinals
points.
* bins : 1D array or integer- number of bins, or a sequence of
bins variable. If not set, bins=6, then
bins=linspace(min(var), max(var), 6)
* blowto : bool. If True, the windrose will be pi rotated,
to show where the wind blow to (usefull for pollutant rose).
* colors : string or tuple - one string color ('k' or 'black'), in this
case all bins will be plotted in this color; a tuple of matplotlib
color args (string, float, rgb, etc), different levels will be plotted
in different colors in the order specified.
* cmap : a cm Colormap instance from matplotlib.cm.
- if cmap == None and colors == None, a default Colormap is used.
others kwargs : see help(pylab.plot)
"""
bins, nbins, nsector, colors, angles, kwargs = self._init_plot(dir, var,
**kwargs)
null = kwargs.pop('facecolor', None)
null = kwargs.pop('edgecolor', None)
#closing lines
angles = np.hstack((angles, angles[-1]-2*np.pi/nsector))
vals = np.hstack((self._info['table'],
np.reshape(self._info['table'][:,0],
(self._info['table'].shape[0], 1))))
offset = 0
for i in range(nbins):
val = vals[i,:] + offset
offset += vals[i, :]
zorder = ZBASE + nbins - i
xs, ys = poly_between(angles, 0, val)
patch = self.fill(xs, ys, facecolor=colors[i],
edgecolor=colors[i], zorder=zorder, **kwargs)
self.patches_list.extend(patch)
def bar(self, dir, var, **kwargs):
"""
Plot a windrose in bar mode. For each var bins and for each sector,
a colored bar will be draw on the axes.
Mandatory:
* dir : 1D array - directions the wind blows from, North centred
* var : 1D array - values of the variable to compute. Typically the wind
speeds
Optional:
* nsector: integer - number of sectors used to compute the windrose
table. If not set, nsectors=16, then each sector will be 360/16=22.5°,
and the resulting computed table will be aligned with the cardinals
points.
* bins : 1D array or integer- number of bins, or a sequence of
bins variable. If not set, bins=6 between min(var) and max(var).
* blowto : bool. If True, the windrose will be pi rotated,
to show where the wind blow to (usefull for pollutant rose).
* colors : string or tuple - one string color ('k' or 'black'), in this
case all bins will be plotted in this color; a tuple of matplotlib
color args (string, float, rgb, etc), different levels will be plotted
in different colors in the order specified.
* cmap : a cm Colormap instance from matplotlib.cm.
- if cmap == None and colors == None, a default Colormap is used.
edgecolor : string - The string color each edge bar will be plotted.
Default : no edgecolor
* opening : float - between 0.0 and 1.0, to control the space between
each sector (1.0 for no space)
"""
bins, nbins, nsector, colors, angles, kwargs = self._init_plot(dir, var,
**kwargs)
null = kwargs.pop('facecolor', None)
edgecolor = kwargs.pop('edgecolor', None)
if edgecolor is not None:
if not isinstance(edgecolor, str):
raise ValueError('edgecolor must be a string color')
opening = kwargs.pop('opening', None)
if opening is None:
opening = 0.8
dtheta = 2*np.pi/nsector
opening = dtheta*opening
for j in range(nsector):
offset = 0
for i in range(nbins):
if i > 0:
offset += self._info['table'][i-1, j]
val = self._info['table'][i, j]
zorder = ZBASE + nbins - i
patch = Rectangle((angles[j]-opening/2, offset), opening, val,
facecolor=colors[i], edgecolor=edgecolor, zorder=zorder,
**kwargs)
self.add_patch(patch)
if j == 0:
self.patches_list.append(patch)
self._update()
def box(self, dir, var, **kwargs):
"""
Plot a windrose in proportional bar mode. For each var bins and for each
sector, a colored bar will be draw on the axes.
Mandatory:
* dir : 1D array - directions the wind blows from, North centred
* var : 1D array - values of the variable to compute. Typically the wind
speeds
Optional:
* nsector: integer - number of sectors used to compute the windrose
table. If not set, nsectors=16, then each sector will be 360/16=22.5°,
and the resulting computed table will be aligned with the cardinals
points.
* bins : 1D array or integer- number of bins, or a sequence of
bins variable. If not set, bins=6 between min(var) and max(var).
* blowto : bool. If True, the windrose will be pi rotated,
to show where the wind blow to (usefull for pollutant rose).
* colors : string or tuple - one string color ('k' or 'black'), in this
case all bins will be plotted in this color; a tuple of matplotlib
color args (string, float, rgb, etc), different levels will be plotted
in different colors in the order specified.
* cmap : a cm Colormap instance from matplotlib.cm.
- if cmap == None and colors == None, a default Colormap is used.
edgecolor : string - The string color each edge bar will be plotted.
Default : no edgecolor
"""
bins, nbins, nsector, colors, angles, kwargs = self._init_plot(dir, var,
**kwargs)
null = kwargs.pop('facecolor', None)
edgecolor = kwargs.pop('edgecolor', None)
if edgecolor is not None:
if not isinstance(edgecolor, str):
raise ValueError('edgecolor must be a string color')
opening = np.linspace(0.0, np.pi/16, nbins)
for j in range(nsector):
offset = 0
for i in range(nbins):
if i > 0:
offset += self._info['table'][i-1, j]
val = self._info['table'][i, j]
zorder = ZBASE + nbins - i
patch = Rectangle((angles[j]-opening[i]/2, offset), opening[i],
val, facecolor=colors[i], edgecolor=edgecolor,
zorder=zorder, **kwargs)
self.add_patch(patch)
if j == 0:
self.patches_list.append(patch)
self._update()
def histogram(dir, var, bins, nsector, normed=False, blowto=False):
"""
Returns an array where, for each sector of wind
(centred on the north), we have the number of time the wind comes with a
particular var (speed, polluant concentration, ...).
* dir : 1D array - directions the wind blows from, North centred
* var : 1D array - values of the variable to compute. Typically the wind
speeds
* bins : list - list of var category against we're going to compute the table
* nsector : integer - number of sectors
* normed : boolean - The resulting table is normed in percent or not.
* blowto : boolean - Normaly a windrose is computed with directions
as wind blows from. If true, the table will be reversed (usefull for
pollutantrose)
"""
if len(var) != len(dir):
raise ValueError, "var and dir must have same length"
angle = 360./nsector
dir_bins = np.arange(-angle/2 ,360.+angle, angle, dtype=np.float)
dir_edges = dir_bins.tolist()
dir_edges.pop(-1)
dir_edges[0] = dir_edges.pop(-1)
dir_bins[0] = 0.
var_bins = bins.tolist()
var_bins.append(np.inf)
if blowto:
dir = dir + 180.
dir[dir>=360.] = dir[dir>=360.] - 360
table = histogram2d(x=var, y=dir, bins=[var_bins, dir_bins],
normed=False)[0]
# add the last value to the first to have the table of North winds
table[:,0] = table[:,0] + table[:,-1]
# and remove the last col
table = table[:, :-1]
if normed:
table = table*100/table.sum()
return dir_edges, var_bins, table
def wrcontour(dir, var, **kwargs):
fig = plt.figure()
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect)
fig.add_axes(ax)
ax.contour(dir, var, **kwargs)
l = ax.legend(axespad=-0.10)
plt.setp(l.get_texts(), fontsize=8)
plt.draw()
plt.show()
return ax
def wrcontourf(dir, var, **kwargs):
fig = plt.figure()
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect)
fig.add_axes(ax)
ax.contourf(dir, var, **kwargs)
l = ax.legend(axespad=-0.10)
plt.setp(l.get_texts(), fontsize=8)
plt.draw()
plt.show()
return ax
def wrbox(dir, var, **kwargs):
fig = plt.figure()
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect)
fig.add_axes(ax)
ax.box(dir, var, **kwargs)
l = ax.legend(axespad=-0.10)
plt.setp(l.get_texts(), fontsize=8)
plt.draw()
plt.show()
return ax
def wrbar(dir, var, **kwargs):
fig = plt.figure()
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect)
fig.add_axes(ax)
ax.bar(dir, var, **kwargs)
l = ax.legend(axespad=-0.10)
plt.setp(l.get_texts(), fontsize=8)
plt.draw()
plt.show()
return ax
def clean(dir, var):
'''
Remove masked values in the two arrays, where if a direction data is masked,
the var data will also be removed in the cleaning process (and vice-versa)
'''
dirmask = dir.mask==False
varmask = var.mask==False
ind = dirmask*varmask
return dir[ind], var[ind]
if __name__=='__main__':
from pylab import figure, show, setp, random, grid, draw
vv=random(500)*6
dv=random(500)*360
fig = figure(figsize=(8, 8), dpi=80, facecolor='w', edgecolor='w')
rect = [0.1, 0.1, 0.8, 0.8]
ax = WindroseAxes(fig, rect, axisbg='w')
fig.add_axes(ax)
# ax.contourf(dv, vv, bins=np.arange(0,8,1), cmap=cm.hot)
# ax.contour(dv, vv, bins=np.arange(0,8,1), colors='k')
# ax.bar(dv, vv, normed=True, opening=0.8, edgecolor='white')
ax.box(dv, vv, normed=True)
l = ax.legend(axespad=-0.10)
setp(l.get_texts(), fontsize=8)
draw()
#print ax._info
show()
答案 0 :(得分：2)
sys.argv是命令行参数的列表。 sys.argv[0]是命令本身，sys.argv[1]是第一个参数，等等。如果没有参数，只需命令sys.argv只有一个元素sys.argv[0]，试图阅读sys.argv[1]超出范围。
通常情况下，如果您的程序需要参数，请检查并打印一条用法消息：
if __name__ == "__main__":
if len(sys.argv) < 2:
sys.stderr.write("Usage: {0} <data-path>\n".format(sys.argv[0]))
sys.exit(1)
main(sys.argv[1])