matplotlib should handle both masked arrays and arrays with NaNs and
treat both the same. Can you reduce the script to something that can be
run independently without data? It's not clear to me yet why this is
failing.
Mike
On 11/01/2011 05:24 PM, questions anon wrote:
Hi All,
I am trying to plot time against mean daily temperature values. The
problem is temperature contains no data in a few areas. I want to be
able to ignore this and continue plotting.
When I run the below script on my data that has all normal numbers it
works fine but when I run the script on my data that has sections of
'no data' I receive the below error and the graph will not plot the
trendline. Any suggestions on how I could fix this.
Thanks
/Warning (from warnings module):
File "C:\Python27\lib\site-packages\numpy\ma\core.py", line 3785
warnings.warn("Warning: converting a masked element to nan.")
UserWarning: Warning: converting a masked element to nan./
from netCDF4 import Dataset
import matplotlib.pyplot as plt
import numpy as N
from mpl_toolkits.basemap import Basemap
from netcdftime import utime
from datetime import datetime
import os
from numpy import *
import matplotlib.dates as mdates
from numpy import ma as MA
TSFCmeanall=[]
timeall=[]
time_intall=[]
MainFolder=r"E:/GriddedData/T_SFC/1987/"
for (path, dirs, files) in os.walk(MainFolder):
for dir in dirs:
print dir
path=path+'/'
for ncfile in files:
if ncfile[-3:]=='.nc':
ncfile=os.path.join(path,ncfile)
ncfile=Dataset(ncfile, 'r+',
'NETCDF4')
TSFC=ncfile.variables['T_SFC'][0:20]
TIME=ncfile.variables['time'][0:20]
fillvalue=ncfile.variables['T_SFC']._FillValue
TSFC=MA.masked_values(TSFC, fillvalue)
ncfile.close()
for TSFC, TIME in
zip((TSFC[:]),(TIME[:])):
cdftime=utime('seconds since
1970-01-01 00:00:00')
ncfiletime=cdftime.num2date(TIME)
timestr=str(ncfiletime)
d = datetime.strptime(timestr,
'%Y-%m-%d %H:%M:%S')
date_string =
d.strftime('%Y%m%d%H')
time_int=int(date_string)
TSFCmean=N.mean(TSFC)
TSFCmeanall.append(TSFCmean)
timeall.append(ncfiletime)
time_intall.append(time_int)
x=timeall
y=TSFCmeanall
x2=time_intall
fig, ax=plt.subplots(1)
z=N.polyfit(x2,y,1)
p=N.poly1d(z)
plt.plot(x,y)
plt.plot(x,p(x2),'r--') #add trendline to plot
fig.autofmt_xdate()
ax.fmt_xdata=mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
plt.ylabel("Temperature C")
plt.title("Mean Daily Temp")
plt.show()
------------------------------------------------------------------------------
RSA® Conference 2012
Save $700 by Nov 18
Register now!
http://p.sf.net/sfu/rsa-sfdev2dev1
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
------------------------------------------------------------------------------
RSA® Conference 2012
Save $700 by Nov 18
Register now!
http://p.sf.net/sfu/rsa-sfdev2dev1
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
