Hi Hannah-
Yes, that works!! Thank you! I’ve got one more question –and if I can understand this example, then I think I can make my plot display the lat/lon lines onto the contour plot. Could you comment on what’s going on with this code with the highlight lines below? https://scitools.org.uk/cartopy/docs/v0.15/matplotlib/advanced_plotting.html
Then, I should be able to apply it to my plotting problem.
Thanks! Randall
Here is my image and I’m trying to plot the lat/lon lines and the plotting code:
# Define an axes object with a projection
ax = plt.axes(projection=ccrs.PlateCarree())
# Plot the coastline
ax.coastlines(lw=1)
stdnasq = stdna.squeeze().plot.contourf(levels=12,add_labels=True)
ax.set_xlabel('')
plt.show()
[cid:image001.jpg at 01D5FE99.80A33A50]
import os
import matplotlib.pyplot as plt
from netCDF4 import Dataset as netcdf_dataset
import numpy as np
from cartopy import config
import cartopy.crs as ccrs
# get the path of the file. It can be found in the repo data directory.
fname = os.path.join(config["repo_data_dir"],
'netcdf', 'HadISST1_SST_update.nc'
)
dataset = netcdf_dataset(fname)
sst = dataset.variables['sst'][0, :, :]
lats = dataset.variables['lat'][:]
lons = dataset.variables['lon'][:]
ax = plt.axes(projection=ccrs.PlateCarree())
plt.contourf(lons, lats, sst, 60,
transform=ccrs.PlateCarree())
ax.coastlines()
plt.show()
From: Hannah <story645 at gmail.com>
Sent: Thursday, March 19, 2020 3:38 PM
To: Benson, Randall <Randall.Benson at avangrid.com>
Cc: Matplotlib-users <matplotlib-users at python.org>
Subject: Re: EXTERNAL: Re: [Matplotlib-users] Variability Plots Matplotlib NetCDF4 Data
Ok, was able to reproduce when I did stdna.plot.contour() (missed that bit the first time!) and the fix was stdna.squeeze().plot.contour()
On Thu, Mar 19, 2020 at 6:35 PM Hannah <story645 at gmail.com<mailto:story645 at gmail.com>> wrote:
try stdna.squeeze().plot() ?
I tried to make a minimum reproduction & I can't reproduce the error. Any chance you can share a binder or how you're getting your data?
This is what I tried:
slp = np.random.random(([1, 73,144]))
stdn = xr.Dataset({'slp': (['month', 'lat', 'lon'], slp)})
stdna = stdn.to_array()# must convert the xarray "dataset" to "dataArray"!!!
print(stdna.shape)
stdna = stdna.rename('Standardized SLP Anomaly')
ax = plt.axes(projection=ccrs.PlateCarree())
ax.coastlines(lw=1)
stdna.plot()
On Thu, Mar 19, 2020 at 5:52 PM Benson, Randall <Randall.Benson at avangrid.com<mailto:Randall.Benson at avangrid.com>> wrote:
Hi -
I solved it by converting the datasets to dataarrays using this below with my variable a dataArray “stdna” and calling the “plot” command.
However, when I try to plot this variable using -- stdna.plot.contourf() – but I get an error saying my data must be 2D. The “stnda” variable looks like this –
stdna
Out[181]:
<xarray.DataArray 'Standardized SLP Anomaly' (variable: 1, month: 1, lat: 73, lon: 144)>
dask.array<stack, shape=(1, 1, 73, 144), dtype=float32, chunksize=(1, 1, 73, 144), chunktype=numpy.ndarray>
Coordinates:
* lon (lon) float32 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5
* lat (lat) float32 90.0 87.5 85.0 82.5 80.0 ... -82.5 -85.0 -87.5 -90.0
* month (month) int64 1
* variable (variable) <U3 'slp'
--------------------------------------------------------------
This works below….
stdna = stdn.to_array()# must convert the xarray "dataset" to "dataArray"!!!
#stdna.rename('Standardized SLP Anomaly')#rename dataarray
stdna = stdna.rename('Standardized SLP Anomaly')#for legend description label
# Define an axes object with a projection
ax = plt.axes(projection=ccrs.PlateCarree())
# Plot the coastline
ax.coastlines(lw=1)
stdna.plot()
#
From: Hannah <story645 at gmail.com<mailto:story645 at gmail.com>>
Sent: Thursday, March 19, 2020 1:32 PM
To: Benson, Randall <Randall.Benson at avangrid.com<mailto:Randall.Benson at avangrid.com>>
Cc: Matplotlib-users <matplotlib-users at python.org<mailto:matplotlib-users at python.org>>
Subject: Re: EXTERNAL: Re: [Matplotlib-users] Variability Plots Matplotlib NetCDF4 Data
Hi,
Sorry for the late reply, been swamped. If you haven't sorted this out, can you please post at least some of the code that generated this error?
Thanks!
On Tue, Mar 17, 2020 at 1:06 AM Benson, Randall <Randall.Benson at avangrid.com<mailto:Randall.Benson at avangrid.com>> wrote:
Hi Hannah –
Are you familiar with this error using xarray to plot gridded netcd4 data?
This is the out from “stdn.var”
<bound method ImplementsDatasetReduce._reduce_method.<locals>.wrapped_func of <xarray.Dataset>
Dimensions: (lat: 73, lon: 144, month: 1)
Coordinates:
* month (month) int64 2
* lon (lon) float32 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5
* lat (lat) float32 90.0 87.5 85.0 82.5 80.0 ... -82.5 -85.0 -87.5 -90.0
Data variables:
slp (month, lat, lon) float32 dask.array<chunksize=(1, 73, 144), meta=np.ndarray>>
I keep getting this error –
- AttributeError: '_Dataset_PlotMethods' object has no attribute 'contourf'
Thank you,
Randall
From: Hannah <story645 at gmail.com<mailto:story645 at gmail.com>>
Sent: Wednesday, March 11, 2020 4:28 PM
To: Benson, Randall <Randall.Benson at avangrid.com<mailto:Randall.Benson at avangrid.com>>
Cc: Matplotlib-users <matplotlib-users at python.org<mailto:matplotlib-users at python.org>>
Subject: EXTERNAL: Re: [Matplotlib-users] Variability Plots Matplotlib NetCDF4 Data
Hi Randall,
I'm not sure what specifically you're asking for. Are you using xarray (http://xarray.pydata.org/en/stable/) ? If not, it might help in more efficiently computing the anomolies once you read all the files into an xarray:
http://xarray.pydata.org/en/stable/examples/weather-data.html#Calculate-monthly-anomalies
On Wed, Mar 11, 2020, 4:17 PM Benson, Randall <Randall.Benson at avangrid.com<mailto:Randall.Benson at avangrid.com>> wrote:
HI-
I’m trying to develop monthly standardized anomaly plots of Sea Level Pressure (SLP) using NCEP reanalysis data in netCDF4 format. I can plot netCDF4 data for a single month in plot form like the example shown below. However, I need to construct average SLP plots for each month given a set of years and use those to plot the standardized anomalies for each month of the current year. So, I’m looking too for just examples (python code) of creating variability plots using gridded data in Matplotlib. Thank you!
Randall Benson
Randall P. Benson, PhD
Wind Asset Meteorologist, Energy Resource - Onshore
1125 NW Couch Street, Suite 700
Portland, Oregon, USA 97209
Telephone 503-796-7129
Cell 971-227-2477
randall.benson at avangrid.com<mailto:randall.benson at avangrid.com>
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