I am attempting to plot fields from a GRIB2 file of GFS model data (example file: https://nomads.ncep.noaa.gov/pub/data/nccf/com/gfs/prod/gfs.20220202/12/atmos/gfs.t12z.pgrb2.0p25.f006 ). Normally I would just use PyGRIB and I'd have this problem solved yesterday, but I am on Windows (because it's what my employer uses, so I'm stuck with it and have to make this work on a Windows environment) and Windows and PyGRIB don't play nice. I am able to open the GRIB2 file and even plot variables over the entire domain using GDAL. The only problem is I need a way to get an array of the latitude and longitude values at each grid point (similar to in PyGRIB doing .latlons() on a GRIB message) so I can plot a subset of the domain.
Basically, I'm trying to replicate what is being done in this video, and need the data (got it using dataset.GetRasterBand(269).ReadAsArray()), then the lat/lon information.
I also tried using xarray, but Windows doesn't play nice with xarray either.
Given your comfort with PyGRIB, I'd say the solution is to use Conda and install it on Windows. You can use conda-forge's miniforge to install conda. Then, however you get Conda, install pygrib with:
conda install -c conda-forge pygrib
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I followed the instructions on the official website to download the TensorFlow. I chose to create a virtual environment as the instruction shown for macOS. My question is that if I need to activate the virtual environment each time before I use TensorFlow?
For example, I want to use tensor flow on Jupiter notebook and that means I need to install Jupiter and other required packages like Seaborn/pandas as well on the virtual environment. However I already downloaded anaconda and basically, it has all the packages I need.
Besides, will it make a difference if I download it with conda?
Well, if you downloaded the packages (like you said TensorFlow and Seaborn) in the base Conda environment which is the default environment that anaconda provides on installation, then to use what it has, you need to run whatever program/IDE like Jupyter lab from it. So you would open Anaconda Prompt and then type in jupyter lab and it would open up a new socket and you can edit with your installed python libraries from Conda.
Otherwise in IDE's VSCode you can simply set the python interpreter to that from Conda.
However, if you install the libraries and packages you need using pip on your actual python installation not Conda, then there is no need for any activation. Everything will run right out of the box. You don't need to select the interpreter in IDE's like VSCode.
Bottom line, if you know what libraries you need and don't mind running pip install package-name every time you need a package, stick with pip.
If you don't like to that sort of 'low level' stuff then use Anaconda or Miniconda.
A screen shot of my problem
I have been trying to install Keras for about a week now. I installed Anaconda and then Tensorflow with Python3.5 and Jupyter. When I start up with the Anaconda3 prompt it always gives me the message
>was unexpected at this time
C:\Users\Ray Van>#IF NOT "==" #chcp > NUL
C:\Users\Ray Van>
I used to be able to just say
Jupyter Notebook but it doesn't like this
Also I want to say activate tensorflow and then say jupyter notebook and then run a Python program with Keras (for Neural networks) but no matter what I tried, nothing works. I read somewhere that having the blank in the name \Ray Van] can be a problem but I didn't set that up. Somehow it was just set up by Windows 10 and from reading various posts, it seem very difficult to change without risking having to install Windows10 again. Various places say that it is very easy to install Keras, but I have found the opposite after trying several days for 3 hours at a time. But I am not good at installing things like this and don't really understand how all the things are connected. Maybe I have to start over and install Anaconda and then tensorflow and then from within the tensorflow environment install Keras and Jupyter. I know the pip command or the conda command are used for this but I don't really understand that either. So a total newbie who just wants to run some Python programs for my Neural Network research using Keras.
Do I absolutely need to use jupyter notebook to run TensorFlow in Windows ?
I tried the detect object example with the jupyter notebook, it works but I'm not really comfortable, Im used to notepad++ and running python directly on my windows without virtual environment.
I tried to copy past all the codes but I run into many hugs.
No, it is not compulsory to use Jupyter notebook to run Tensorflow on Windows. I personally use PyCharm as my IDE and Anaconda for dependency management (this is completely optional).
I would recommend you to use a proper IDE instead of notepad++ because it's much easier to do debugging using an IDE. You'll also be cloning a lot from Git when you start developing your own model, and usually the open source models out there has a lot of classes and methods in it (take Google's Inception net for example).
Another alternative would be maybe you can start posting about the bugs you are facing, then we can all start helping you.
I followed a handy tutorial to setup a Google Compute Engine VM instance with data science libraries and Debian GNU/Linux 9 disk image. I ran a data exploration notebook I had put together on my local machine, and found pandas.read_csv() to screw up the import of my training data.
Correctly imported, the dataset is a pandas dataframe with one column ('text'). Each of 3000 entries in that column is an article from a biomedical literature corpus. What happens on the VM though is that some length threshold is applied and pandas shunts part of a given article to a new row of the dataframe. It does this to most but not all of the articles and the dataframe ends up with close to 6000 entries. More importantly, it's useless to try to train a model on.
I cloned my local environment using Vagrant but it looks like it might be difficult to get my disk image into Google Cloud and optimized. So, I thought I would check here first if anyone knows a simpler solution, like perhaps choosing a different machine type than Debian/Linux to set up my Compute Engine instance so that pandas functions work properly. Thanks for your input!
After you login to the Google Cloud VM instance that has Debian/GNU Linux default, you can use the usual:
sudo apt-get update
sudo apt-get install python-pandas
Else, if you prefer to use the pip installer, that works too:
sudo apt-get update
sudo apt-get install python-pip
Then you can install other PyPi libraries, such as pandas as sudo pip install pandas
Remember that if you want to install libraries for Python 3.x, use python3 instead of python in the above snippets.
I am new to cartopy and tried the examples in the documentation (e.g. http://scitools.org.uk/cartopy/docs/latest/examples/waves.py ). The colour plot displays fine, however, the coastlines are missing when I run the example.
I'm using anaconda on windows and tried installing cartopy via Christoph Gohlke's binaries as well as Rich Signell's conda package on binstar (both of which seem to be the same, resulting in version '0.11.x'). My matplotlib version is '1.3.1'.
How can I get the coastlines to display? Is there anything missing in my installation?
Thanks!
This has been fixed and the package uploaded to the scitools binstar channel. This issue reflects the change in the url of files on the natural earth website (i.e. changing under our feet).