Cartopy Plot Lines

Package installation. geometry as sgeom def find_side(ls, side): """ Given a shapely LineString which is assumed to be. The crosshair shows this: for the case that the lines should actually become curved, they are implemented as a piecewise linear curve with 10 vertices. Basemap and Cartopy conflict¶ The map projection that cf-plot uses at present conflicts with the Cartopy software. crs as ccrs ax = plt. This is the first of several labs on the Generic Mapping Tools (GMT). Below we show how to create Choropleth Maps using either px. This recipe converts raster pixels with a specified value to vector lines. Cartopy provides various "features" that can provide some or all of this content at varying resolutions. Cartopy Plot of Scotland. We will pass the radius value to the function argument and then it will calculate the Surface Area and Volume of a Sphere as per the formula. great_circle. ANN-Cartopy: A new mapping library using matplotlib. plot / #plotting based on data and metrics cartopy/ #matplotlib/cartopy graphing back end set5. Cartopy builds on top of matplotlib to provide object oriented map projection definitions and close integration with Shapely for powerful yet easy-to-use vector data processing tools. Inventory or Catalog objects can be performed with builtin methods, see e. Recognising this burden, the xarray developers have built on top of matplotlib. How to start doing GIS with Python on your own computer? Well, first you need to install Python and necessary Python modules that are used to perform various GIS-tasks. html)中找到了一个: import matplotlib. My first attempt, where I plot 1 million very small white points on a black map bounded to the latitude/longitude coordinates of NYC, turned out pretty well, and with less than 10 lines of code. The sence of the repository is to establish a kind of a platform for Earth scientists for searching and representing Python scripts and packages using PyNGL/PYNIO, matplotlib, cartopy, etc. Plot continuous magnetic field lines using Python Plot electric field lines around a point charge wi Draw electric field lines due to point charges usi The effect of pad_inches in Python Matplotlib. pyplot as plt # plot a line, implicitly creating a subplot(111) plt. The cartopy is a great tool for creating maps in many ways more advanced than the usual workhorse for map creation in pyhton - the Basemap module. In this post, we showed how to use xarray to easily open and filter NetCDF4 files, and how craft a publication ready plot with Matplotlib and cartopy. info can be None. nids format. Series) – Colors for the lines, defaults to “g” for Lines and “cyan. Updated on 1 November 2019 at 00:33 UTC. Recently a collegue asked me for help in creating a high resolution plot of this data for a poster. The ESRI shapefile is a popular geospatial vector data format. plot ([1, 2, 3]) # now create a subplot which represents the top plot of a grid # with 2 rows and 1 column. figure(figsize=(10,10), facecolor='w') # create the map using the cartopy Orthographic projection, selecting the South Pole. It can be read by cartopy and NetworkX. Trying to use Cartopy at work behind a firewall and proxy; How can I show a km ruler on a cartopy / matplotlib plot? Location of stored offline data for cartopy; Plot triangular grid with cartopy and matplotlib. We extract the features using - the OGR. 4, numpy and shapely libraries and has a simple and intuitivedrawing interface to matplotlib for creating publication quality maps. It makes sense to use a Equal Area projection (not to use one would be weird), but the choice of Albers is unexplained in any documentation I could find. From the optimally smoothed kernel density estimate, there are two modes. A new post about maps (with improved examples!) can be found here. wrf-python includes several routines to assist with plotting, primarily for obtaining the mapping object used for cartopy, basemap, and PyNGL. Cartopy builds on top of matplotlib to provide object oriented map projection definitions and close integration with Shapely for powerful yet easy-to-use vector data processing tools. You can control the defaults of almost every property in matplotlib: figure size and dpi, line width, color and style, axes, axis and grid properties, text and font properties and so on. And because we are using longitude and latitude coordinates, the appropriate projection is the plate carrée projection which maps meridians to vertical straight lines of constant spacing, and circles of latitude to horizontal straight lines of constant spacing, assuming the standard parallel is the equator. A few things before we get started. I have plotted a map of the world using matplotlib Cartopy. Cartopy is a Python library that provides cartographic tools for Python. pyplot as plt # plot a line, implicitly creating a subplot(111) plt. line_colors (dict/pandas. Additional arguments are passed directly to the matplotlib function which does the work. ) Unfortunately my output image is always empty (i. The yellow dots mark pressure observations assimilated while making the field shown. It can be read by cartopy and NetworkX. Source distributions. Anaconda is available for 64 and 32 bit Windows, macOS, and 64 and 32 bit Linux on the Intel and AMD x86 and x86-64 CPU architectures, and for 64 bit Linux on the IBM Power CPU. the precise line width, colour, alpha value or label position you want. takes an optional argument 'ax' which allows you to reuse an Axis to plot multiple lines. Cartopy (Not distributed with matplotlib)¶ An alternative mapping library written for matplotlib v1. Plotting functions will not work. We could now go ahead and plot our climatology using matplotlib, but it would take many lines of code to extract all the latitude and longitude information and to setup all the plot characteristics. It's a matplotlib extension, so it has got all its features to create data visualizations, and adds the geographical projections and some datasets to be able to plot coast lines, countries, and so on directly from the library. Cartopy Plot of Scotland Recently I've been using Python and Cartopy to plot some Latitude/Longitude data on a map. Polygon or shapely. contour() , except that it takes an iris. Series) - Colors for the buses, defaults to "b" bus_sizes (dict/pandas. Mollweide taken from open source projects. It makes sense to use a Equal Area projection (not to use one would be weird), but the choice of Albers is unexplained in any documentation I could find. Precedents of how to make line plots, scramble plots, zone diagrams, bar outlines, blunder bars, box plots, histograms, heatmaps, subplots, numerous tomahawks, polar graphs, and air pocket outlines. 0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3. Changing the fonts for the labels on each axis (the numbers) is a little bit more complicated, but you can use it in combination with the content above to specify fonts for every part of your graph. add_axes(x, y, width, height), in fractions of the plot size. prettyplotlib is an extension to matplotlib which changes many of the defaults to make plots some consider more attractive. Basemap is a great tool for creating maps using python in a simple way. For a full plot of 3 independent variables and one resultant variable, you need to encode the resultant variable as marker shape (one scatter3 or plot3 call for each different marker shape), or point size (scatter3; or a lot of plot3 calls), or as color (scatter3 or patch or a lot of plot3 calls), or as transparency (patch). What is Shapefile? The shapefile format:. How to use yam¶. matplotlib is a Python package used for data plotting and visualisation. there corresponding shortcut in intellij idea? if in project view, press alt+insert (new) | class. add_axes(x, y, width, height), in fractions of the plot size. How to plot city locations in Cartopy? Hi, I was looking at cartopy and am trying to find how to plot cities. A " datum " (called a "globe" in cartopy) that gives the three dimensional shape of the earth (and other things) A " projection " that maps a point on the earth's surface onto an x-y coordinate system to make a 2-dimensional plot. A Choropleth Map is a heatmap using geographical boundaries. geometry as sgeom def find_side(ls, side): """ Given a shapely LineString which is assumed to be. Maps with cartopy. With support from the National Science Foundation, Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. The yellow dots mark pressure observations assimilated while making the field shown. Most colormaps are directly inherited and renamed for meteorological applicati. There are 3 distinct options for visualising vector fields: quivers (example), barbs (example) and streamplots (example) each with their own benefits for displaying certain vector field forms. The functions bring the high-level, dataset-oriented API of the seaborn categorical plotting functions to more general plots (scatter plots and line plots). This allows us to visualize spherical harmonics appropriately on a sphere! I had previously worked out how to do all of this with Basemap, but it seems that Cartopy is slated to replace Basemap. If you search on Anaconda. The repository is still in progress. Unidata’s Online Python Training. The line connecting the three points is plot on the main map; Then, three new axes are created using fig. add_feature. All maintenance and development efforts should be focused on Cartopy. Recently I've been using Python and Cartopy to plot some Latitude/Longitude dataon a map. Plotting functions will not work. scatter() for line or scatter plots. 0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3. It's very straightforward and easy to use. Key features of cartopy are its object oriented projection definitions, and its ability to transform points, lines, vectors, polygons and images between those projections. Here are the examples of the python api cartopy. netCDF is just a storage format. Plotting maps with a loop: Best Practices Best practices for plotting data on a map with a loop If you want to plot many. Plots input source contour on a map using Matplotlib contour method. ogr) or want to use a different version of GEOS than the one included in the project wheels you should first install the GEOS library, Cython, and Numpy on your system (using apt, yum, brew, or other means) and then direct pip to ignore the binary. Plot with cartopy. A couple of things jumped out at me. great_circle. For absolute beginners, try plt. I want to plot the shapefile, and fill the polygon with a color according to the value in the polygon. With support from the National Science Foundation, Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. In this lesson, you will learn how to crop a raster dataset in Python. This allows for complete customization and fine control over the aesthetics of each plot, albeit with a lot of additional lines of code. Does anyone know how I can plot a longitude line in python? I am looking at ocean temperature in python and have created a map of global ocean surface temperature: >>> highres_temp='/home/data. I'm plotting some filled contours with Cartopy and Matplotlib. Cartopy (Not distributed with matplotlib)¶ An alternative mapping library written for matplotlib v1. Quite the same Wikipedia. AxesSubplot or cartopy. I am new to gis and am trying to plot a shapefile containing land polygons. Naturally it is also possible to create your own colormap ; there is an example of this in the Gallery. Plotting basic map features; Plotting projections; Using grid lines and labels; Plotting locations on the map; Plotting country maps with political boundaries; Plotting country maps using GeoPandas and cartopy; Plotting populated places of the world; Plotting the top five and bottom five populated countries; Plotting temperatures across the globe. Cartopy provides various “features” that can provide some or all of this content at varying resolutions. Since the data is 1 dimensional the line plot was used. We can use line plots to check the variation of air temperature at three different latitudes along a longitude line:. In this course, we learn how to select map projections, do contour plots, select color maps (or create your own color map), create colorbars, etc. Plotting with Geoplot and GeoPandas¶ Geoplot is a Python library providing a selection of easy-to-use geospatial visualizations. A few things before we get started. It makes sense to use a Equal Area projection (not to use one would be weird), but the choice of Albers is unexplained in any documentation I could find. The Cartopy documentation includes examples of how to plot points on a map projection. Some of the key features of cartopy are: object oriented projection definitions; point, line, vector, polygon and image transformations between projections. This example is a brief tour of the geoplot API. Suppose I have x and y go from 0 to 1 with 0. crs as ccrs import cartopy. subplot (211). The NWS makes its precipitation data available for download in NetCDF format, specifically we wanted to look at the April 18, 2013 data. Cartopy Projections and other reference systems¶ In Cartopy, each projection is a class. First, they are using an Albers Equal Area Projection in which to draw the mesh grid. Contour Plot: Contour Plot is like a 3D surface plot, where the 3rd dimension (Z) gets plotted as constant slices (contour) on a 2 Dimensional surface. cartopy/ # matplotlib/cartopy graphing back end acme_parser. project view can activated via alt+1. Here are the examples of the python api cartopy. If None (default) is passed the projection for cartopy is set to cartopy. I am new to gis and am trying to plot a shapefile containing land polygons. Try the following code. units import units from netCDF4 import num2date import numpy as np import scipy. Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. Homework 10: Cartopy¶ 1) Plot data from NARR¶ NARR is NCEP's North American Regional Reanalysis, a widely used product for studying the weather and climate of the continental US. Is this something you could help me with?. Udacity Inc. Excel tools: Matplotlib provides the facility to utilities for exchanging data with Microsoft Excel. import numpy as np import xarray as xr import matplotlib. Series) - Colors for the buses, defaults to "b" bus_sizes (dict/pandas. Parameters. plot (ax = ax) plt. The coordinates of the features are reprojected on the fly using the dest_srs keyword of wradlib. New Gorgeous White/Ivory Tulle Pearl A-Line Wedding/Bridal Dress Size4-6-8-12-++ Unrecognized grids can be decoded by EDEX simply by dropping *. plot ([1, 2, 3]) # now create a subplot which represents the top plot of a grid # with 2 rows and 1 column. We can use matplotlib's gca() function to get hold of the automatically created cartopy axes:. Here we use Cartopy instead of Basemap because we are loading a custom cut version of the fine resolution database. exercises/landsat exercise. IPythonデータサイエンスクックブックを読んでる 第7章のレシピ7. Installing Python + GIS¶ How to start doing GIS with Python on your own computer? Well, first you need to install Python and necessary Python modules that are used to perform various GIS-tasks. yam-h gives an overview over available commands and options. I hope you enjoyed it, and feel free to comment if you have questions or remarks (especially if you managed to properly display Google map's tiles in a cartopy plot!). line() calls matplotlib. Compound path. We’ll use QGis for the shapefile and Pyramid Analytics’ BI Office…. I am new to gis and am trying to plot a shapefile containing land polygons. Using folium - 4: Draw lines (Plot San Andreas Fault) In this blog, we will plot the San Andreas Fault on the Folium map using PolyLine. Package installation. The line plt. That is, given a value for z, lines are drawn for connecting the (x,y) coordinates where that z value occurs. How to start doing GIS with Python on your own computer? Well, first you need to install Python and necessary Python modules that are used to perform various GIS-tasks. Recommend:matplotlib - How to Embed Cartopy in a Python Tkinter GUI), but I need help figuring out how. Mar 02, 2015. However I really missed one nice feature that Basemap have - easy way to add background image to the map. Coverage increased (+4. The quick plot above just plots the raster data without any projection onto a coordinate system. * ``None`` to use either the Basemap or Cartopy library,. It can be read by cartopy and NetworkX. I think this is a problem in plot. The larger the number, the fewer vertices and edges each polygon has. PlateCarree() Here is a quick setup that shows what I'm talking about. The key features of Cartopy are its projection definitions and its ability to transform points, lines, vectors, polygons, and images between those projections. crs as ccrs: # Workaround for plotting lines of constant latitude/longitude as gridlines # labels not supported for this projection. show_vlines – If True, show vertical alignment grid lines on plot at positions of the major x-tick marks. When the result of a plot operation is a map, Iris will automatically create an appropriate cartopy axes if one doesn't already exist. ), or providing a higher-level API on top to simplify plot creation (ggplot, plotnine, HoloViews, GeoViews), or extending it with. Some simple shortcuts to Natural Earth data are provided in the cartopy. gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER import cartopy import cartopy. given a path to a Modis level1b file with a standard ‘CoreMetadata. How to use yam¶. The purpose of this page is to help you out installing Python and all those modules into your own computer. The convenience method xarray. Udacity Inc. Py-ART also contains routines which can produce common radar plots including PPIs and RHIs. pyplot as plt import metpy. The page containing the plots is named cfp. We need to put ax = plt. coastlines ds ['SpeciesConc_O3'][0, 0]. This tutorial will take you to a journey to create a simple flight tracking with python. Making a Scatter Plot When it comes to comparing multiple variables and establish their effect on each other, Scatter plot is a good way to present the same. The data is on a latitude/longitude grid, and when plotting on a cartopy projection, a white line runs down the middle of the figure, or wherever I set "central_longitude" into in ccrs. title ('surface ozone'); GEOS-FP met field ¶ We can also use the xarray package to load data from one of the met field files that are used to drive GEOS-Chem. ), or providing a higher-level API on top to simplify plot creation (ggplot, plotnine, HoloViews, GeoViews), or extending it with. Guide to PmagPy¶. warn("Warning: Cartopy is not installed in your python environment. Plotting with a map projection¶ Here, we plot countries as patches on a projected map. # we will set up a dict mapping legend line to orig line, and enable # picking on the legend line lines = [line1, line2] lined = dict for legline, origline in zip (leg. It makes sense to use a Equal Area projection (not to use one would be weird), but the choice of Albers is unexplained in any documentation I could find. Compound path. pyplot as plt import cartopy. Cartopy's maps are great, but they are not interactive. I want to plot the shapefile, and fill the polygon with a color according to the value in the polygon. Alternatively, we can use xarray's matplotlib wrappers to automate some of this plotting for us. The thin blue lines are mslp contours from each of 56 ensemble members (all members for v2c, the first 56 members for v3). feature module and can be added via ax. Now, in line 17, change the cmap from cartopy. 1-D interpolation (interp1d) ¶The interp1d class in scipy. Cartopy comes with powerful vector field plotting functionality. Consider the 3D variable air defined above. The coordinates of the features are reprojected on the fly using the dest_srs keyword of wradlib. gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTER import shapely. conda install -c conda-forge cartopy Then install pyleoclim via pip. gmplot allows you to easily plot polygons, lines, and points on google maps, using a "matplotlib-like interface". Dr Philip E. Series) – Sizes of bus points, defaults to 10. The decimal point is roughly where the data point is located. get_lines (), lines): legline. Plotting with CartoPy. Contour Plot: Contour Plot is like a 3D surface plot, where the 3rd dimension (Z) gets plotted as constant slices (contour) on a 2 Dimensional surface. Shorelines, river and political boundary datasets. Script Details. ABSTRACT: Output of a WRF-Hydro (configured as the NWM) simulation for the Clear Creek IA CZO. patches as mpatches. Finally a scatter plot is created. I think this is possible but not. The geopandas plot does not support adding a legend. Here we use Cartopy instead of Basemap because we are loading a custom cut version of the fine resolution database. # we will set up a dict mapping legend line to orig line, and enable # picking on the legend line lines = [line1, line2] lined = dict for legline, origline in zip (leg. This module contains classes representing coordinates in spatial, celestial, and terrestrial coordinate systems, as well as implementations of transformations between many of the coordinate systems. Series) – Sizes of bus points, defaults to 10. mymap and this is the object you should operate on. I'm having a little trouble plotting an iris cube on an orthographic plot. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive. python绘制地图一般使用Basemap绘图包,但该包配置相对较繁琐,自定义性不强,这里介绍一个绘制地图的利器Cartopy,个人认为该工具方便、快捷,附上一些自己写的程序。. coastlines()を使えば、作成したGeoAxesクラスの地図にNaturalEarthの海岸…. read_csv ( '2016_travel. Contour Plot: Contour Plot is like a 3D surface plot, where the 3rd dimension (Z) gets plotted as constant slices (contour) on a 2 Dimensional surface. The cartopy is a great tool for creating maps in many ways more advanced than the usual workhorse for map creation in pyhton - the Basemap module. Examples selected from hundreds of plots for each set of diagnostics. The code as shown in that URL apparently has worked and the plot has been shown. Extreamly Useful Python Libs that Can Be Installed with Conda and Pip. Can somebody tell me what I am doing wrong?. The following are code examples for showing how to use shapely. Cartopy¶ (Not distributed with matplotlib) An alternative mapping library written for matplotlib v1. Layer AttributeFilter and - the wradlib. It is also possible to use cartopy along with matplotlib if you are interested to add any graph on your existing map [9]. The first is a figure-level interface to the latter two that combines them with a FacetGrid. Simplify County, State Lines¶ Below is a choropleth that uses several other parameters. With the help of this cookbook, you'll be able. The Cartopy shape reader downloads global transportation routes from Natural Earth. gmplot allows you to easily plot polygons, lines, and points on google maps, using a "matplotlib-like interface". Mollweide taken from open source projects. Bring to Front: R G B Swap: R G R B G B Flip: Copy your colormap. Does anyone know how I can plot a longitude line in python? I am looking at ocean temperature in python and have created a map of global ocean surface temperature: >>> highres_temp='/home/data. Plot legends give meaning to a visualization, assigning meaning to the various plot elements. Cartopy¶ (Not distributed with matplotlib) An alternative mapping library written for matplotlib v1. Unfortunately, I can't seem to get this to work. feature module and can be added via ax. It is possible to make line plots of two-dimensional data by calling xarray. The horizontal lines runs across the map when the longitude data values are mixed across the boundary (0 or 360 degree). 2 and above) Excel tools: utilities for exchanging data with Microsoft Excel. Plotting with a map projection¶ Here, we plot countries as patches on a projected map. Line, Poly and RegularPoly Collection with autoscaling. Compound path. in eclipse or spring tools suite, add new class or package, example, shortcut ctrl+n. If you search on Anaconda. I've had far more success with cartopy, another UK Met Office toolkit. Geopandas dataframes are a lot like Pandas dataframes, so the two usually play nicely. COASTLINE) どちらか必要 #ax. Plot the network buses and lines using matplotlib and Basemap. How to plot city locations in Cartopy? Hi, I was looking at cartopy and am trying to find how to plot cities. cf-plot will move to using Cartopy when it is a little more mature but in the meantime if you need both then install them with the following before installing cf-plot. Cartopy provides various “features” that can provide some or all of this content at varying resolutions. The ESRI shapefile is a popular geospatial vector data format. This allows us to visualize spherical harmonics appropriately on a sphere! I had previously worked out how to do all of this with Basemap, but it seems that Cartopy is slated to replace Basemap. We previously saw how to create a simple legend; here we'll take a look at customizing the placement and aesthetics of the legend in Matplotlib. Here we demonstrate this from within the notebook by just calling the PmagPy functions. set_picker (5) # 5 pts tolerance lined [legline] = origline # blank line. In [3]: psy. For instance, we can quickly make a faceted plot of our seasonal data (including with a cartopy axis) with just a few lines of code:. The coordinates of the features are reprojected on the fly using the dest_srs keyword of wradlib. The repository is still in progress. The horizontal lines runs across the map when the longitude data values are mixed across the boundary (0 or 360 degree). takes an optional argument 'ax' which allows you to reuse an Axis to plot multiple lines. Cartopy: It is a mapping library consisting of object-oriented map projection definitions, and arbitrary point, line, polygon, and image transformation abilities. conda install -c conda-forge cartopy Then install pyleoclim via pip. get_vector_coordinates function. Note that while pyplot's imshow() function only shows a rectangular image cartopy's projections still work to project the data onto a globe. Plotting Geostationary Satellites in Python. Matplotlib aims to have a Python object representing everything that appears on the plot: for example, recall that the figure is the bounding box within which plot elements appear. Welcome! Looking for a fast and flexible visualization software? Here we present psyplot, an open source python project that mainly combines the plotting utilities of matplotlib and the data management of the xarray package and integrates them into a software that can be used via command-line and via a GUI!. What Does Crop a Raster Mean? Cropping (sometimes also referred to as clipping), is when you subset or make a dataset smaller, by removing all data outside of the crop area or spatial extent. coordsys – coordinate systems and transforms¶. The Shapely geometry of each route is used to determine whether it intersects with the Shapely geometry track of hurricane Katrina. lines_bars_and_markers Examples; misc Examples; mplot3d Examples; pie_and_polar_charts Examples; pylab_examples Examples; shapes_and_collections Examples; showcase Examples; specialty_plots Examples; statistics Examples; style_sheets Examples; subplots_axes_and_figures Examples; tests Examples; text_labels_and_annotations Examples; ticks_and. show(), or save figures by plt. Plots available include polygons with fills, drop pins, scatter points, grid lines, and heatmaps. 0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3. Some of the key features of cartopy are: object oriented projection definitions; point, line, vector, polygon and image transformations between projections. If string is passed, it will be. Therefore, we specify the x- and y-limits we want our zoomed-up plot. axes(projection=ccrs. These are downloaded and cached on the fly, so there may be some issues if the WiFi is being flaky in MP408. If you want to build Shapely from source for compatibility with other modules that depend on GEOS (such as cartopy or osgeo. 2 and above) Excel tools: utilities for exchanging data with Microsoft Excel. py * removed forloop * basic outline with cartopy, removed basemap \(from mpl\_hsec. Example 25 - irregular grid plot - Check of data values¶ To see if this plot is correct we can add some extra code to that above to plot the station locations and values at that point. Plot legends give meaning to a visualization, assigning meaning to the various plot elements. I'm having a little trouble plotting an iris cube on an orthographic plot. We previously saw how to create a simple legend; here we'll take a look at customizing the placement and aesthetics of the legend in Matplotlib. We present a new Python interface for GMT (GMT/Python) that makes use of the GMT API and of new features being developed for the upcoming GMT 6 release. pyplot as plt import cartopy. This example shows how to create a GeoDataFrame when starting from a regular DataFrame that has coordinates either WKT (well-known text) format, or in two columns. mymap and this is the object you should operate on. Plotting with CartoPy. crs as ccrs: # Workaround for plotting lines of constant latitude/longitude as gridlines # labels not supported for this projection. PlateCarree()) # Set up an OSGB map. contourf for filled contour plots, and plt. On jupyter:. Here we use Cartopy instead of Basemap because we are loading a custom cut version of the fine resolution database. by Christoph Gohlke, Laboratory for Fluorescence Dynamics, University of California, Irvine. Installing Python + GIS¶ How to start doing GIS with Python on your own computer? Well, first you need to install Python and necessary Python modules that are used to perform various GIS-tasks. netCDF is just a storage format. pyplot as plt import numpy as np # Draw map m = Basemap(projection='lcc', llcrnrlat=12, urcrnrlat=34,llcrnrlon=-115, urcrnrlon=-80,lat_1=20. Well, turns out the answer is: not very hard! We only need a few lines of code to process and plot all data points. How to plot city locations in Cartopy? Hi, I was looking at cartopy and am trying to find how to plot cities. For example:: # Set up a standard map for latlon data. pyplot as plt # plot a line, implicitly creating a subplot(111) plt. This post is a quick example on how to read geotiff images with GDAL and plot them with Cartopy. A variety of tools have built on Matplotlib's 2D-plotting capability over the years, either using it as a rendering engine for a certain type of data or in a certain domain (pandas, NetworkX, Cartopy, yt, etc. show_plot_methods barplot Make a bar plot of one-dimensional data combined Plot a 2D scalar field with an overlying vector field density Make a density plot of point data fldmean Calculate and plot the mean over x- and y-dimensions lineplot Make a line plot of one-dimensional data mapcombined Plot a 2D scalar field with an. Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Naturally it is also possible to create your own colormap ; there is an example of this in the Gallery. Interactive data visualization with python¶. It can be read by cartopy and NetworkX. PlateCarree ()) ax. Series) - Sizes of bus points, defaults to 10. axes(projection=cartopy. We learned how to make 2D plots, and touched a little bit of cartopy and Basemap. The Cartopy project will replace Basemap, but it hasn't yet implemented all of Basemap's features. html)中找到了一个: import matplotlib. I've been helping out a few people with plots recently. ncss import NCSS. 2 and above) Excel tools: utilities for exchanging data with Microsoft Excel. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: