def plotPoints(map_name, lat_long, cl):
    fig, ax = plt.subplots()
    x = [lat_long['lng']]
    y = [lat_long['lat']]
    ax.plot(x, y, cl)
    maps = "templates/" + map_name + ".html"
    f = open(maps, "w")
    f.write(mplleaflet.fig_to_html(fig=fig))
    f.close()
def plotWeather(map_name, hail_la_ln, wind_la_ln, tornado_la_ln):
    fig, ax = plt.subplots()
    x = [hail_la_ln['lng']]
    y = [hail_la_ln['lat']]
    ax.plot(x, y, 'b*')
    x = [wind_la_ln['lng']]
    y = [wind_la_ln['lat']]
    ax.plot(x, y, 'r>')
    x = [tornado_la_ln['lng']]
    y = [tornado_la_ln['lat']]
    ax.plot(x, y, 'g^')
    maps = "templates/" + map_name + ".html"
    f = open(maps, "w")
    f.write(mplleaflet.fig_to_html(fig=fig))
    f.close()
Beispiel #3
0
    def evaluate(self, data: GpxFile):
        # fig, ax = plt.subplots()

        fig = plt.figure()
        ax = fig.add_subplot(111)

        df = data.df[['Point_Longitude', 'Point_Latitude']].dropna()
        ax.plot(df['Point_Longitude'],
                df['Point_Latitude'],
                color="#00A6ED",
                linewidth=3,
                alpha=0.9)
        val = mplleaflet.fig_to_html(fig=fig)  # , tiles='esri_aerial')
        """
        attribution = _attribution + ' | ' + tiles[1]
        attribution = "" # :(
        """
        # print(val)
        return val, InlineHTML(val)
Beispiel #4
0
boston_polygon = shapely.ops.cascaded_union(census_tracts.geometry.values)


# Plot the data.

# We're building a webmap, so we'll first create an unprojected map.
ax = gplt.kdeplot(listings)
gplt.polyplot(gpd.GeoSeries([boston_polygon]), edgecolor='white', linewidth=4, ax=ax)

# Now we'll output this map to mplleaflet to generate our webmap. In this example we'll actually go one step further,
# and use a non-default tile layer as well. The default mplleaflet webmap uses the default Leaflet tile service,
# which is Open Street Map (OSM). OSM works great in a lot of cases, but tends to be very busy at a local level (an
# actual strategic choice on the part of the OSM developers, as the higher visibility rewards contributions to the
# project).
#
# Luckily Leaflet (and, by extension, mplleaflet) can be made to work with any valid time service. To do this we can use
# the mplleaflet.fig_to_html method, which creates a string (which we'll write to a file) containing our desired
# data. Here is the method signature that we need:
# >>> mplleaflet.fig_to_html(<matplotlib.Figure>, tiles=(<tile url>, <attribution string>)
# For this demo we'll use the super-basic Hydda.Base tile layer.
#
# For a list of possible valid inputs:
# https://leaflet-extras.github.io/leaflet-providers/preview/
# For the full fig_to_html method signature run mplleaflet.fig_to_html? in IPython or see further:
# https://github.com/jwass/mplleaflet/blob/master/mplleaflet/_display.py#L26
fig = plt.gcf()
with open("boston_kde.html", 'w') as f:
    f.write(
        mplleaflet.fig_to_html(fig, tiles=('http://{s}.tile.openstreetmap.se/hydda/base/{z}/{x}/{y}.png',
                                       'Tiles courtesy of <a href="http://openstreetmap.se/" target="_blank">OpenStreetMap Sweden</a> &mdash; Map data &copy; <a href="http://www.openstreetmap.org/copyright">OpenStreetMap</a>'))
    )
Beispiel #5
0
ax = gplt.kdeplot(listings)
gplt.polyplot(gpd.GeoSeries([boston_polygon]),
              edgecolor='white',
              linewidth=4,
              ax=ax)

# Now we'll output this map to mplleaflet to generate our webmap. In this example we'll actually go one step further,
# and use a non-default tile layer as well. The default mplleaflet webmap uses the default Leaflet tile service,
# which is Open Street Map (OSM). OSM works great in a lot of cases, but tends to be very busy at a local level (an
# actual strategic choice on the part of the OSM developers, as the higher visibility rewards contributions to the
# project).
#
# Luckily Leaflet (and, by extension, mplleaflet) can be made to work with any valid time service. To do this we can use
# the mplleaflet.fig_to_html method, which creates a string (which we'll write to a file) containing our desired
# data. Here is the method signature that we need:
# >>> mplleaflet.fig_to_html(<matplotlib.Figure>, tiles=(<tile url>, <attribution string>)
# For this demo we'll use the super-basic Hydda.Base tile layer.
#
# For a list of possible valid inputs:
# https://leaflet-extras.github.io/leaflet-providers/preview/
# For the full fig_to_html method signature run mplleaflet.fig_to_html? in IPython or see further:
# https://github.com/jwass/mplleaflet/blob/master/mplleaflet/_display.py#L26
fig = plt.gcf()
with open("boston_kde.html", 'w') as f:
    f.write(
        mplleaflet.fig_to_html(
            fig,
            tiles=
            ('http://{s}.tile.openstreetmap.se/hydda/base/{z}/{x}/{y}.png',
             'Tiles courtesy of <a href="http://openstreetmap.se/" target="_blank">OpenStreetMap Sweden</a> &mdash; Map data &copy; <a href="http://www.openstreetmap.org/copyright">OpenStreetMap</a>'
             )))
Beispiel #6
0
def test_scatter():
    plt.scatter([0, 10, 0, 10], [0, 0, 10, 10], c=[1, 2, 3, 4])
    mplleaflet.fig_to_html()
Beispiel #7
0
def test_basic():
    plt.plot([0, 0], [1, 1])
    mplleaflet.fig_to_html()
def test_basic_tiles():
    plt.plot([0, 1], [0, 1])
    mplleaflet.fig_to_html(tiles='osm')
def test_basic():
    plt.plot([0, 1], [0, 1])
    mplleaflet.fig_to_html()
def test_scatter():
    plt.scatter([0, 10, 0, 10], [0, 0, 10, 10], c=[1, 2, 3, 4])
    mplleaflet.fig_to_html()