python类AutoDateLocator()的实例源码

def get_locator(self, dmin, dmax):
        'Pick the best locator based on a distance.'
        delta = relativedelta(dmax, dmin)

        num_days = ((delta.years * 12.0) + delta.months * 31.0) + delta.days
        num_sec = (delta.hours * 60.0 + delta.minutes) * 60.0 + delta.seconds
        tot_sec = num_days * 86400. + num_sec

        if abs(tot_sec) < self.minticks:
            self._freq = -1
            locator = MilliSecondLocator(self.tz)
            locator.set_axis(self.axis)

            locator.set_view_interval(*self.axis.get_view_interval())
            locator.set_data_interval(*self.axis.get_data_interval())
            return locator

        return dates.AutoDateLocator.get_locator(self, dmin, dmax)

def plot_states_and_var(data, hidden_states, cmap=None, columns=None, by='Activity'):
    """
    Make  a plot of the data and the states

    Parameters
    ----------
    data : pandas DataFrame
        Data to plot
    hidden_states: iteretable
        the hidden states corresponding to the timesteps
    columns : list, optional
        Which columns to plot
    by : str
        The column to group on
    """
    fig, ax = plt.subplots(figsize=(15, 5))
    if columns is None:
        columns = data.columns
    df = data[columns].copy()
    stateseq = np.array(hidden_states)
    stateseq_norep, durations = rle(stateseq)
    datamin, datamax = np.array(df).min(), np.array(df).max()
    y = np.array(
        [datamin, datamax])
    maxstate = stateseq.max() + 1
    x = np.hstack(([0], durations.cumsum()[:-1], [len(df.index) - 1]))
    C = np.array(
        [[float(state) / maxstate] for state in stateseq_norep]).transpose()
    ax.set_xlim((min(x), max(x)))

    if cmap is None:
        num_states = max(hidden_states) + 1
        colormap, cmap = get_color_map(num_states)
    pc = ax.pcolorfast(x, y, C, vmin=0, vmax=1, alpha=0.3, cmap=cmap)
    plt.plot(df.as_matrix())
    locator = AutoDateLocator()
    locator.create_dummy_axis()
    num_index = pd.Index(df.index.map(date2num))
    ticks_num = locator.tick_values(min(df.index), max(df.index))
    ticks = [num_index.get_loc(t) for t in ticks_num]
    plt.xticks(ticks, df.index.strftime('%H:%M')[ticks], rotation='vertical')
    cb = plt.colorbar(pc)
    cb.set_ticks(np.arange(1./(2*cmap.N), 1, 1./cmap.N))
    cb.set_ticklabels(np.arange(0, cmap.N))
    # Plot the activities
    if by is not None:
        actseq = np.array(data[by])
        sca = ax.scatter(
            np.arange(len(hidden_states)), #data.index,
            np.ones_like(hidden_states) * datamax,
            c=actseq,
            edgecolors='none'
        )
    plt.show()
    return fig, ax

def line_2subplots():
    """
    Creates a split plot with one set of x axis labels and
    two subplots.

    """

# Save data to redraw plot later

    save_data('line_2subplots')

# set the screen title, size, density

    fig = plt.figure(title,graph_dimensions,graph_dpi)

# do the plot
# top half of the graph plot_number 1
    nrows = 2
    ncols = 1
    plot_number = 1   
    ax = plt.subplot(nrows,ncols,plot_number)
    plt.title(title)
    plt.ylabel(ylabel1)
    plt.grid(which="major")
    red = 'r'
    plt.plot(xdatetimes,ylists[0],red)
    plt.autoscale(tight=True)
    fig.autofmt_xdate()
    ax.fmt_xdata = mdates.DateFormatter('%m/%d/%Y %H:%M')
    datetimefmt = mdates.DateFormatter('')
    ax.xaxis.set_major_formatter(datetimefmt)
# bottom half of the graph plot_number 2
    plot_number = 2   
    ax = plt.subplot(nrows,ncols,plot_number)
    plt.ylabel(ylabel2)
    plt.grid(which="major")
    green='g'
    plt.plot(xdatetimes,ylists[1],green)
    plt.autoscale(tight=True)
    fig.autofmt_xdate()
    ax.fmt_xdata = mdates.DateFormatter('%m/%d/%Y %H:%M')
    loc=mdates.AutoDateLocator()
    datetimefmt = mdates.AutoDateFormatter(loc)
    ax.xaxis.set_major_formatter(datetimefmt)
    ax.xaxis.set_major_locator(loc)

# subplots_adjust settings
    vleft  = 0.07  # the left side of the subplots of the figure
    vright = 0.97    # the right side of the subplots of the figure
#    vbottom = 0.15   # the bottom of the subplots of the figure
    vbottom = 0.10   # the bottom of the subplots of the figure
    vtop = 0.95      # the top of the subplots of the figure
    vwspace = 0.0   # the amount of width reserved for blank space between subplots
    vhspace = 0.08   # the amount of height reserved for white space between subplots

    plt.subplots_adjust(left=vleft,right=vright,bottom=vbottom,top=vtop,wspace=vwspace,hspace=vhspace)


    fileorscreen(title+'.png')

    return

def line():
    """
    Creates a single graph with date and time as the x axis and
    a variable number of plots.

    """

# Save data to redraw plot later

    save_data('line')

# set the screen title, size, density

    fig = plt.figure(title,graph_dimensions,graph_dpi)

# do the plot
    plt.title(title)
    plt.ylabel(ylabel1)
    plt.grid(which="major")

    for plot_num in range(len(ylists)):
         plt.plot(xdatetimes,ylists[plot_num],color=my_colors(plot_num))

# date time formatting

    ax = plt.axes()
    fig.autofmt_xdate()
    ax.fmt_xdata = mdates.DateFormatter('%m/%d/%Y %H:%M')
    loc=mdates.AutoDateLocator()
    datetimefmt = mdates.AutoDateFormatter(loc)
    ax.xaxis.set_major_formatter(datetimefmt)
    ax.xaxis.set_major_locator(loc)

# other formatting

    plt.legend(ylistlabels,loc='upper left')
    plt.autoscale(tight=True)

    # subplots_adjust settings - single plot so zero space between plots
    vleft  = 0.06  # the left side of the subplots of the figure
    vright = 0.97    # the right side of the subplots of the figure
    vbottom = 0.12   # the bottom of the subplots of the figure
    vtop = 0.95      # the top of the subplots of the figure
    vwspace = 0.0   # the amount of width reserved for blank space between subplots
    vhspace = 0.0   # the amount of height reserved for white space between subplots

    plt.subplots_adjust(left=vleft,right=vright,bottom=vbottom,top=vtop,wspace=vwspace,hspace=vhspace)

    fileorscreen(title+'.png')

    return