flask_plots package

Submodules

flask_plots.core module

Flask-Plots.

Implementation of Matplotlib in Flask.

raise_helper(message)[source]

Handle for raise in jinja templates.

class Plots(app=None)[source]

Bases: object

Base extension class for different Plots versions.

New in version 0.0.1.

static_folder = 'plots'
init_app(app)[source]

Sample factory function for initialize the extension.

get_data(fig, fmt='png', decode='ascii')[source]

Create a data for embed the result in the html output.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • format (str, default: "png") – A extension type for the images.

  • decode (str, default: "ascii") – A buffer decode.

hist(fig, x, ax=None, hist_kws=None)[source]

Plot a histogram using Matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x ((n,) array or sequence of (n,) arrays) – Input values, this takes either a single array or a sequence of arrays which are not required to be of the same length.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • hist_kwargs (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

errorbar(fig, x, y, ax=None, errorbar_kws=None)[source]

Plot y versus x as lines and/or markers with attached errorbars.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (float or array-like) – The data positions.

  • y (float or array-like) – The data positions.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • errorbar_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

violinplot(fig, dataset, positions, ax=None, violinplot_kws=None)[source]

Make a violin plot using Matlotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • dataset (Array or a sequence of vectors.) – The input data.

  • positions (array-like, default: [1, 2, ..., n]) – The positions of the violins. The ticks and limits are automatically set to match the positions.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • violinplot_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

eventplot(fig, positions, ax=None, eventplot_kws=None)[source]

Plot identical parallel lines at the given positions.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • positions (array-like or list of array-like) – A 1D array-like defines the positions of one sequence of events. Multiple groups of events may be passed as a list of array-likes. Each group can be styled independently by passing lists of values to lineoffsets, linelengths, linewidths, colors and linestyles. Note that positions can be a 2D array, but in practice different event groups usually have different counts so that one will use a list of different-length arrays rather than a 2D array.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • eventplot_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

hist2d(fig, x, y, ax=None, hist2d_kws=None)[source]

Make a 2D histogram plot using Matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (array-like, shape (n, )) – Input values

  • y (array-like, shape (n, )) – Input values

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • hist2d_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

hexbin(fig, x, y, ax=None, hexbin_kws=None)[source]

Make a 2D hexagonal binning plot of points x, y using Matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (array-like) – The data positions. x and y must be of the same length.

  • y (array-like) – The data positions. x and y must be of the same length.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • hexbin_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

scatter_hist2d(fig, x, y, ax=None, hist2d_kws=None, scatter_kws=None)[source]

Make a 2D histogram plot using Matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (array-like, shape (n, )) – Input values

  • y (array-like, shape (n, )) – Input values

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • hist2d_kws (dict or None (optional)) – The parameters to send to the data plot.

  • scatter_kws (dict or None (optional)) – The parameters to send to the data plot in term scatter method.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

scatter_hexbin(fig, x, y, ax=None, hexbin_kws=None, scatter_kws=None)[source]

Make a 2D scatter-hexagonal binning plot of points x, y.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (array-like) – The data positions. x and y must be of the same length.

  • y (array-like) – The data positions. x and y must be of the same length.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • hexbin_kws (dict or None (optional)) – The parameters to send to the data plot in term hexbin method.

  • scatter_kws (dict or None (optional)) – The parameters to send to the data plot in term scatter method.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

bar(fig, x, bar_height=None, ax=None, bar_kws=None)[source]

Make a bar plot using Matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (float or array-like) – The x coordinates of the bars. See also align for the alignment of the bars to the coordinates.

  • bar_height (float or array-like,) – The height(s) of the bars. You can config this value using app.config["BAR_HEIGHT"].

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • bar_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

pie(fig, x, ax=None, pie_kws=None)[source]

Make a pie plot using Matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (1D array-like) – The wedge sizes.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • bar_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

boxplot(fig, x, ax=None, boxplot_kws=None)[source]

Draw a box and whisker plot using MAtplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (Array or a sequence of vectors.) – The input data. If a 2D array, a boxplot is drawn for each column in x. If a sequence of 1D arrays, a boxplot is drawn for each array in x.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • boxplot_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

quiver(fig, x, y, u, v, ax=None, quiver_kws=None)[source]

Plot a 2D field of arrows using matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (1D or 2D array-like, optional) – The x and y coordinates of the arrow locations. If not given, they will be generated as a uniform integer meshgrid based on the dimensions of u and v. If x and y are 1D but u, v are 2D, x, y are expanded to 2D using x, y = np.meshgrid(x, y). In this case len(x) and len(y) must match the column and row dimensions of u and v.

  • y (1D or 2D array-like, optional) – The x and y coordinates of the arrow locations. If not given, they will be generated as a uniform integer meshgrid based on the dimensions of u and v. If x and y are 1D but u, v are 2D, x, y are expanded to 2D using x, y = np.meshgrid(x, y). In this case len(x) and len(y) must match the column and row dimensions of u and v.

  • u (1D or 2D array-like) – The x and y direction components of the arrow vectors. They must have the same number of elements, matching the number of arrow locations. u and v may be masked. Only locations unmasked in u, v, and C will be drawn.

  • v (1D or 2D array-like) – The x and y direction components of the arrow vectors. They must have the same number of elements, matching the number of arrow locations. u and v may be masked. Only locations unmasked in u, v, and C will be drawn.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • quiver_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

streamplot(fig, x, y, u, v, ax=None, streamplot_kws=None)[source]

Draw streamlines of a vector flow using matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (1D/2D arrays) – Evenly spaced strictly increasing arrays to make a grid. If 2D, all rows of x must be equal and all columns of y must be equal; i.e., they must be as if generated by np.meshgrid(x_1d, y_1d).

  • y (1D/2D arrays) – Evenly spaced strictly increasing arrays to make a grid. If 2D, all rows of x must be equal and all columns of y must be equal; i.e., they must be as if generated by np.meshgrid(x_1d, y_1d).

  • u (2D arrays) – x and y-velocities. The number of rows and columns must match the length of y and x, respectively.

  • v (2D arrays) – x and y-velocities. The number of rows and columns must match the length of y and x, respectively.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • streamplot_kws (dict or None (optional)) – The parameters to send to the data plot.

contourf(fig, x, y, z, levels, ax=None, contourf_kws=None)[source]

Plot contour lines using matplotlib.

Parameters

  • fig (matplotlib.Figure) – A instance of Figure Object.

  • x (array-like, optional) –

    The coordinates of the values in z.

    x and y must both be 2D with the same shape as z (e.g. created via numpy.meshgrid), or they must both be 1-D such that len(x) == N is the number of columns in z and len(y) == M is the number of rows in z.

    X and Y must both be ordered monotonically.

    If not given, they are assumed to be integer indices, i.e. x = range(N), y = range(M).

  • y (array-like, optional) –

    The coordinates of the values in z.

    x and y must both be 2D with the same shape as z (e.g. created via numpy.meshgrid), or they must both be 1-D such that len(x) == N is the number of columns in z and len(y) == M is the number of rows in z.

    X and Y must both be ordered monotonically.

    If not given, they are assumed to be integer indices, i.e. x = range(N), y = range(M).

  • levels (int or array-like, optional) –

    Determines the number and positions of the contour lines / regions.

    If an int n, use ~matplotlib.ticker.MaxNLocator, which tries to automatically choose no more than n+1 “nice” contour levels between vmin and vmax.

    If array-like, draw contour lines at the specified levels. The values must be in increasing order.

  • ax (matplotlib.Figure.Axis, (optional)) – A matplotlib axis.

  • contourf_kws (dict or None (optional)) – The parameters to send to the data plot.

Returns

ax – A matplotlib axis.

Return type

matplotlib.Figure.Axis

Module contents

Flask-Plots.

Implementation of Plots in Flask.