Python plotly.graph_objects.Heatmap() Examples
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code examples of plotly.graph_objects.Heatmap().
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Example #1
Source File: basic.py From vectorbt with GNU General Public License v3.0 | 6 votes |
def update_data(self, data): """Update the data of the plot efficiently. Args: data (array_like): Data in any format that can be converted to NumPy. Must be of shape (any, `trace_names`). """ data = reshape_fns.to_2d(np.asarray(data)) checks.assert_same_shape(data, self._trace_names, axis=(1, 0)) # Update traces with self.batch_update(): for i, box in enumerate(self.data): if self._horizontal: box.x = data[:, i] box.y = None else: box.x = None box.y = data[:, i] # ############# Heatmap ############# #
Example #2
Source File: basic.py From vectorbt with GNU General Public License v3.0 | 5 votes |
def __init__(self, x_labels, y_labels, data=None, horizontal=False, trace_kwargs={}, **layout_kwargs): """Create an updatable heatmap plot. Args: x_labels (list of str): X-axis labels, corresponding to columns in pandas. y_labels (list of str): Y-axis labels, corresponding to index in pandas. data (array_like): Data in any format that can be converted to NumPy. horizontal (bool): Plot horizontally. trace_kwargs (dict): Keyword arguments passed to `plotly.graph_objects.Heatmap`. **layout_kwargs: Keyword arguments for layout. Example: ```py vbt.Heatmap(['a', 'b'], ['x', 'y'], data=[[1, 2], [3, 4]]) ``` ![](/vectorbt/docs/img/Heatmap.png) """ self._x_labels = x_labels self._y_labels = y_labels self._horizontal = horizontal super().__init__() self.update_layout(**layout_kwargs) # Add traces heatmap = go.Heatmap( hoverongaps=False, colorscale='Plasma' ) if self._horizontal: heatmap.y = x_labels heatmap.x = y_labels else: heatmap.x = x_labels heatmap.y = y_labels heatmap.update(**trace_kwargs) self.add_trace(heatmap) if data is not None: self.update_data(data)
Example #3
Source File: visualization.py From AeroSandbox with MIT License | 4 votes |
def spy( matrix, show=True, ): """ Plots the sparsity pattern of a matrix. :param matrix: The matrix to plot the sparsity pattern of. [2D ndarray or CasADi array] :param show: Whether or not to show the sparsity plot. [boolean] :return: The figure to be plotted [go.Figure] """ try: matrix = matrix.toarray() except: pass abs_m = np.abs(matrix) sparsity_pattern = abs_m >= 1e-16 matrix[sparsity_pattern] = np.log10(abs_m[sparsity_pattern] + 1e-16) j_index_map, i_index_map = np.meshgrid(np.arange(matrix.shape[1]), np.arange(matrix.shape[0])) i_index = i_index_map[sparsity_pattern] j_index = j_index_map[sparsity_pattern] val = matrix[sparsity_pattern] val = np.ones_like(i_index) fig = go.Figure( data=go.Heatmap( y=i_index, x=j_index, z=val, # type='heatmap', colorscale='RdBu', showscale=False, ), ) fig.update_layout( plot_bgcolor="black", xaxis=dict(showgrid=False, zeroline=False), yaxis=dict(showgrid=False, zeroline=False, autorange="reversed", scaleanchor="x", scaleratio=1), width=800, height=800 * (matrix.shape[0] / matrix.shape[1]), ) if show: fig.show() return fig