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| import numpy as np |
| import matplotlib.pyplot as plt |
| import matplotlib.gridspec as gridspec |
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| def heatmap(ax, mat, title=None, x_label=None, y_label=None, show_bar=True, close_ticks=False): |
| cmap = "Reds" |
| vmin, vmax = 0, 0.5 |
| im = ax.matshow(mat, interpolation='nearest', cmap=cmap, aspect='auto', vmin=vmin, vmax=vmax) |
| if show_bar: |
| cbar = plt.colorbar(im, ax=ax, aspect=9, shrink=0.3, ticks=[vmin, vmax]) |
| cbar.ax.yaxis.set_ticks_position('none') |
| cbar.ax.set_yticklabels([]) |
| cbar.ax.set_xlabel('Low', fontsize='large') |
| cbar.ax.set_title('High', fontsize='large') |
| cbar.ax.set_ylabel('reads', rotation=-90, va='bottom', fontsize='x-large') |
| if close_ticks: |
| ax.set_xticks([]) |
| ax.set_yticks([]) |
| if title is not None: |
| ax.set_title(title) |
| if x_label is not None: |
| ax.set_xlabel(x_label) |
| if y_label is not None: |
| ax.set_ylabel(y_label) |
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| return im |
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| def hic_heatmap(data, dediag=0, ncols=1, titles=None, x_labels=None, y_labels=None, file=None): |
| if isinstance(data, list): |
| axs = [] |
| nrows = int(len(data) // ncols + 1) |
| figure = plt.figure(facecolor='w', figsize=(4.9 * ncols, 4 * nrows)) |
| gs = gridspec.GridSpec(nrows, ncols) |
| for i, mat in enumerate(data): |
| row, col = i // ncols, i % ncols |
| axs.append(figure.add_subplot(gs[row, col])) |
| if dediag > 0 and mat.ndim == 2: |
| mat = np.triu(mat, dediag) + np.triu(mat.T, dediag).T |
| |
| title = titles[col] if titles is not None else None |
| y_label = y_labels[row] if col == 0 and y_labels is not None else None |
| x_label = x_labels[col] if row == 0 and x_labels is not None else None |
| heatmap(axs[-1], mat, title, x_label, y_label) |
| else: |
| figure = plt.figure(facecolor='w') |
| ax = figure.add_subplot(1, 1, 1) |
| if dediag > 0: |
| data = np.triu(data, dediag) + np.triu(data.T, dediag).T |
| heatmap(ax, data, title=titles, x_label=x_labels, y_label=y_labels) |
| figure.tight_layout() |
| if file is not None: |
| figure.savefig(file, format='svg') |
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|
| def surf(data): |
| fig = plt.figure() |
| ax = fig.gca(projection='3d') |
| m, n = data.shape |
| x, y = np.meshgrid(range(m), range(n)) |
| ax.plot_surface(x, y, data) |
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|
| def _clear_max_min(x, y): |
| idx_x = np.where((x > x.min()) & (x < x.max()))[0] |
| idx_y = np.where((y > y.min()) & (y < y.max()))[0] |
| idx_setx, idx_sety = set(idx_x), set(idx_y) |
| inter_idx = np.array(list(idx_setx.intersection(idx_sety))) |
| return x[inter_idx], y[inter_idx] |
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