Python matplotlib.pyplot.axes() Examples
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Example #1
Source File: tutorial.py From feets with MIT License | 8 votes |
def ts_anim(): # create a simple animation fig = plt.figure() ax = plt.axes(xlim=(0, 100), ylim=(-1, 1)) Color = [ 1 ,0.498039, 0.313725]; line, = ax.plot([], [], '*',color = Color) plt.xlabel("Time") plt.ylabel("Measurement") def init(): line.set_data([], []) return line, def animate(i): x = np.linspace(0, i+1, i+1) ts = 5*np.cos(x * 0.02 * np.pi) * np.sin(np.cos(x) * 0.02 * np.pi) line.set_data(x, ts) return line, return animation.FuncAnimation(fig, animate, init_func=init, frames=100, interval=200, blit=True)
Example #2
Source File: main.py From wechat-analyse with MIT License | 7 votes |
def analyseSex(firends): sexs = list(map(lambda x:x['Sex'],friends[1:])) counts = Counter(sexs).items() counts = sorted(counts, key=lambda x:x[0], reverse=False) counts = list(map(lambda x:x[1],counts)) labels = ['Unknow','Male','Female'] colors = ['red','yellowgreen','lightskyblue'] plt.figure(figsize=(8,5), dpi=80) plt.axes(aspect=1) plt.pie(counts, labels=labels, colors=colors, labeldistance = 1.1, autopct = '%3.1f%%', shadow = False, startangle = 90, pctdistance = 0.6 ) plt.legend(loc='upper right',) plt.title(u'%s的微信好友性别组成' % friends[0]['NickName']) plt.show()
Example #3
Source File: tf_gmm_tools.py From tf-example-models with Apache License 2.0 | 7 votes |
def _plot_gaussian(mean, covariance, color, zorder=0): """Plots the mean and 2-std ellipse of a given Gaussian""" plt.plot(mean[0], mean[1], color[0] + ".", zorder=zorder) if covariance.ndim == 1: covariance = np.diag(covariance) radius = np.sqrt(5.991) eigvals, eigvecs = np.linalg.eig(covariance) axis = np.sqrt(eigvals) * radius slope = eigvecs[1][0] / eigvecs[1][1] angle = 180.0 * np.arctan(slope) / np.pi plt.axes().add_artist(pat.Ellipse( mean, 2 * axis[0], 2 * axis[1], angle=angle, fill=False, color=color, linewidth=1, zorder=zorder ))
Example #4
Source File: examples.py From feets with MIT License | 7 votes |
def basic_animation(frames=100, interval=30): """Plot a basic sine wave with oscillating amplitude""" fig = plt.figure() ax = plt.axes(xlim=(0, 10), ylim=(-2, 2)) line, = ax.plot([], [], lw=2) x = np.linspace(0, 10, 1000) def init(): line.set_data([], []) return line, def animate(i): y = np.cos(i * 0.02 * np.pi) * np.sin(x - i * 0.02 * np.pi) line.set_data(x, y) return line, return animation.FuncAnimation(fig, animate, init_func=init, frames=frames, interval=interval)
Example #5
Source File: view_geometry.py From geomeppy with MIT License | 6 votes |
def view_polygons(polygons): """Display a collection of polygons for inspection. :param polygons: A dict keyed by colour, containing Polygon3D objects to show in that colour. """ # create the figure and add the surfaces plt.figure() ax = plt.axes(projection="3d") collections = _make_collections(polygons, opacity=0.5) for c in collections: ax.add_collection3d(c) # calculate and set the axis limits limits = _get_limits(polygons=polygons) ax.set_xlim(limits["x"]) ax.set_ylim(limits["y"]) ax.set_zlim(limits["z"]) plt.show()
Example #6
Source File: test1.py From pyeo with GNU General Public License v3.0 | 6 votes |
def blank_axes(ax): """ blank_axes: blank the extraneous spines and tick marks for an axes Input: ax: a matplotlib Axes object Output: None """ ax.spines['right'].set_visible(False) ax.spines['top'].set_visible(False) ax.spines['bottom'].set_visible(False) ax.spines['left'].set_visible(False) ax.yaxis.set_ticks_position('none') ax.xaxis.set_ticks_position('none') ax.tick_params(labelbottom='off', labeltop='off', labelleft='off', labelright='off', \ bottom='off', top='off', left='off', right='off') # end blank_axes ####################################################### # MAIN #######################################################
Example #7
Source File: helper_functions.py From pylustrator with GNU General Public License v3.0 | 6 votes |
def add_axes(dim: Sequence, unit: str = "cm", *args, **kwargs): """ add an axes with dimensions specified in cm """ fig = plt.gcf() x, y, w, h = dim if unit == "cm": x = x / 2.54 / fig.get_size_inches()[0] y = y / 2.54 / fig.get_size_inches()[1] w = w / 2.54 / fig.get_size_inches()[0] h = h / 2.54 / fig.get_size_inches()[1] if x < 0: x += 1 if y < 0: y += 1 return plt.axes([x, y, w, h], *args, **kwargs)
Example #8
Source File: example7.py From bert-as-service with MIT License | 6 votes |
def vis(embed, vis_alg='PCA', pool_alg='REDUCE_MEAN'): plt.close() fig = plt.figure() plt.rcParams['figure.figsize'] = [21, 7] for idx, ebd in enumerate(embed): ax = plt.subplot(2, 6, idx + 1) vis_x = ebd[:, 0] vis_y = ebd[:, 1] plt.scatter(vis_x, vis_y, c=subset_label, cmap=ListedColormap(["blue", "green", "yellow", "red"]), marker='.', alpha=0.7, s=2) ax.set_title('pool_layer=-%d' % (idx + 1)) plt.tight_layout() plt.subplots_adjust(bottom=0.1, right=0.95, top=0.9) cax = plt.axes([0.96, 0.1, 0.01, 0.3]) cbar = plt.colorbar(cax=cax, ticks=range(num_label)) cbar.ax.get_yaxis().set_ticks([]) for j, lab in enumerate(['ent.', 'bus.', 'sci.', 'heal.']): cbar.ax.text(.5, (2 * j + 1) / 8.0, lab, ha='center', va='center', rotation=270) fig.suptitle('%s visualization of BERT layers using "bert-as-service" (-pool_strategy=%s)' % (vis_alg, pool_alg), fontsize=14) plt.show()
Example #9
Source File: burst_plot.py From FRETBursts with GNU General Public License v2.0 | 6 votes |
def _alex_plot_style(g, colorbar=True): """Set plot style and colorbar for an ALEX joint plot. """ g.set_axis_labels(xlabel="E", ylabel="S") g.ax_marg_x.grid(True) g.ax_marg_y.grid(True) g.ax_marg_x.set_xlabel('') g.ax_marg_y.set_ylabel('') plt.setp(g.ax_marg_y.get_xticklabels(), visible=True) plt.setp(g.ax_marg_x.get_yticklabels(), visible=True) g.ax_marg_x.locator_params(axis='y', tight=True, nbins=3) g.ax_marg_y.locator_params(axis='x', tight=True, nbins=3) if colorbar: pos = g.ax_joint.get_position().get_points() X, Y = pos[:, 0], pos[:, 1] cax = plt.axes([1., Y[0], (X[1] - X[0]) * 0.045, Y[1] - Y[0]]) plt.colorbar(cax=cax)
Example #10
Source File: caltable.py From eht-imaging with GNU General Public License v3.0 | 6 votes |
def plot_dterms(self, sites='all', label=None, legend=True, clist=ehc.SCOLORS, rangex=False, rangey=False, markersize=2 * ehc.MARKERSIZE, show=True, grid=True, export_pdf=""): # sites if sites in ['all' or 'All'] or sites == []: sites = list(self.data.keys()) if not isinstance(sites, list): sites = [sites] keys = [self.tkey[site] for site in sites] axes = plot_tarr_dterms(self.tarr, keys=keys, label=label, legend=legend, clist=clist, rangex=rangex, rangey=rangey, markersize=markersize, show=show, grid=grid, export_pdf=export_pdf) return axes
Example #11
Source File: solver.py From osim-rl with MIT License | 6 votes |
def plot_convergence(self, filename=None): yy = self.iter_values xx = range(len(yy)) import matplotlib.pyplot as plt # Plot plt.ioff() fig = plt.figure() fig.set_size_inches(18.5, 10.5) font = {'size': 28} plt.title('Value over # evaluations') plt.xlabel('X', fontdict=font) plt.ylabel('Y', fontdict=font) plt.plot(xx, yy) plt.axes().set_yscale('log') if filename is None: filename = 'plots/iter.png' plt.savefig(filename, bbox_inches='tight') plt.close(fig) print('plotting convergence OK.. ' + filename)
Example #12
Source File: ephys_qc_raw.py From ibllib with MIT License | 6 votes |
def _plot_rmsmap(outfil, typ, savefig=True): rmsmap = alf.io.load_object(outpath, '_iblqc_ephysTimeRms' + typ.upper()) plt.figure(figsize=[12, 4.5]) axim = plt.axes([0.2, 0.1, 0.7, 0.8]) axrms = plt.axes([0.05, 0.1, 0.15, 0.8]) axcb = plt.axes([0.92, 0.1, 0.02, 0.8]) axrms.plot(np.median(rmsmap['rms'], axis=0)[:-1] * 1e6, np.arange(1, rmsmap['rms'].shape[1])) axrms.set_ylim(0, rmsmap['rms'].shape[1]) im = axim.imshow(20 * np.log10(rmsmap['rms'].T + 1e-15), aspect='auto', origin='lower', extent=[rmsmap['timestamps'][0], rmsmap['timestamps'][-1], 0, rmsmap['rms'].shape[1]]) axim.set_xlabel(r'Time (s)') axim.set_ylabel(r'Channel Number') plt.colorbar(im, cax=axcb) if typ == 'ap': im.set_clim(-110, -90) axrms.set_xlim(100, 0) elif typ == 'lf': im.set_clim(-100, -60) axrms.set_xlim(500, 0) axim.set_xlim(0, 4000) if savefig: plt.savefig(outpath / (typ + '_rms.png'), dpi=150)
Example #13
Source File: test_axes.py From neural-network-animation with MIT License | 6 votes |
def test_polar_wrap(): D2R = np.pi / 180.0 fig = plt.figure() plt.subplot(111, polar=True) plt.polar([179*D2R, -179*D2R], [0.2, 0.1], "b.-") plt.polar([179*D2R, 181*D2R], [0.2, 0.1], "g.-") plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3]) assert len(fig.axes) == 1, 'More than one polar axes created.' fig = plt.figure() plt.subplot(111, polar=True) plt.polar([2*D2R, -2*D2R], [0.2, 0.1], "b.-") plt.polar([2*D2R, 358*D2R], [0.2, 0.1], "g.-") plt.polar([358*D2R, 2*D2R], [0.2, 0.1], "r.-") plt.rgrids([0.05, 0.1, 0.15, 0.2, 0.25, 0.3])
Example #14
Source File: pixel.py From yatsm with MIT License | 6 votes |
def plot_DOY(dates, y, mpl_cmap): """ Create a DOY plot Args: dates (iterable): sequence of datetime y (np.ndarray): variable to plot mpl_cmap (colormap): matplotlib colormap """ doy = np.array([d.timetuple().tm_yday for d in dates]) year = np.array([d.year for d in dates]) sp = plt.scatter(doy, y, c=year, cmap=mpl_cmap, marker='o', edgecolors='none', s=35) plt.colorbar(sp) months = mpl.dates.MonthLocator() # every month months_fmrt = mpl.dates.DateFormatter('%b') plt.tick_params(axis='x', which='minor', direction='in', pad=-10) plt.axes().xaxis.set_minor_locator(months) plt.axes().xaxis.set_minor_formatter(months_fmrt) plt.xlim(1, 366) plt.xlabel('Day of Year')
Example #15
Source File: tf_gmm.py From tf-example-models with Apache License 2.0 | 6 votes |
def plot_fitted_data(points, c_means, c_variances): """Plots the data and given Gaussian components""" plt.plot(points[:, 0], points[:, 1], "b.", zorder=0) plt.plot(c_means[:, 0], c_means[:, 1], "r.", zorder=1) for i in range(c_means.shape[0]): std = np.sqrt(c_variances[i]) plt.axes().add_artist(pat.Ellipse( c_means[i], 2 * std[0], 2 * std[1], fill=False, color="red", linewidth=2, zorder=1 )) plt.show() # PREPARING DATA # generating DATA_POINTS points from a GMM with COMPONENTS components
Example #16
Source File: utils.py From tf-example-models with Apache License 2.0 | 6 votes |
def _plot_gaussian(mean, covariance, color, zorder=0): """Plots the mean and 2-std ellipse of a given Gaussian""" plt.plot(mean[0], mean[1], color[0] + ".", zorder=zorder) if covariance.ndim == 1: covariance = np.diag(covariance) radius = np.sqrt(5.991) eigvals, eigvecs = np.linalg.eig(covariance) axis = np.sqrt(eigvals) * radius slope = eigvecs[1][0] / eigvecs[1][1] angle = 180.0 * np.arctan(slope) / np.pi plt.axes().add_artist(pat.Ellipse( mean, 2 * axis[0], 2 * axis[1], angle=angle, fill=False, color=color, linewidth=1, zorder=zorder ))
Example #17
Source File: view_geometry.py From geomeppy with MIT License | 6 votes |
def _get_limits(idf=None, polygons=None): """Get limits for the x, y and z axes so the plot is fitted to the axes.""" if polygons: x = [pt[0] for color in polygons for p in polygons[color] for pt in p] y = [pt[1] for color in polygons for p in polygons[color] for pt in p] z = [pt[2] for color in polygons for p in polygons[color] for pt in p] elif idf: surfaces = _get_surfaces(idf) x = [pt[0] for s in surfaces for pt in getcoords(s)] y = [pt[1] for s in surfaces for pt in getcoords(s)] z = [pt[2] for s in surfaces for pt in getcoords(s)] if all([x, y, z]): max_delta = max((max(x) - min(x)), (max(y) - min(y)), (max(z) - min(z))) limits = { "x": (min(x), min(x) + max_delta), "y": (min(y), min(y) + max_delta), "z": (min(z), min(y) + max_delta), } else: limits = {"x": (0, 0), "y": (0, 0), "z": (0, 0)} return limits
Example #18
Source File: utility.py From ILCC with BSD 2-Clause "Simplified" License | 6 votes |
def draw_chessboard_model(marker_size=marker_size): gird_coords = generate_grid_coords(x_res=marker_size[0], y_res=marker_size[1]) grid_ls = [(p[0]).flatten()[:2] for p in gird_coords] corner_arr = np.transpose(np.array(grid_ls).reshape(marker_size[0], marker_size[1], 2)[1:, 1:], (1, 0, 2)) c = np.zeros([corner_arr.shape[0], corner_arr.shape[1], 3]).reshape( corner_arr.shape[0] * corner_arr.shape[1], 3).astype(np.float32) c[0] = np.array([0, 0, 1]) c[-1] = np.array([1, 0, 0]) s = np.zeros(corner_arr[:, :, 0].flatten().shape[0]) + 20 s[0] = 60 s[-1] = 60 plt.scatter(corner_arr[:, :, 0].flatten(), corner_arr[:, :, 1].flatten(), c=c, s=s) plt.plot(corner_arr[:, :, 0].flatten(), corner_arr[:, :, 1].flatten()) plt.xlim(corner_arr[:, :, 0].min(), corner_arr[:, :, 0].max()) plt.ylim(corner_arr[:, :, 1].min(), corner_arr[:, :, 1].max()) plt.xlabel("x coordinates [cm]") plt.ylabel("y coordinates [cm]") # plt.axes().set_aspect('equal', 'datalim') plt.axis('equal') plt.show()
Example #19
Source File: test_axes.py From neural-network-animation with MIT License | 5 votes |
def test_polar_coord_annotations(): # You can also use polar notation on a catesian axes. Here the # native coordinate system ('data') is cartesian, so you need to # specify the xycoords and textcoords as 'polar' if you want to # use (theta, radius) from matplotlib.patches import Ellipse el = Ellipse((0, 0), 10, 20, facecolor='r', alpha=0.5) fig = plt.figure() ax = fig.add_subplot(111, aspect='equal') ax.add_artist(el) el.set_clip_box(ax.bbox) ax.annotate('the top', xy=(np.pi/2., 10.), # theta, radius xytext=(np.pi/3, 20.), # theta, radius xycoords='polar', textcoords='polar', arrowprops=dict(facecolor='black', shrink=0.05), horizontalalignment='left', verticalalignment='baseline', clip_on=True, # clip to the axes bounding box ) ax.set_xlim(-20, 20) ax.set_ylim(-20, 20)
Example #20
Source File: test_axes.py From neural-network-animation with MIT License | 5 votes |
def test_vert_violinplot_baseline(): # First 9 digits of frac(sqrt(2)) np.random.seed(414213562) data = [np.random.normal(size=100) for i in range(4)] ax = plt.axes() ax.violinplot(data, positions=range(4), showmeans=0, showextrema=0, showmedians=0)
Example #21
Source File: test_axes.py From neural-network-animation with MIT License | 5 votes |
def test_boxplot_no_weird_whisker(): x = np.array([3, 9000, 150, 88, 350, 200000, 1400, 960], dtype=np.float64) ax1 = plt.axes() ax1.boxplot(x) ax1.set_yscale('log') ax1.yaxis.grid(False, which='minor') ax1.xaxis.grid(False)
Example #22
Source File: test_axes.py From neural-network-animation with MIT License | 5 votes |
def test_single_point(): # Issue #1796: don't let lines.marker affect the grid matplotlib.rcParams['lines.marker'] = 'o' matplotlib.rcParams['axes.grid'] = True fig = plt.figure() plt.subplot(211) plt.plot([0], [0], 'o') plt.subplot(212) plt.plot([1], [1], 'o')
Example #23
Source File: helper_functions.py From pylustrator with GNU General Public License v3.0 | 5 votes |
def selectRectangle(axes: Axes = None): """ add a rectangle selector to the given axes """ if axes is None: axes = plt.gca() def onselect(eclick, erelease): 'eclick and erelease are matplotlib events at press and release' print(' startposition : (%f, %f)' % (eclick.xdata, eclick.ydata)) print(' endposition : (%f, %f)' % (erelease.xdata, erelease.ydata)) print(' used button : ', eclick.button) from matplotlib.widgets import RectangleSelector rect_selector = RectangleSelector(axes, onselect) return rect_selector
Example #24
Source File: helper_functions.py From pylustrator with GNU General Public License v3.0 | 5 votes |
def removeContentFromFigure(fig: Figure): """ remove axes and text from a figure """ axes = [] for ax in fig._axstack.as_list(): axes.append(ax) fig._axstack.remove(ax) text = fig.texts fig.texts = [] return axes + text
Example #25
Source File: helper_functions.py From pylustrator with GNU General Public License v3.0 | 5 votes |
def changeFigureSize(w: float, h: float, cut_from_top: bool = False, cut_from_left: bool = False, fig: Figure = None): """ change the figure size to the given dimensions. Optionally define if to remove or add space at the top or bottom and left or right. """ if fig is None: fig = plt.gcf() oldw, oldh = fig.get_size_inches() fx = oldw / w fy = oldh / h for axe in fig.axes: box = axe.get_position() if cut_from_top: if cut_from_left: axe.set_position([1 - (1 - box.x0) * fx, box.y0 * fy, (box.x1 - box.x0) * fx, (box.y1 - box.y0) * fy]) else: axe.set_position([box.x0 * fx, box.y0 * fy, (box.x1 - box.x0) * fx, (box.y1 - box.y0) * fy]) else: if cut_from_left: axe.set_position( [1 - (1 - box.x0) * fx, 1 - (1 - box.y0) * fy, (box.x1 - box.x0) * fx, (box.y1 - box.y0) * fy]) else: axe.set_position([box.x0 * fx, 1 - (1 - box.y0) * fy, (box.x1 - box.x0) * fx, (box.y1 - box.y0) * fy]) for text in fig.texts: x0, y0 = text.get_position() if cut_from_top: if cut_from_left: text.set_position([1 - (1- x0) * fx, y0 * fy]) else: text.set_position([x0 * fx, y0 * fy]) else: if cut_from_left: text.set_position([1 - (1 - x0) * fx, 1 - (1 - y0) * fy]) else: text.set_position([x0 * fx, 1 - (1 - y0) * fy]) fig.set_size_inches(w, h, forward=True)
Example #26
Source File: helper_functions.py From pylustrator with GNU General Public License v3.0 | 5 votes |
def add_image(filename: str): """ add an image to the current axes """ plt.imshow(plt.imread(filename)) plt.xticks([]) plt.yticks([])
Example #27
Source File: _utils.py From scanpy with BSD 3-Clause "New" or "Revised" License | 5 votes |
def default_palette(palette: Union[Sequence[str], Cycler, None] = None) -> Cycler: if palette is None: return rcParams['axes.prop_cycle'] elif not isinstance(palette, Cycler): return cycler(color=palette) else: return palette
Example #28
Source File: visualization.py From NTM-Keras with MIT License | 5 votes |
def update(self, matrix_list, name_list): # draw first line axes_input = plt.subplot2grid((3, 1), (0, 0), colspan=1) axes_input.set_aspect('equal') plt.imshow(matrix_list[0], interpolation='none') axes_input.set_xticks([]) axes_input.set_yticks([]) # draw second line axes_output = plt.subplot2grid((3, 1), (1, 0), colspan=1) plt.imshow(matrix_list[1], interpolation='none') axes_output.set_xticks([]) axes_output.set_yticks([]) # draw third line axes_predict = plt.subplot2grid((3, 1), (2, 0), colspan=1) plt.imshow(matrix_list[2], interpolation='none') axes_predict.set_xticks([]) axes_predict.set_yticks([]) # # add text # plt.text(-2, -19.5, name_list[0], ha='right') # plt.text(-2, -7.5, name_list[1], ha='right') # plt.text(-2, 4.5, name_list[2], ha='right') # plt.text(6, 10, 'Time $\longrightarrow$', ha='right') # set tick labels invisible make_tick_labels_invisible(plt.gcf()) # adjust spaces plt.subplots_adjust(hspace=0.05, wspace=0.05, bottom=0.1, right=0.8, top=0.9) # add color bars # *rect* = [left, bottom, width, height] cax = plt.axes([0.85, 0.125, 0.015, 0.75]) plt.colorbar(cax=cax) # show figure # plt.show() plt.draw() plt.pause(0.025) # plt.pause(15)
Example #29
Source File: visualization.py From NTM-Keras with MIT License | 5 votes |
def make_tick_labels_invisible(fig): for i, ax in enumerate(fig.axes): # ax.text(0.5, 0.5, "ax%d" % (i+1), va="center", ha="center") for tl in ax.get_xticklabels() + ax.get_yticklabels(): tl.set_visible(False)
Example #30
Source File: _utils.py From scanpy with BSD 3-Clause "New" or "Revised" License | 5 votes |
def _set_default_colors_for_categorical_obs(adata, value_to_plot): """ Sets the adata.uns[value_to_plot + '_colors'] using default color palettes Parameters ---------- adata AnnData object value_to_plot Name of a valid categorical observation Returns ------- None """ categories = adata.obs[value_to_plot].cat.categories length = len(categories) # check if default matplotlib palette has enough colors if len(rcParams['axes.prop_cycle'].by_key()['color']) >= length: cc = rcParams['axes.prop_cycle']() palette = [next(cc)['color'] for _ in range(length)] else: if length <= 20: palette = palettes.default_20 elif length <= 28: palette = palettes.default_28 elif length <= len(palettes.default_102): # 103 colors palette = palettes.default_102 else: palette = ['grey' for _ in range(length)] logg.info( f'the obs value {value_to_plot!r} has more than 103 categories. Uniform ' "'grey' color will be used for all categories." ) adata.uns[value_to_plot + '_colors'] = palette[:length]