class MainView(ZApplicationView): # Constructor def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 1200, 500) self.ax1= self.plotter.add(131) self.ax1.hist(rand(100), bins=20, color='k', alpha=0.3) self.ax2= self.plotter.add(132) self.ax2.scatter(np.arange(30), np.arange(30) + 3 * rand(30)) self.ax3 = self.plotter.add(133) sns.set() uniform_data = np.random.rand(100, 100) sns.heatmap(uniform_data, ax = self.ax3) self.add(self.plotter) self.show() def file_save(self): try: abs_current_path = os.path.abspath(os.path.curdir) files_types = "PDF (*.pdf);;PGF (*.pgf);;PNG (*.png);;PS (*.ps);;EPS (*.eps);;RAW (*.raw);;RGBA (*.rgba);;SVG (*.svg);;SVGZ (*.svgz)" filename, _ = QFileDialog.getSaveFileName(self, "FileSaveDialog", os.path.join(abs_current_path, "figure.png"), files_types) if filename: plt.savefig(filename) except: traceback.print_exc()
def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 800, 600) self.ax= self.plotter.add(111) sns.set() dataset3 = pd.read_csv("http://pythondatascience.plavox.info/wp-content/uploads/2016/05/sample_dataset.csv") dataset3 = dataset3.pivot("Sex", "Occupation", "Salary") sns.heatmap(dataset3, cmap="jet", ax = self.ax) self.add(self.plotter) self.show()
def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 1200, 1200) self.minist = keras.datasets.mnist (self.X_train, self.y_train), (self.X_test_, self.y_test) = keras.datasets.mnist.load_data() self.class_names = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] for i in range(25): plt.subplot(5, 5, i + 1) plt.xticks([]) plt.yticks([]) plt.grid(False) plt.imshow(self.X_train[i], cmap=plt.cm.gray_r, interpolation="nearest") plt.xlabel(self.class_names[self.y_train[i]]) self.add(self.plotter) self.show()
class MainView(ZApplicationView): def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 800, 600) self.ax= self.plotter.add(111) sns.set() dataset3 = pd.read_csv("http://pythondatascience.plavox.info/wp-content/uploads/2016/05/sample_dataset.csv") dataset3 = dataset3.pivot("Sex", "Occupation", "Salary") sns.heatmap(dataset3, cmap="jet", ax = self.ax) self.add(self.plotter) self.show() def file_save(self): try: abs_current_path = os.path.abspath(os.path.curdir) files_types = "All Files (*);;Image Files (*.png;*jpg;*.jpeg)" filename, _ = QFileDialog.getSaveFileName(self, "FileSaveDialog", os.path.join(abs_current_path, "image.png"), file_types) if filename: self.image_view.file_save(filename) except: traceback.print_exc()
class MainView(ZApplicationView): def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 800, 600) self.ax= self.plotter.add(111) sns.set() flights = sns.load_dataset("flights") flights = flights.pivot("month", "year", "passengers") sns.heatmap(flights, annot=True, fmt="d", ax = self.ax) self.add(self.plotter) self.show() def file_save(self): try: abs_current_path = os.path.abspath(os.path.curdir) files_types = "PDF (*.pdf);;PGF (*.pgf);;PNG (*.png);;PS (*.ps);;EPS (*.eps);;RAW (*.raw);;RGBA (*.rgba);;SVG (*.svg);;SVGZ (*.svgz)" filename, _ = QFileDialog.getSaveFileName(self, "FileSaveDialog", os.path.join(abs_current_path, "figure.png"), files_types) if filename: plt.savefig(filename) except: traceback.print_exc()
def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 800, 600) self.ax= self.plotter.add(111) sns.set() flights = sns.load_dataset("flights") flights = flights.pivot("month", "year", "passengers") sns.heatmap(flights, annot=True, fmt="d", ax = self.ax) self.add(self.plotter) self.show()
def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 1200, 500) self.ax1= self.plotter.add(131) self.ax1.hist(rand(100), bins=20, color='k', alpha=0.3) self.ax2= self.plotter.add(132) self.ax2.scatter(np.arange(30), np.arange(30) + 3 * rand(30)) self.ax3 = self.plotter.add(133) sns.set() uniform_data = np.random.rand(100, 100) sns.heatmap(uniform_data, ax = self.ax3) self.add(self.plotter) self.show()
def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) # Load iris data iris = sns.load_dataset("iris") sns.set() sns.swarmplot(x="species", y="petal_length", data=iris) self.plotter = ZScrolledPlottingArea(self, 800, 600, plt.gcf()) self.add(self.plotter) self.show()
def __init__(self, title, x, y, width, height): super(MainView, self).__init__(title, x, y, width, height) self.plotter = ZScrolledPlottingArea(self, 1200, 1200) self.fashion_mnist = keras.datasets.fashion_mnist (self.X_train, self.y_train), (self.X_test_, self.y_test) = keras.datasets.fashion_mnist.load_data() self.class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot'] for i in range(100): plt.subplot(10, 10, i+1) plt.xticks([]) plt.yticks([]) plt.grid(False) plt.imshow(self.X_train[i], cmap=plt.cm.gray_r, interpolation="nearest") plt.xlabel(self.class_names[self.y_train[i]]) self.add(self.plotter) self.show()