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()