X 值的水平/垂直坐标是可选的,默认为 range (len (y))。 Commonly, these parameters are 1D arrays. 通常,这些参数是一维数组。 They can also be scalars, or two-dimensional (in that case, the columns represent separate data sets). 它们也可以是标量或二维的(在这种情况下,列表示单独的数据集)。
Or, if plot_func is a python function that takes numpy arrays as input and draw a plot by returning a matplotlib Figure, we can wrap this function as a Tensor factory, such as: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 >>> tf_plot = tfplot.wrap(plot_func, name="MyPlot", ...
you will usenumpyarrays.In fact, all sequences are converted to numpy arrays internally. The examplebelow illustrates a plotting several lines with different format styles in onecommand using arrays.
In order to use our cursor on a real plot, we introduce an initial function by defining twoNumPyarrays, “x” and “y”. The “x” array is defined by exploiting theNumPyfunction.linspace(), which will generate an array of 100 equally spaced numbers from 0 to 10. The “y” array is...
Below is an example where I am plotting two random arrays. plt.rc('text', usetex=True) plt.rc('font', family='serif') y1 = np.random.random(10) y2 = np.random.random(10) fig, ax = plt.subplots(ncols=2, figsize=(8, 3)) ...
X,Y,Data values as numpy.arrays Z zdirThe direction to use: x, y or z (default) offsetIf specified plot a projection of the filled contour on this position in plane normal to zdir The positional and keyword arguments are passed on tocontourf() ...
这最终与您最初显示的代码几乎相同: import pyvista as pvimport numpy as np# Define a simple linear surfacex = np.array([1,2,3,4,5,6,7,8,9])y = np.array([1,2,3,4,5,6,7,8,9])x, y = np.meshgrid(x, y)z = x*y# Create and plot structured gridgrid = pv.StructuredGrid(...
This module get a pretty print confusion matrix from a NumPy matrix or from 2 NumPy arrays (y_testandpredictions). Installation pip install pretty-confusion-matrix Get Started Plotting from DataFrame: importnumpyasnpimportpandasaspdfrompretty_confusion_matriximportpp_matrixarray=np.array([[13,0,1...
这最终与您最初显示的代码几乎相同: import pyvista as pvimport numpy as np# Define a simple linear surfacex = np.array([1,2,3,4,5,6,7,8,9])y = np.array([1,2,3,4,5,6,7,8,9])x, y = np.meshgrid(x, y)z = x*y# Create and plot structured gridgrid = pv.StructuredGrid(...
tria = np.random.triangular(2,9,11, N)# Generate some random indices that we'll use to resample the original data# arrays. For code brevity, just use the same random indices for each arraybootstrapIndices = np.random.random_integers(0, N -1, N) ...