1D{1,1} datasets

In the following example, we illustrate how one can covert a Numpy array into a CSDM object. Start by importing the Numpy and csdmpy libraries.

import matplotlib.pyplot as plt
import numpy as np

import csdmpy as cp

Let’s generate two 1D NumPy arrays as the dependent variables of as our dataset.

test_data1 = np.zeros(500)
test_data1[250] = 1

test_data2 = np.zeros(500)
test_data2[150] = 1

Create the two DependentVariable objects from the numpy objects.

dv1 = cp.as_dependent_variable(test_data1, unit="%")
dv2 = cp.as_dependent_variable(test_data2, unit="J")

Create the corresponding dimension object. Here, we create a LinearDimension object.

dim = cp.LinearDimension(count=500, increment="43 cm", coordinates_offset="-0.1 km")

Creating the CSDM object.

csdm_object = cp.CSDM(dependent_variables=[dv1, dv2], dimensions=[dim])

Plot of the dataset.

plt.figure(figsize=(5, 3.5))
ax = plt.subplot(projection="csdm")
ax.plot(csdm_object)
plt.tight_layout()
plt.show()

To serialize the file, use the save method.

csdm_object.save("1D_11_dataset.csdf")