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new_obj = cp.CSDM(
    dimensions=old_obj.x,
    dependent_variables=[some_dv]
)

ValueError: A list of valid Dimension objects or equivalent dictionary objects is required, found <class 'csdmpy.abstract_list.DimensionList'>

new_obj = cp.CSDM(
    dimensions=[old_obj.x[0]],  # one dimension only
    dependent_variables=[some_dv]
)

f_2d.x[0].to('Hz','nmr_frequency_ratio')
f_2d.x[1].to('Hz','nmr_frequency_ratio')
f_2d.x[0] = f_2d.x[0]*cp.ScalarQuantity("s")
f_2d.x[1] = f_2d.x[1]*cp.ScalarQuantity("s")


f_2d.x[0].increment = f_2d.x[0].increment.decompose()
f_2d.x[1].increment = f_2d.x[1].increment.decompose()
f_2d.x[0].origin_offset = f_2d.x[0].origin_offset.decompose()
f_2d.x[1].origin_offset = f_2d.x[1].origin_offset.decompose()
f_2d.x[0].period = f_2d.x[0].period.decompose()
f_2d.x[1].period = f_2d.x[1].period.decompose()
f_2d.x[0]._equivalent_unit = (f_2d.x[0]._equivalent_unit*(cp.ScalarQuantity("s").quantity.unit)).decompose()
f_2d.x[1]._equivalent_unit = (f_2d.x[1]._equivalent_unit*(cp.ScalarQuantity("s").quantity.unit)).decompose()
f_2d.x[0]._unit = f_2d.x[0].coordinates.unit.decompose()
f_2d.x[1]._unit = f_2d.x[1].coordinates.unit.decompose()

import csdmpy as cp
import numpy as np
dataset = cp.as_csdm(np.arange(20))  # Integer type by default
dataset.fft()

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/.../csdmpy/csdmpy/csdm.py", line 1144, in fft
    return fft(self, axis)
  File "/Users/.../csdmpy/csdmpy/numpy_wrapper/__init__.py", line 63, in fft
    item.subtype._components[slice_] /= scale_factor
numpy.core._exceptions._UFuncOutputCastingError: Cannot cast ufunc 'divide' output from dtype('float64') to dtype('int64') with casting rule 'same_kind'with casting rule 'same_kind'

import csdmpy as cp
import numpy as np
dataset = cp.as_csdm(np.arange(20, dtype=np.float64))  # Now a float type
dataset.fft()

cptest = 10*cp.ScalarQuantity('Hz')
TypeError: unsupported operand type(s) for *: 'int' and 'ScalarQuantity'

test = cp.as_dependent_variable(np.array([1,2,3,4,5]))
print(test*2)
TypeError: unsupported operand type(s) for *: 'DependentVariable' and 'int'

import csdmpy as cp

# create dimensions and dependent variables
dimension1 = cp.as_dimension(np.arange(10), application = {"test": "d0"})
dimension1.reciprocal.application = {"test": "reciprocal-d0"}
dimension2 = cp.as_dimension(np.arange(20), application = {"test": "d1"})
dimension2.reciprocal.application = {"test": "reciprocal-d1"}
data = cp.as_dependent_variable(np.random.rand(20, 10), application = {"test": "dv0"})

# create csdm object
before = cp.new()
before.application = {"test": "root"}
before.add_dimension(dimension1)
before.add_dimension(dimension2)
before.add_dependent_variable(data)

# save
before.save('test_file.csdf')

# expected the result to be same
after = cp.load('test_file.csdf', application=True)
print(before.application, after.application)
print(before.dimensions[0].application, after.dimensions[0].application)
print(before.dimensions[0].reciprocal.application, after.dimensions[0].reciprocal.application)
print(before.dimensions[1].application, after.dimensions[1].application)
print(before.dimensions[1].reciprocal.application, after.dimensions[1].reciprocal.application)
print(before.dependent_variables[0].application, after.dependent_variables[0].application)

{'test': 'root'} {}
{'test': 'd0'} {'test': 'd0'}
{'test': 'reciprocal-d0'} {'test': 'reciprocal-d0'}
{'test': 'd1'} {'test': 'd1'}
{'test': 'reciprocal-d1'} {'test': 'reciprocal-d1'}
{'test': 'dv0'} {'test': 'dv0'}

AttributeError: Incompatible shape for in-place modification. Use `.reshape()` to make a copy with the desired shape.

import numpy as np
import csdmpy as cp

arr_c = np.zeros((1028, 1028))
arr_f = np.zeros((1028, 1028))
arr_f = np.asfortranarray(arr_f)

print(arr_c.data.c_contigious)  # True
print(arr_c.data.f_contigious)  # False
print(arr_f.data.c_contigious)  # False
print(arr_f.data.f_contigious)  # True

dv_c = cp.as_dependent_variable(arr_c)  # works
dv_f = cp.as_dependent_variable(arr_f)  # throws following error

AttributeError                            Traceback (most recent call last)
/var/folders/rx/hp_ntm7x7vxfstm8twywpgdw0000gn/T/ipykernel_22510/210171252.py in <module>
    12 dv_c = cp.as_dependent_variable(arr_c)  # works
---> 13dv_f = cp.as_dependent_variable(arr_f)  # throws following error

~/opt/anaconda3/envs/mrsimulator-dev/lib/python3.9/site-packages/csdmpy/dependent_variable/__init__.py in as_dependent_variable(array, **kwargs)
    820         kwargs["quantity_type"] = "scalar"
    821 
--> 822     return DependentVariable(type="internal", components=array, **kwargs)

~/opt/anaconda3/envs/mrsimulator-dev/lib/python3.9/site-packages/csdmpy/dependent_variable/__init__.py in __init__(self, *args, **kwargs)
     94         self._type = "internal" if dictionary["type"] == "internal" else "external"
     95         self.subtype = (
---> 96             InternalDataset(**dictionary)
     97             if dictionary["type"] == "internal"
     98             else ExternalDataset(**dictionary)

~/opt/anaconda3/envs/mrsimulator-dev/lib/python3.9/site-packages/csdmpy/dependent_variable/internal.py in __init__(self, **kwargs)
     55         size = self._components.size
     56         p = self.quantity_type.p
---> 57         self._components.shape = (p, int(size / p))
     58 
     59     def dict(self, filename=None, dataset_index=None, for_display=False):

AttributeError: Incompatible shape for in-place modification. Use `.reshape()` to make a copy with the desired shape.