ma.masked_array | alias of MaskedArray
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ma.array (data[, dtype, copy, order, mask, ...]) | An array class with possibly masked values. |
ma.copy (self, *args, **params) a.copy(order=) | Return a copy of the array. |
ma.frombuffer (buffer[, dtype, count, offset]) | Interpret a buffer as a 1-dimensional array. |
ma.fromfunction (function, shape, **kwargs) | Construct an array by executing a function over each coordinate. |
ma.MaskedArray.copy ([order]) | Return a copy of the array. |
ma.empty (shape[, dtype, order]) | Return a new array of given shape and type, without initializing entries. |
ma.empty_like (a[, dtype, order, subok]) | Return a new array with the same shape and type as a given array. |
ma.masked_all (shape[, dtype]) | Empty masked array with all elements masked. |
ma.masked_all_like (arr) | Empty masked array with the properties of an existing array. |
ma.ones (shape[, dtype, order]) | Return a new array of given shape and type, filled with ones. |
ma.zeros (shape[, dtype, order]) | Return a new array of given shape and type, filled with zeros. |
ma.all (self[, axis, out]) | Check if all of the elements of a are true. |
ma.any (self[, axis, out]) | Check if any of the elements of a are true. |
ma.count (a[, axis]) | Count the non-masked elements of the array along the given axis. |
ma.count_masked (arr[, axis]) | Count the number of masked elements along the given axis. |
ma.getmask (a) | Return the mask of a masked array, or nomask. |
ma.getmaskarray (arr) | Return the mask of a masked array, or full boolean array of False. |
ma.getdata (a[, subok]) | Return the data of a masked array as an ndarray. |
ma.nonzero (self) | Return the indices of unmasked elements that are not zero. |
ma.shape (obj) | Return the shape of an array. |
ma.size (obj[, axis]) | Return the number of elements along a given axis. |
ma.is_masked (x) | Determine whether input has masked values. |
ma.is_mask (m) | Return True if m is a valid, standard mask. |
ma.MaskedArray.data | Return the current data, as a view of the original underlying data. |
ma.MaskedArray.mask | Mask |
ma.MaskedArray.recordmask | Return the mask of the records. |
ma.MaskedArray.all ([axis, out]) | Check if all of the elements of a are true. |
ma.MaskedArray.any ([axis, out]) | Check if any of the elements of a are true. |
ma.MaskedArray.count ([axis]) | Count the non-masked elements of the array along the given axis. |
ma.MaskedArray.nonzero () | Return the indices of unmasked elements that are not zero. |
ma.shape (obj) | Return the shape of an array. |
ma.size (obj[, axis]) | Return the number of elements along a given axis. |
ma.atleast_1d (*arys) | Convert inputs to arrays with at least one dimension. |
ma.atleast_2d (*arys) | View inputs as arrays with at least two dimensions. |
ma.atleast_3d (*arys) | View inputs as arrays with at least three dimensions. |
ma.expand_dims (x, axis) | Expand the shape of an array. |
ma.squeeze (a[, axis]) | Remove single-dimensional entries from the shape of an array. |
ma.MaskedArray.squeeze ([axis]) | Remove single-dimensional entries from the shape of a . |
ma.column_stack (tup) | Stack 1-D arrays as columns into a 2-D array. |
ma.concatenate (arrays[, axis]) | Concatenate a sequence of arrays along the given axis. |
ma.dstack (tup) | Stack arrays in sequence depth wise (along third axis). |
ma.hstack (tup) | Stack arrays in sequence horizontally (column wise). |
ma.hsplit (ary, indices_or_sections) | Split an array into multiple sub-arrays horizontally (column-wise). |
ma.mr_ | Translate slice objects to concatenation along the first axis. |
ma.row_stack (tup) | Stack arrays in sequence vertically (row wise). |
ma.vstack (tup) | Stack arrays in sequence vertically (row wise). |
ma.asarray (a[, dtype, order]) | Convert the input to a masked array of the given data-type. |
ma.asanyarray (a[, dtype]) | Convert the input to a masked array, conserving subclasses. |
ma.fix_invalid (a[, mask, copy, fill_value]) | Return input with invalid data masked and replaced by a fill value. |
ma.masked_equal (x, value[, copy]) | Mask an array where equal to a given value. |
ma.masked_greater (x, value[, copy]) | Mask an array where greater than a given value. |
ma.masked_greater_equal (x, value[, copy]) | Mask an array where greater than or equal to a given value. |
ma.masked_inside (x, v1, v2[, copy]) | Mask an array inside a given interval. |
ma.masked_invalid (a[, copy]) | Mask an array where invalid values occur (NaNs or infs). |
ma.masked_less (x, value[, copy]) | Mask an array where less than a given value. |
ma.masked_less_equal (x, value[, copy]) | Mask an array where less than or equal to a given value. |
ma.masked_not_equal (x, value[, copy]) | Mask an array where not equal to a given value. |
ma.masked_object (x, value[, copy, shrink]) | Mask the array x where the data are exactly equal to value. |
ma.masked_outside (x, v1, v2[, copy]) | Mask an array outside a given interval. |
ma.masked_values (x, value[, rtol, atol, ...]) | Mask using floating point equality. |
ma.masked_where (condition, a[, copy]) | Mask an array where a condition is met. |
ma.anom (self[, axis, dtype]) | Compute the anomalies (deviations from the arithmetic mean) along the given axis. |
ma.anomalies (self[, axis, dtype]) | Compute the anomalies (deviations from the arithmetic mean) along the given axis. |
ma.average (a[, axis, weights, returned]) | Return the weighted average of array over the given axis. |
ma.conjugate (x[, out]) | Return the complex conjugate, element-wise. |
ma.corrcoef (x[, y, rowvar, bias, ...]) | Return Pearson product-moment correlation coefficients. |
ma.cov (x[, y, rowvar, bias, allow_masked, ddof]) | Estimate the covariance matrix. |
ma.cumsum (self[, axis, dtype, out]) | Return the cumulative sum of the elements along the given axis. |
ma.cumprod (self[, axis, dtype, out]) | Return the cumulative product of the elements along the given axis. |
ma.mean (self[, axis, dtype, out]) | Returns the average of the array elements. |
ma.median (a[, axis, out, overwrite_input]) | Compute the median along the specified axis. |
ma.power (a, b[, third]) | Returns element-wise base array raised to power from second array. |
ma.prod (self[, axis, dtype, out]) | Return the product of the array elements over the given axis. |
ma.std (self[, axis, dtype, out, ddof]) | Compute the standard deviation along the specified axis. |
ma.sum (self[, axis, dtype, out]) | Return the sum of the array elements over the given axis. |
ma.var (self[, axis, dtype, out, ddof]) | Compute the variance along the specified axis. |
ma.MaskedArray.anom ([axis, dtype]) | Compute the anomalies (deviations from the arithmetic mean) along the given axis. |
ma.MaskedArray.cumprod ([axis, dtype, out]) | Return the cumulative product of the elements along the given axis. |
ma.MaskedArray.cumsum ([axis, dtype, out]) | Return the cumulative sum of the elements along the given axis. |
ma.MaskedArray.mean ([axis, dtype, out]) | Returns the average of the array elements. |
ma.MaskedArray.prod ([axis, dtype, out]) | Return the product of the array elements over the given axis. |
ma.MaskedArray.std ([axis, dtype, out, ddof]) | Compute the standard deviation along the specified axis. |
ma.MaskedArray.sum ([axis, dtype, out]) | Return the sum of the array elements over the given axis. |
ma.MaskedArray.var ([axis, dtype, out, ddof]) | Compute the variance along the specified axis. |
ma.argmax (a[, axis, fill_value]) | Returns array of indices of the maximum values along the given axis. |
ma.argmin (a[, axis, fill_value]) | Return array of indices to the minimum values along the given axis. |
ma.max (obj[, axis, out, fill_value]) | Return the maximum along a given axis. |
ma.min (obj[, axis, out, fill_value]) | Return the minimum along a given axis. |
ma.ptp (obj[, axis, out, fill_value]) | Return (maximum - minimum) along the the given dimension (i.e. |
ma.MaskedArray.argmax ([axis, fill_value, out]) | Returns array of indices of the maximum values along the given axis. |
ma.MaskedArray.argmin ([axis, fill_value, out]) | Return array of indices to the minimum values along the given axis. |
ma.MaskedArray.max ([axis, out, fill_value]) | Return the maximum along a given axis. |
ma.MaskedArray.min ([axis, out, fill_value]) | Return the minimum along a given axis. |
ma.MaskedArray.ptp ([axis, out, fill_value]) | Return (maximum - minimum) along the the given dimension (i.e. |
ma.diag (v[, k]) | Extract a diagonal or construct a diagonal array. |
ma.dot (a, b[, strict, out]) | Return the dot product of two arrays. |
ma.identity (n[, dtype]) | Return the identity array. |
ma.inner (a, b) | Inner product of two arrays. |
ma.innerproduct (a, b) | Inner product of two arrays. |
ma.outer (a, b) | Compute the outer product of two vectors. |
ma.outerproduct (a, b) | Compute the outer product of two vectors. |
ma.trace (self[, offset, axis1, axis2, ...]) | Return the sum along diagonals of the array. |
ma.transpose (a[, axes]) | Permute the dimensions of an array. |
ma.MaskedArray.trace ([offset, axis1, axis2, ...]) | Return the sum along diagonals of the array. |
ma.MaskedArray.transpose (*axes) | Returns a view of the array with axes transposed. |
ma.allequal (a, b[, fill_value]) | Return True if all entries of a and b are equal, using fill_value as a truth value where either or both are masked. |
ma.allclose (a, b[, masked_equal, rtol, atol]) | Returns True if two arrays are element-wise equal within a tolerance. |
ma.apply_along_axis (func1d, axis, arr, ...) | Apply a function to 1-D slices along the given axis. |
ma.arange ([start,] stop[, step,][, dtype]) | Return evenly spaced values within a given interval. |
ma.choose (indices, choices[, out, mode]) | Use an index array to construct a new array from a set of choices. |
ma.ediff1d (arr[, to_end, to_begin]) | Compute the differences between consecutive elements of an array. |
ma.indices (dimensions[, dtype]) | Return an array representing the indices of a grid. |
ma.where (condition[, x, y]) | Return a masked array with elements from x or y, depending on condition. |
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