{ "info": { "author": "Michael Christoph Nowotny", "author_email": "nowotnym@gmail.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: Implementation :: CPython" ], "description": "\n# ![coconut](https://raw.githubusercontent.com/michaelnowotny/cocos/master/images/coconut-isolated-tiny.jpg) Cocos (Core Computational System) - Scientific GPU Computing in Python\n\n\n## Overview\n\nCocos is a package for numeric and scientific computing on GPUs for Python with a NumPy-like API. It supports both CUDA and OpenCL on Windows, Mac OS, and Linux. Internally, it relies on the ArrayFire C/C++ library. In addition to its numeric functionality, it allows parallel computation of SymPy expressions on the GPU.\n\n## Highlights\n\n* Fast vectorized computation on GPUs with a NumPy-like API.\n* High-performance random number generators for beta, chi-square, exponential, gamma, logistic, lognormal, normal, uniform, and Wald distributions. Antithetic random numbers for uniform and normal distributions.\n* Provides a GPU equivalent to SymPy's lambdify, which enables numeric evaluation of symbolic SymPy (multi-dimensional array) expressions on the GPU for vectors of input parameters in parallel.\n\n## Table of Contents\n\n1. [Installation](#installation)\n2. [Getting Started](#getting-started)\n3. [Benchmark](#benchmark)\n4. [Functionality](#functionality)\n5. [Limitations and Differences with NumPy](#limitations-and-differences-with-numpy)\n6. [License](#license)\n\n## Installation\n\n1. Download and install \n - Windows or Linux: [ArrayFire 3.6.4](http://arrayfire.s3.amazonaws.com/index.html#!/3.6.4%2F)\n - MacOS: [ArrayFire 3.5.1](http://arrayfire.s3.amazonaws.com/index.html#!/3.5.1%2F)\n2. Install Cocos via PIP: \n 
\n    pip install cocos \n
\n or \n 
\n    pip3 install cocos \n
\n if not using Anaconda.\n\n To get the latest version, clone the repository from github, \n open a terminal/command prompt, navigate to the root folder and install via\n 
\n    pip install .\n
\n or \n 
\n    pip3 install . \n
\n if not using Anaconda.\n\n## Getting Started\n\n### Using Cocos is as easy as using NumPy\n#### Platform Information:\nPrint available devices\n
\nimport cocos.device as cd\ncd.info()\n
\n\nSelect a device\n
\ncd.ComputeDeviceManager.set_compute_device(0)\n
\n\n#### First Steps:\n
    \n# begin by importing the numerics package\nimport cocos.numerics as cn\n\n# create two arrays from lists\na = cn.array([[1.0, 2.0], [3.0, 4.0]])\nb = cn.array([[5.0], [6.0]])\n\n# print their contents\nprint(a)\nprint(b)\n\n# matrix product of b and a\nc = a @ b\nprint(c)\n\n# create an array of normally distributed random numbers\nd = cn.random.randn(2, 2)\nprint(d)\n
\n\n### Packaged examples:\n1. [Estimating Pi via Monte Carlo](#estimating-pi-via-monte-carlo)\n2. [Option Pricing in a Stochastic Volatility Model via Monte Carlo](#option-pricing-in-a-stochastic-volatility-model-via-monte-carlo)\n3. [Numeric evaluation of SymPy array expressions on the GPU](#numeric-evaluation-of-sympy-array-expressions-on-the-gpu)\n\n### Estimating Pi via Monte-Carlo\n\nThe following code estimates Pi via Monte-Carlo simulation. \nSince Cocos offers a NumPy-like API, the same code works on the both the GPU and the CPU via NumPy.\n\n
    \nimport time\nimport cocos.device as cd\n\ndef estimate_pi(n: int, gpu: bool = True) -> float:\n    if gpu:\n        import cocos.numerics as np\n        import cocos.numerics.random as random\n    else:\n        import numpy as np\n        import numpy.random as random\n\n    x = np.random.rand(n)\n    y = np.random.rand(n)\n    in_quarter_circle = (x * x + y * y) <= 1.0\n    estimate = int(np.sum(in_quarter_circle))\n\n    return estimate / n * 4\n\n# initialize cocos device - the architecture is selected automatically\n# the architecture can be specified explitly by providing one of\n#   'cpu', 'cuda', and 'opencl'\ncd.init()\n\n# print information regarding the available devices in the machine\ncd.info()\n\n# number of draws\nn = 100000000\nprint(f'simulating {n} draws')\n\n# run estimation of Pi on the cpu via numpy\npi_cpu = estimate_pi(n, gpu=False)\nprint(f'Estimate of Pi on cpu: {pi_cpu}')\n\n# run estimation of Pi on the cpu via numpy\npi_gpu = estimate_pi(n, gpu=True)\nprint(f'Estimate of Pi on gpu: {pi_gpu}')\n\n# run a benchmark - repeating the simulation R times on both cpu and gpu\nR = 10\n\n# on gpu\ntic = time.time()\nfor r in range(R):\n    pi_gpu = estimate_pi(n, gpu=True)\n    cd.sync()\n\ntime_on_gpu = time.time() - tic\n\nprint(f'time elapsed on gpu: {time_on_gpu}')\n\n# on cpu\ntic = time.time()\nfor r in range(R):\n    pi_cpu = estimate_pi(n, gpu=False)\n\ntime_on_cpu = time.time() - tic\n\nprint(f'time elapsed on cpu: {time_on_cpu}')\n\n# compute and print the speedup factor\nprint(f'speedup factor on gpu: {time_on_cpu/time_on_gpu}')\n
\n\n\n### Option Pricing in a Stochastic Volatility Model via Monte Carlo\nIn this example, we are simulating sample paths of the logarithmic price of an \nunderlying security under the risk-neutral probability measure via the \nEuler\u2013Maruyama discretization method.\n\nThe stochastic process is Heston's classical 1992 setup of a security price \nsubject to stochastic volatility. The log price and its instantanous variance \nare governed by the following system of stochastic differential equations (SDE):\n\n![log price sde](https://raw.githubusercontent.com/michaelnowotny/cocos/master/images/security_price_sde.png)\n\n![volatility sde](https://raw.githubusercontent.com/michaelnowotny/cocos/master/images/volatility_sde.png)\n\nThe simulation code below demonstrates how to write code that supports both CPU \nand GPU computing. The complete code is available under examples.\n\n
\ndef simulate_heston_model(T: float,\n                          N: int,\n                          R: int,\n                          mu: float,\n                          kappa: float,\n                          v_bar: float,\n                          sigma_v: float,\n                          rho: float,\n                          x0: float,\n                          v0: float,\n                          gpu: bool = False) -> tp.Tuple:\n    \"\"\"\n    This function simulates R paths from the Heston stochastic volatility model\n    over a time horizon of length T divided into N steps.\n\n    :param T: time horizon of the simulation\n    :param N: number of steps\n    :param R: number of paths to simulate\n    :param mu: expected return\n    :param kappa: mean-reversion speed of volatility\n    :param v_bar: long-run mean of volatility\n    :param sigma_v: volatility of volatility\n    :param rho: instantaneous correlation of shocks to price and to volatility\n    :param x0: initial log price\n    :param v0: initial volatility\n    :param gpu: whether to compute on the GPU\n    :return: a tuple of two R-dimensional numeric arrays for log price and\n             volatility\n    \"\"\"\n    if gpu:\n        import cocos.numerics as np\n        import cocos.numerics.random as random\n    else:\n        import numpy as np\n        import numpy.random as random\n\n    Delta_t = T / float(N - 1)\n\n    x = [np.full((R,), x0, dtype=numpy.float32),\n         np.zeros((R,), dtype=numpy.float32)]\n\n    v = [np.full((R,), v0, dtype=numpy.float32),\n         np.zeros((R,), dtype=numpy.float32)]\n\n    sqrt_delta_t = math.sqrt(Delta_t)\n    sqrt_one_minus_rho_square = math.sqrt(1 - rho ** 2)\n\n    # m = np.array([[rho, sqrt_one_minus_rho_square]])\n    m = np.zeros((2,), dtype=numpy.float32)\n    m[0] = rho\n    m[1] = sqrt_one_minus_rho_square\n    zero_array = np.zeros((R,), dtype=numpy.float32)\n\n    t_current = 0\n    for t in range(1, N):\n        t_previous = (t + 1) % 2\n        t_current = t % 2\n\n        # generate antithetic standard normal random variables\n        dBt = random.randn(R, 2) * sqrt_delta_t\n\n        sqrt_v_lag = np.sqrt(v[t_previous])\n        x[t_current] = x[t_previous] \\\n                     + (mu - 0.5 * v[t_previous]) * Delta_t \\\n                     + np.multiply(sqrt_v_lag, dBt[:, 0])\n        v[t_current] = v[t_previous] \\\n                     + kappa * (v_bar - v[t_previous]) * Delta_t \\\n                     + sigma_v * np.multiply(sqrt_v_lag, np.dot(dBt, m))\n        v[t_current] = np.maximum(v[t_current], 0.0)\n\n    x = x[t_current]\n    v = np.maximum(v[t_current], 0.0)\n\n    return x, v\n
\n\nThe following computes the option price from simulated price paths of the \nunderlying. It demonstrates how to dynamically choose between Cocos and NumPy \nbased on the type input array.\n\n
\ndef compute_option_price(r: float,\n                         T: float,\n                         K: float,\n                         x_simulated,\n                         num_pack: tp.Optional[types.ModuleType] = None):\n    \"\"\"\n    Compute the function of a plain-vanilla call option from simulated\n    log-returns.\n\n    :param r: the risk-free rate\n    :param T: the time to expiration\n    :param K: the strike price\n    :param x_simulated: a numeric array of simulated log prices of the underlying\n    :param num_pack: a module - either numpy or cocos.numerics\n    :return: option price\n    \"\"\"\n\n    if not num_pack:\n        use_gpu, num_pack = get_gpu_and_num_pack_by_dtype(x_simulated)\n\n    return math.exp(-r * T) \\\n           * num_pack.mean(num_pack.maximum(num_pack.exp(x_simulated) - K, 0))\n
\n\n\n### Numeric evaluation of SymPy array expressions on the GPU\n
\nimport cocos.numerics as cn\nimport cocos.device as cd\nimport cocos.symbolic as cs\nimport numpy as np\nimport sympy as sym\nimport time\n\nsym.init_printing()\n\n# define symbolic arguments to the function\nx1, x2, x3, t = sym.symbols('x1, x2, x3, t')\nargument_symbols = [x1, x2, x3]\n\n# define a function f: R^3 -> R^3\nf = sym.Matrix([[x1 + x2], [(x1+x3)**2], [sym.exp(x1 + x2)]])\nprint(\"defining the vector valued function f(x1, x2, x3) as\")\nprint(f)\nprint()\n\n# Compute the Jacobian symbolically\njacobian_f = f.jacobian([x1, x2, x3])\nprint(\"symbolically derived Jacobian:\")\nprint(jacobian_f)\nprint()\n\n# Convert the symbolic array expression to an object that can evaluated\n# numerically on the cpu or gpu.\njacobian_f_lambdified \\\n    = cs.LambdifiedVectorExpression(argument_symbols=argument_symbols,\n                                    time_symbol=t,\n                                    symbolic_vector_expression=jacobian_f)\n\n# Define a 3 dimensional vector X = (x1, x2, x3) = (1, 2, 3)\nX_gpu = cn.array([[1], [2], [3]])\n\n# Numerically evaluate the Jacobian at X = (1, 2, 3)\nprint(\"numerical Jacobian at X = (1, 2, 3)\")\njacobian_f_lambdified.evaluate(X_gpu.transpose(), t=0)\n\n# Compare the performance on cpu and gpu by numerically evaluating the Jacobian\n# at n different vectors (x1, x2, x3)\nn = 10000000\nprint(f'evaluating Jacobian at {n} vectors\\n')\n\nX_gpu = cn.random.rand(n, 3)\nX_cpu = np.array(X_gpu)\n\ntic = time.time()\njacobian_f_numeric_gpu = jacobian_f_lambdified.evaluate(X_gpu, t=0)\ncd.sync()\ntime_gpu = time.time() - tic\nprint(f'time on gpu: {time_gpu}')\n\ntic = time.time()\njacobian_f_numeric_cpu = jacobian_f_lambdified.evaluate(X_cpu, t=0)\ntime_cpu = time.time() - tic\nprint(f'time on cpu: {time_cpu}')\n\nprint(f'speedup on gpu vs cpu: {time_cpu / time_gpu}\\n')\n\n# Verify that the results match\nprint(f'numerical results from cpu and gpu match: '\n      f'{np.allclose(jacobian_f_numeric_gpu, jacobian_f_numeric_cpu)}')\n\n
\n\n## Benchmark\nThis benchmark compares the runtime performance of the option pricing example \nunder a Heston stochastic volatility model on the CPU using NumPy and the GPU \nusing Cocos and CuPy. CuPy is another package that provides a NumPy-like API for \nGPU computing.\n\nThe results were produced on a machine with an Intel Core i7 3770K with 32GB of \nRAM and a NVidia GeForce GTX 1070 running Windows 10. Two Million paths are being simulated with \n500 time steps per year.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Total Time in SecondsSpeedup Compared to NumPy
NumPy145.638995170593261.0
Cocos0.995002269744873146.37051552448852
CuPy2.408000707626342860.4812925134707
\n\n![benchmark_results](https://raw.githubusercontent.com/michaelnowotny/cocos/master/images/benchmark_results.png)\n\nPackage versions used:\n- arrayfire: 3.6.4\n- arrayfire-python: 3.6.20181017\n- cocos: 0.0.7\n- CUDA: 9.2\n- cupy-cuda92: 6.2.0 \n- NumPy: 1.16.4\n- Python: 3.7\n\n## Functionality\n\nMost differences between NumPy and Cocos stem from two sources:\n\n1. NumPy is row-major (C style) whereas ArrayFire is column-major (Fortran style).\n2. Only part of NumPy's functionality is present in ArrayFire, which Cocos is based on.\n\n### Attributes of the ndarray class\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
AttributeDescriptionNotes
TSame as self.transpose(), except that self is returned if self.ndim < 2.
HConjugate transpose.attribute is not present in NumPy
dataPython buffer object pointing to the start of the array\u2019s data.attribute not implemented
dtypeData-type of the array\u2019s elements.
flagsInformation about the memory layout of the array.attribute not implemented
flatA 1-D iterator over the array.attribute not implemented
imagThe imaginary part of the array.
realThe real part of the array.
sizeNumber of elements in the array.
itemsizeLength of one array element in bytes.
nbytesTotal bytes consumed by the elements of the array.
ndimNumber of array dimensions.
shapeTuple of array dimensions.
stridesTuple of bytes to step in each dimension when traversing an array.
ctypesAn object to simplify the interaction of the array with the ctypes module.attribute not implemented
baseBase object if memory is from some other object.attribute not implemented
\n\n### Methods of the ndarray class\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
MethodDescriptionNotes
all(axis=None)Returns True if all elements evaluate to True.parameters \"out\" and \"keepdims\" are not supported
any(axis=None)Returns True if any of the elements of a evaluate to True.parameters \"out\" and \"keepdims\" are not supported
argmax(axis=None)Return indices of the maximum values along the given axis.parameter \"out\" is not supported
argmin(axis=None)Return indices of the minimum values along the given axis of a.parameter \"out\" is not supported
argpartitionReturns the indices that would partition this array.method not implemented
argsort(axis=-1, ascending=True)Returns the indices that would sort this array.has additional parameter \"ascending\"; does not support parameters \"kind\" and \"order\"
astype(dtype)Copy of the array, cast to a specified type.does not support parameters \"order\", \"casting\", \"subok\", and \"copy\"
byteswapSwap the bytes of the array elementsmethod not implemented
chooseUse an index array to construct a new array from a set of choices.method not implemented
clip(min, max)Return an array whose values are limited to [min, max].parameter \"out\" is not supported
compressReturn selected slices of this array along given axis.method not implemented
conj()Complex-conjugate all elements.
conjugate()Return the complex conjugate, element-wise.
copy()Return a copy of the array.
cumprodReturn the cumulative product of the elements along the given axis.method not implemented
cumsum(axis=-1)Return the cumulative sum of the elements along the given axis.parameters \"dtype\" and \"out\" are not supported
diagonal(offset = 0)Return specified diagonals.parameters \"axis1\" and \"axis2\" are not supported
dot(a, b)Dot product of two arrays.parameter \"out\" is not supported
dumpDump a pickle of the array to the specified file.method not implemented
dumpsReturns the pickle of the array as a string.method not implemented
fill(value)Fill the array with a scalar value.
flatten()Return a copy of the array collapsed into one dimension.parameter \"order\" is not supported; flattens array column by column in contrast to numpy, which operates row by row (may be changed in the future)
getfieldReturns a field of the given array as a certain type.method not implemented
item(*args)Copy an element of an array to a standard Python scalar and return it.implemented indirectly and therefore slow
itemset(*args)Insert scalar into an array (scalar is cast to array\u2019s dtype, if possible)implemented indirectly and therefore slow
max(axis=None)Return the maximum along a given axis.parameter \"out\" is not supported; different criterion from numpy for complex arrays
mean(axis=None)Returns the average of the array elements along given axis.parameters \"dtype\", \"out\", and \"keepdims\" are not supported
min(axis=None)Returns the average of the array elements along given axis.parameter \"out\" is not supported; different criterion from numpy for complex arrays
newbyteorderReturn the array with the same data viewed with a different byte order.method not implemented
nonzeroReturn the indices of the elements that are non-zero.does not support arrays with more than three axis
partitionRearranges the elements in the array in such a way that value of the element in kth position is in the position it would be in a sorted array.method not implemented
prod(axis=None)Return the product of the array elements over the given axisparameters \"dtype\", \"out\", and \"keepdims\" are not supported
ptpPeak to peak (maximum - minimum) value along a given axis.parameter \"out\" is not supported; different output from numpy for complex arrays due to differences of min and max criteria compared to numpy
putSet a.flat[n] = values[n] for all n in indices.method not implemented; straightforward once the attribute \"flat\" has been implemented
ravelReturn a flattened array.method not implemented
repeat(repeats, axis=None)Repeat elements of an array.order is reversed compared to numpy (see remarks for the method flatten)
reshape(shape)Returns an array containing the same data with a new shape.parameter \"order\" is not supported
resize(newshape)Change shape and size of array in-place.method not implemented
round()Return a with each element rounded to the given number of decimals.parameters \"decimals\" and \"out\" are not supported
searchsortedFind indices where elements of v should be inserted in a to maintain order.method not implemented
setfieldPut a value into a specified place in a field defined by a data-type.method not implemented
setflagsSet array flags WRITEABLE, ALIGNED, and UPDATEIFCOPY, respectively.method not implemented
sort(axis=-1, ascending=True)Sort an array, in-place.has additional parameter \"ascending\"; parameters \"kind\" and \"order\" are not supported
squeeze(axis=None)Remove single-dimensional entries from the shape of a.
std(axis=None)Returns the standard deviation of the array elements along given axis.parameters \"dtype\", \"out\", \"ddof\", and \"keepdims\" are not supported
sum(axis=None)Return the sum of the array elements over the given axis.parameters \"dtype\", \"out, and \"keepdims\" are not supported
swapaxesReturn a view of the array with axis1 and axis2 interchanged.method not implemented
takeReturn an array formed from the elements of a at the given indices.method not implemented
tobytesConstruct Python bytes containing the raw data bytes in the array.method not implemented; could be implemented by first converting to numpy array for instance
tofileWrite array to a file as text or binary (default).method not implemented; could be implemented by first converting to numpy array for instance
tolistReturn the array as a (possibly nested) list.method not implemented; could be implemented by first converting to numpy array for instance
tostringConstruct Python bytes containing the raw data bytes in the array.method not implemented; could be implemented by first converting to numpy array for instance
trace(offset=0)Return the sum along diagonals of the array.parameters \"axis1\", \"axis2\", \"dtype\", and \"out\" are not supported
transpose()Returns a new array with axes transposed.parameter \"*axis\" is not supported; look into arrayfire function \"moddims\" to support *axis; new array is not a view on the old data
var(axis=None, ddof=0)Returns the variance of the array elements, along given axis.parameters \"dtype\", \"out\", and \"keepdims\" are not supported
viewNew view of array with the same data.method not implemented
\n\n### Statistics Functions\n\n#### Order Statistics\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
aminReturn the minimum of an array or minimum along an axis.function not implemented
amaxReturn the maximum of an array or maximum along an axis.function not implemented
nanminReturn minimum of an array or minimum along an axis, ignoring any NaNs.function not implemented
nanmaxReturn the maximum of an array or maximum along an axis, ignoring any NaNs.function not implemented
ptp(a, axis=None)Range of values (maximum - minimum) along an axis.parameter \"out\" not supported
percentileCompute the qth percentile of the data along the specified axis.function not implemented
nanpercentileCompute the qth percentile of the data along the specified axis, while ignoring nan values.function not implemented
\n\n#### Averages and Variances\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
medianCompute the median along the specified axis.parameters \"out\", \"overwrite_input\"=False, and \"keepdims\" are not supported
average(a, axis=None, weights=None)Compute the weighted average along the specified axis.parameter \"returned\" is not supported; does not work on Mac OS X with AMD chip when weights are given
mean(a, axis=None)parameters \"dtype\", \"out\", and \"keepdims\" are not supported
std(a, axis=None, ddof=0)Compute the arithmetic mean along the specified axis.parameters \"dtype\", \"out\", and \"keepdims\" are not supported
var(a, axis=None, ddof=0)Compute the variance along the specified axis.parameters \"dtype\", \"out\", and \"keepdims\" are not supported
nanmedianCompute the median along the specified axis, while ignoring NaNs.function not implemented
nanmeanCompute the arithmetic mean along the specified axis, ignoring NaNs.function not implemented
nanstdCompute the standard deviation along the specified axis, while ignoring NaNs.function not implemented
nanvarCompute the variance along the specified axis, while ignoring NaNs.function not implemented
\n\n#### Correlating\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
corrcoeff(x, bias=False, ddof=NoneReturn Pearson product-moment correlation coefficients.parameters \"y\" and \"rowvar\" are not supported
correlateCross-correlation of two 1-dimensional sequences.function not implemented
cov(m, bias=False, ddof=None)Estimate a covariance matrix, given data and weights.parameters \"y\", \"rowvar\", \"fweights\", and \"aweights\" are not supported
\n\n#### Histograms\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
histogramCompute the histogram of a set of data.function not implemented
histogram2dCompute the bi-dimensional histogram of two data samples.function not implemented
histogramddCompute the multidimensional histogram of some data.function not implemented
bincountCount number of occurrences of each value in array of non-negative ints.function not implemented
digitizeReturn the indices of the bins to which each value in input array belongs.function not implemented
\n\n### Array Creation Routines\n\n#### Ones and Zeros\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
emptyReturn a new array of given shape and type, initializing entries to zero.in contrast to numpy it initializes entries to zero just like zeros
empty_likeReturn a new array with the same shape and type as a given array.in contrast to numpy it initializes entries to zero just like zeros
eye(N, M=None, k=0, dtype=np.float32)Return a 2-D array with ones on the diagonal and zeros elsewhere.
identity(n, dtype=np.float32)Return the identity array.
[ones(shape, dtype=np.float32)](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.ones)Return a new array of given shape and type, filled with ones.parameter \"order\" is not supported
[ones_like(a, dtype=None)](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.ones_like)Return an array of ones with the same shape and type as a given array.parameters \"order\" and \"subok\" are not supported
[zeros(shape, dtype=n.float32)](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.zeros)Return a new array of given shape and type, filled with zeros.parameter \"order\" is not supported
[zeros_like(a, dtype=None)](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.zeros_like)Return an array of zeros with the same shape and type as a given array.parameters \"order\" and \"subok\" are not supported
[full(shape, fill_value, dtype=n.float32)](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.full)Return a new array of given shape and type, filled with fill_value.parameter \"order\" is not supported
[full_like(a, fill_value, dtype=None)](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.full_like)Return a full array with the same shape and type as a given array.parameters \"order\" and \"subok\" are not supported
\n\n#### From Existing Data\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
array(object, dtype=None)Create an array.parameters \"copy\", \"order\", \"subok\", and \"ndmin\" are not supported
asarrayConvert the input to an array.function not implemented
asanyarrayConvert the input to an ndarray, but pass ndarray subclasses through.function not implemented
ascontiguousarrayReturn a contiguous array in memory (C order).function not implemented
asmatrixInterpret the input as a matrix.function not implemented
copy(a)Return an array copy of the given object.parameter \"order\" is not supported
frombufferInterpret a buffer as a 1-dimensional array.function not implemented
fromfileConstruct an array from data in a text or binary file.function not implemented
fromfunctionConstruct an array by executing a function over each coordinate.function not implemented
fromiterCreate a new 1-dimensional array from an iterable object.function not implemented
fromstringA new 1-D array initialized from raw binary or text data in a string.function not implemented
loadtxtLoad data from a text file.function not implemented
\n\n#### Building Matrices\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
diag(v, k=0)Extract a diagonal or construct a diagonal array.
diagflat(v, k=0)Create a two-dimensional array with the flattened input as a diagonal.
triAn array with ones at and below the given diagonal and zeros elsewhere.function not implemented
tril(m)Lower triangle of an array.parameter \"k\" is not supported
triu(m)Upper triangle of an array.parameter \"k\" is not supported
vanderGenerate a Vandermonde matrix.function not implemented
\n\n### Array Manipulation Routines\n\n#### Basic Operations\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
copytoCopies values from one array to another, broadcasting as necessary.function not implemented
\n\n#### Changing Array Shape\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
FunctionDescriptionNotes
reshape(a, newshape)Gives a new shape to an array without changing its data.parameter \"order\" is not supported
ravelReturn a contiguous flattened array.function not implemented
ndarray.flatA 1-D iterator over the array.function not implemented
ndarray.flattenReturn a copy of the array collapsed into one dimension.parameter \"order\" is not implemented
\n\n#### Transpose-like Operations\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
moveaxisMove axes of an array to new positions.function not implemented
rollaxis(a, axis[, start])Roll the specified axis backwards, until it lies in a given position.function not implemented
swapaxes(a, axis1, axis2)Interchange two axes of an array.function not implemented
ndarray.TSame as self.transpose(), except that self is returned if self.ndim < 2.
transpose(a)Permute the dimensions of an array.parameter \"axes\" is not supported
\n\n#### Changing Number of Dimensions\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
atleast_1d(*arys)Convert inputs to arrays with at least one dimension.function not implemented
atleast_2d(*arys)View inputs as arrays with at least two dimensions.function not implemented
atleast_3d(*arys)View inputs as arrays with at least three dimensions.function not implemented
broadcastProduce an object that mimics broadcasting.function not implemented
broadcast_to(array, shape[, subok])Broadcast an array to a new shape.function not implemented
broadcast_arrays(*args, **kwargs)Broadcast any number of arrays against each other.function not implemented
expand_dims(a, axis)Expand the shape of an array.function not implemented
[squeeze(a, axis=None)](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.squeeze.html)Remove single-dimensional entries from the shape of an array.
\n\n#### Changing Kind of Array\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
asarray(a[, dtype, order])Convert the input to an array.function not implemented
asanyarray(a[, dtype, order])Convert the input to an ndarray, but pass ndarray subclasses through.function not implemented
asmatrix(data[, dtype])Interpret the input as a matrix.function not implemented
asfarray(a[, dtype])Return an array converted to a float type.function not implemented
asfortranarray(a[, dtype])Return an array laid out in Fortran order in memory.function not implemented
ascontiguousarray(a[, dtype])Return a contiguous array in memory (C order).function not implemented
asarray_chkfinite(a[, dtype, order])Convert the input to an array, checking for NaNs or Infs.function not implemented
asscalar(a)Convert an array of size 1 to its scalar equivalent.
require(a[, dtype, requirements])Return an ndarray of the provided type that satisfies requirements.function not implemented
\n\n#### Joining Arrays\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
concatenate((a1, a2, ...), axis=0)Join a sequence of arrays along an existing axis.
stack(arrays[, axis])Join a sequence of arrays along a new axis.function not implemented
column_stack(tup)Stack 1-D arrays as columns into a 2-D array.function not implemented
dstack(tup)Stack arrays in sequence depth wise (along third axis).
hstack(tup)Stack arrays in sequence horizontally (along second axis).
vstack(tup)Stack arrays in sequence vertically (along first axis).
block(arrays)Assemble an nd-array from nested lists of blocks.function not implemented
\n\n#### Splitting Arrays\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
split(ary, indices_or_sections[, axis])Split an array into multiple sub-arrays.function not implemented
array_split(ary, indices_or_sections[, axis])Split an array into multiple sub-arrays.function not implemented
dsplit(ary, indices_or_sections)Split array into multiple sub-arrays along the 3rd axis (depth).function not implemented
hsplit(ary, indices_or_sections)Split an array into multiple sub-arrays horizontally (column-wise).function not implemented
vsplit(ary, indices_or_sections)Split an array into multiple sub-arrays vertically (row-wise).function not implemented
\n\n#### Tiling Arrays\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
tile(A, reps)Construct an array by repeating A the number of times given by reps.
repeat(a, repeats[, axis])Repeat elements of an array.function not implemented
\n\n#### Adding and Removing Elements (not implemented)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
delete(arr, obj[, axis])Return a new array with sub-arrays along an axis deleted.function not implemented
insert(arr, obj, values[, axis])Insert values along the given axis before the given indices.function not implemented
append(arr, values[, axis])Append values to the end of an array.function not implemented
resize(a, new_shape)Return a new array with the specified shape.function not implemented
trim_zeros(filt[, trim])Trim the leading and/or trailing zeros from a 1-D array or sequence.function not implemented
unique(ar[, return_index, return_inverse, ...])Find the unique elements of an array.function not implemented
\n\n#### Rearranging Elements\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
flip(m, axis)Reverse the order of elements in an array along the given axis.
fliplr(m)Flip array in the left/right direction.
flipud(m)Flip array in the up/down direction.
reshape(a, newshape)Gives a new shape to an array without changing its data.parameter \"order\" is not supported
roll(a, shift, axis=None)Roll array elements along a given axis.
rot90(m[, k, axes])Rotate an array by 90 degrees in the plane specified by axes.function not implemented
\n\n### Binary Operations\n\n#### Elementwise Bit Operations\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
bitwise_and(x1, x2)Compute the bit-wise AND of two arrays element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
bitwise_or(x1, x2)Compute the bit-wise OR of two arrays element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
bitwise_xor(x1, x2)Compute the bit-wise XOR of two arrays element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
invert(x)Compute bit-wise inversion, or bit-wise NOT, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
left_shift(x1, x2)Shift the bits of an integer to the left.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
right_shift(x1, x2)Shift the bits of an integer to the right.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
\n\n#### Bit Packing (not implemented)\n\n### Indexing Routines\n\n#### Generating Index Arrays (not implemented)\n\n#### Indexing-like Operations\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
take(a, indices[, axis, out, mode])Take elements from an array along an axis.function not implemented
choose(a, choices[, out, mode])Construct an array from an index array and a set of arrays to choose from.function not implemented
compress(condition, a[, axis, out])Return selected slices of an array along given axis.function not implemented
diag(v, k=0)Extract a diagonal or construct a diagonal array.
diagonal(a[, offset, axis1, axis2])Return specified diagonals.function not implemented
select(condlist, choicelist[, default])Return an array drawn from elements in choicelist, depending on conditions.function not implemented
lib.stride_tricks.as_strided(x[, shape, ...])Create a view into the array with the given shape and strides.function not implemented
\n\n#### Inserting Data into Arrays (not implemented)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
place(arr, mask, vals)Change elements of an array based on conditional and input values.function not implemented
put(a, ind, v[, mode])Replaces specified elements of an array with given values.function not implemented
putmask(a, mask, values)Changes elements of an array based on conditional and input values.function not implemented
fill_diagonal(a, val[, wrap])Fill the main diagonal of the given array of any dimensionality.function not implemented
\n\n#### Iterating over Arrays (not implemented)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
nditerEfficient multi-dimensional iterator object to iterate over arrays.function not implemented
ndenumerate(arr)Multidimensional index iterator.function not implemented
ndindex(*shape)An N-dimensional iterator object to index arrays.function not implemented
flatiterFlat iterator object to iterate over arrays.function not implemented
lib.Arrayterator(var[, buf_size])Buffered iterator for big arrays.function not implemented
\n\n### Linear Algebra\n\n#### Matrix and Vector Products\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
dot(a, b)Dot product of two arrays.parameter \"out\" is not supported
linalg.multi_dot(arrays)Compute the dot product of two or more arrays in a single function call, while automatically selecting the fastest evaluation order.function not implemented
vdot(a, b)Return the dot product of two vectors.
inner(a, b)Inner product of two arrays.function not implemented
outer(a, b)Outer product of two arrays.function not implemented
matmul(a, b[, out])Matrix product of two arrays.only handles 2d arrays
tensordot(a, b[, axes])Compute tensor dot product along specified axes for arrays >= 1-D.function not implemented
einsum(subscripts, *operands[, out, dtype, ...])Evaluates the Einstein summation convention on the operands.function not implemented
linalg.matrix_power(M, n)Raise a square matrix to the (integer) power n.function not implemented
kron(a, b)Kronecker product of two arrays.function not implemented
\n\n#### Decompositions\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
linalg.cholesky(a)Cholesky decomposition.
linalg.qr(a)Compute the qr factorization of a matrix.parameter \"mode\" is not supported
linalg.svd(a[, full_matrices, compute_uv])Singular Value Decomposition.
\n\n#### Matrix Eigenvalues (not implemented)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
linalg.eig(a)Compute the eigenvalues and right eigenvectors of a square array.function not implemented
linalg.eigh(a[, UPLO])Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix.function not implemented
linalg.eigvals(a)Compute the eigenvalues of a general matrix.function not implemented
linalg.eigvalsh(a[, UPLO])Compute the eigenvalues of a Hermitian or real symmetric matrix.function not implemented
\n\n#### Norms and Other Numbers\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
linalg.norm(x[, ord, axis, keepdims])Matrix or vector norm.parameter \"keepdims\" is not supported
linalg.cond(x[, p])Compute the condition number of a matrix.function not implemented
linalg.det(a)Compute the determinant of an array.function not implemented
linalg.matrix_rank(M, tol=None)Return matrix rank of array using SVD method
linalg.slogdet(a)Compute the sign and (natural) logarithm of the determinant of an array.function not implemented
trace(a, offset=0)Return the sum along diagonals of the array.parameters \"axis1\", \"axis2\", \"dtype\", and \"out\" are not supported
\n\n#### Solving Equations and Inverting Matrices\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
linalg.solve(a, b)Solve a linear matrix equation, or system of linear scalar equations.additional parameter \"trans\" indicating whether the argument should be transposed
linalg.tensorsolve(a, b[, axes])Solve the tensor equation a x = b for x.function not implemented
linalg.lstsq(a, b[, rcond])Return the least-squares solution to a linear matrix equation.function not implemented
linalg.inv(a)Compute the (multiplicative) inverse of a matrix.
linalg.pinv(a[, rcond])Compute the (Moore-Penrose) pseudo-inverse of a matrix.function not implemented
linalg.tensorinv(a[, ind])Compute the \u2018inverse\u2019 of an N-dimensional array.
\n\n### Logic Functions\n\n#### Truth Value Testing\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
all(a, axis=None)Test whether all array elements along a given axis evaluate to True.parameters \"out\" and \"keepdims\" are not supported
any(a, axis=None)Test whether any array element along a given axis evaluates to True.parameters \"out\" and \"keepdims\" are not supported
\n\n#### Array Contents\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
isfinite(x)Test element-wise for finiteness (not infinity or not Not a Number).parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
isinf(x)Test element-wise for positive or negative infinity.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
isnan(x)Test element-wise for NaN and return result as a boolean array.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", and \"extobj\" are not supported
isneginf(x)Test element-wise for negative infinity, return result as bool array.parameter \"out\" is not supported
isposinf(x)Test element-wise for positive infinity, return result as bool array.parameter \"out\" is not supported
\n\n#### Array Type Testing\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
iscomplex(x)Returns a bool array, where True if input element is complex.function not implemented
iscomplexobj(x)Check for a complex type or an array of complex numbers.
isfortran(a)Returns True if the array is Fortran contiguous but not C contiguous.
isreal(x)Returns a bool array, where True if input element is real.function not implemented
isrealobj(x)Return True if x is a not complex type or an array of complex numbers.
isscalar(num)Returns True if the type of num is a scalar type.
\n\n#### Logical Operations\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
logical_and(x1, x2)Compute the truth value of x1 AND x2 element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
logical_or(x1, x2)Compute the truth value of x1 OR x2 element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
logical_not(x)Compute the truth value of NOT x element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
logical_xor(x1, x2)Compute the truth value of x1 XOR x2 element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
\n\n#### Comparison\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
allclose(a, b[, rtol, atol, equal_nan])Returns True if two arrays are element-wise equal within a tolerance.function not implemented
isclose(a, b[, rtol, atol, equal_nan])Returns a boolean array where two arrays are element-wise equal within a tolerance.function not implemented
array_equal(a1, a2)True if two arrays have the same shape and elements, False otherwise.
array_equiv(a1, a2)Returns True if input arrays are shape consistent and all elements equal.function not implemented
greater(x1, x2)Return the truth value of (x1 > x2) element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
greater_equal(x1, x2)Return the truth value of (x1 >= x2) element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
less(x1, x2)Return the truth value of (x1 < x2) element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
less_equal(x1, x2)Return the truth value of (x1 =< x2) element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
equal(x1, x2)Return (x1 == x2) element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
not_equal(x1, x2)Return (x1 != x2) element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
\n\n### Mathematical Functions\n\n#### Trigonometric Functions\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
sin(x)Trigonometric sine, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
cos(x)Cosine element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
tan(x)Compute tangent element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
arcsin(x)Inverse sine, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
arccos(x)Trigonometric inverse cosine, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
arctan(x)Trigonometric inverse tangent, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
hypot(x1, x2)Given the \u201clegs\u201d of a right triangle, return its hypotenuse.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
arctan2(x1, x2)Element-wise arc tangent of x1/x2 choosing the quadrant correctly.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
degrees(x, /[, out, where, casting, order, ...])Convert angles from radians to degrees.function not implemented
radians(x, /[, out, where, casting, order, ...])Convert angles from degrees to radians.function not implemented
unwrap(p[, discont, axis])Unwrap by changing deltas between values to 2*pi complement.function not implemented
deg2rad(x, /[, out, where, casting, order, ...])Convert angles from degrees to radians.function not implemented
rad2deg(x, /[, out, where, casting, order, ...])Convert angles from radians to degrees.function not implemented
\n\n#### Hyperbolic Functions\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
sinh(x)Hyperbolic sine, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
cosh(x)Hyperbolic cosine, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
tanh(x)Compute hyperbolic tangent element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
arcsinh(x)Inverse hyperbolic sine element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
arccosh(x)Inverse hyperbolic cosine, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
arctanh(x)Inverse hyperbolic tangent element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
\n\n#### Rounding\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
around(a[, decimals, out])Evenly round to the given number of decimals.function not implemented
round_(a[, decimals, out])Evenly round to the given number of decimals.function not implemented
rint(x, /[, out, where, casting, order, ...])Round elements of the array to the nearest integer.function not implemented
fix(x[, out])Round to nearest integer towards zero.function not implemented
floor(x)Return the floor of the input, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
ceil(x)Return the ceiling of the input, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
trunc(x)Return the truncated value of the input, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
\n\n#### Sums, Products, Differences\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
prod(a, axis=None)Return the product of array elements over a given axis.parameters \"dtype\", \"out\", and \"keepdims\" are not supported
sum(a, axis=None)Sum of array elements over a given axis.parameters \"dtype\", \"out\", and \"keepdims\" are not supported
nanprod(a[, axis, dtype, out, keepdims])Return the product of array elements over a given axis treating Not a Numbers (NaNs) as ones.function not implemented
nansum(a[, axis, dtype, out, keepdims])Return the sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.function not implemented
cumprod(a[, axis, dtype, out])Return the cumulative product of elements along a given axis.function not implemented
cumsum(a, axis=None)Return the cumulative sum of the elements along a given axis.parameters \"dtype\" and \"out\" are not supported
nancumprod(a[, axis, dtype, out])Return the cumulative product of array elements over a given axis treating Not a Numbers (NaNs) as one.function not implemented
nancumsum(a[, axis, dtype, out])Return the cumulative sum of array elements over a given axis treating Not a Numbers (NaNs) as zero.function not implemented
diff(a, n=1, axis=-1)Calculate the n-th discrete difference along given axis.
ediff1d(ary[, to_end, to_begin])The differences between consecutive elements of an array.function not implemented
gradient(f, *varargs, **kwargs)Return the gradient of an N-dimensional array.function not implemented
cross(a, b[, axisa, axisb, axisc, axis])Return the cross product of two (arrays of) vectors.function not implemented
trapz(y[, x, dx, axis])Integrate along the given axis using the composite trapezoidal rule.function not implemented
\n\n#### Exponents and Logarithms\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
exp(x)Calculate the exponential of all elements in the input array.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
expm1(x)Calculate exp(x) - 1 for all elements in the array.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
exp2(x)Calculate 2**p for all p in the input array.function not implemented
log(x)Natural logarithm, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
log10(x)Return the base 10 logarithm of the input array, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
log2(x)Base-2 logarithm of x.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
log1p(x)Return the natural logarithm of one plus the input array, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
logaddexp(x1, x2, /[, out, where, casting, ...])Logarithm of the sum of exponentiations of the inputs.function not implemented
logaddexp2(x1, x2, /[, out, where, casting, ...])Logarithm of the sum of exponentiations of the inputs in base-2.function not implemented
\n\n#### Other Special Functions (not implemented)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
i0(x)Modified Bessel function of the first kind, order 0.function not implemented
sinc(x)Return the sinc function.function not implemented
\n\n#### Floating Point Routines (not implemented)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
signbit(x, /[, out, where, casting, order, ...])Returns element-wise True where signbit is set (less than zero).function not implemented
copysign(x1, x2, /[, out, where, casting, ...])Change the sign of x1 to that of x2, element-wise.function not implemented
frexp(x[, out1, out2], / [[, out, where, ...])Decompose the elements of x into mantissa and twos exponent.function not implemented
ldexp(x1, x2, /[, out, where, casting, ...])Returns x1 * 2**x2, element-wise.function not implemented
nextafter(x1, x2, /[, out, where, casting, ...])Return the next floating-point value after x1 towards x2, element-wise.function not implemented
spacing(x, /[, out, where, casting, order, ...])Return the distance between x and the nearest adjacent number.function not implemented
\n\n#### Arithmetic Operations\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
add(x1, x2)Add arguments element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
reciprocal(x)Return the reciprocal of the argument, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
negative(x)Numerical negative, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
multiply(x1, x2)Multiply arguments element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
divide(x1, x2)Divide arguments element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
power(x1, x2)First array elements raised to powers from second array, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
subtract(x1, x2)Subtract arguments, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
true_divide(x1, x2)Returns a true division of the inputs, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
floor_divide(x1, x2)Return the largest integer smaller or equal to the division of the inputs.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
float_power(x1, x2, /[, out, where, ...])First array elements raised to powers from second array, element-wise.function not implemented
fmod(x1, x2, /[, out, where, casting, ...])Return the element-wise remainder of division.function not implemented
mod(x1, x2)Return the element-wise remainder of division.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
modf(x[, out1, out2], / [[, out, where, ...])Return the fractional and integral parts of an array, element-wise.function not implemented
remainder(x1, x2)Return element-wise remainder of division.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
divmod(x1, x2[, out1, out2], / [[, out, ...])Return element-wise quotient and remainder simultaneously.function not implemented
\n\n#### Handling Complex Numbers\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
angle(z)Return the angle of the complex argument.parameter \"deg\" is not supported
real(val)Return the real part of the complex argument.
imag(val)Return the imaginary part of the complex argument.
conj(x)Return the complex conjugate, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
\n\n#### Miscellaneous\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
convolve(a, v[, mode])Returns the discrete, linear convolution of two one-dimensional sequences.function not implemented
convolve(a, v[, mode])Returns the discrete, linear convolution of two one-dimensional sequences.function not implemented
clip(a, a_min, a_max)Clip (limit) the values in an array.parameter \"out\" is not supported
sqrt(x)Return the positive square-root of an array, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
cbrt(x)Return the cube-root of an array, element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
square(x)Return the element-wise square of the input.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
absolute(x)Calculate the absolute value element-wise.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
fabs(x, /[, out, where, casting, order, ...])Compute the absolute values element-wise.function not implemented
sign(x)Returns an element-wise indication of the sign of a number.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
heaviside(x1, x2, /[, out, where, casting, ...])Compute the Heaviside step function.function not implemented
maximum(x1, x2)Element-wise maximum of array elements.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
minimum(x1, x2)Element-wise minimum of array elements.parameters \"out\", \"where\", \"casting\", \"order\", \"dtype\", \"subok\", \"signature\", \"extobj\" are not supported
fmax(x1, x2, /[, out, where, casting, ...])Element-wise maximum of array elements.function not implemented
fmin(x1, x2, /[, out, where, casting, ...])Element-wise minimum of array elements.function not implemented
nan_to_num(x[, copy])Replace nan with zero and inf with finite numbers.function not implemented
real_if_close(a[, tol])If complex input returns a real array if complex parts are close to zero.function not implemented
interp(x, xp, fp[, left, right, period])One-dimensional linear interpolation.function not implemented
\n\n### Random Sampling\n\n#### Simple Random Data\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
rand(d0, d1, ..., dn)Random values in a given shape.
randn(d0, d1, ..., dn)Return a sample (or samples) from the \u201cstandard normal\u201d distribution.
randint(low[, high, size, dtype])Return random integers from low (inclusive) to high (exclusive).
random_integers(low[, high, size])Random integers of type np.int between low and high, inclusive.function not implemented
random_sample([size])Return random floats in the half-open interval [0.0, 1.0).function not implemented
random([size])Return random floats in the half-open interval [0.0, 1.0).function not implemented
ranf([size])Return random floats in the half-open interval [0.0, 1.0).function not implemented
sample([size])Return random floats in the half-open interval [0.0, 1.0).function not implemented
choice(a[, size, replace, p])Generates a random sample from a given 1-D arrayreplace=False and p != None are not supported
bytes(length)Return random bytes.function not implemented
\n\n#### Permutations\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
shuffle(x)Modify a sequence in-place by shuffling its contents.
permutation(x)Randomly permute a sequence, or return a permuted range.
\n\n#### Distributions\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
beta(a, b, size=None)Draw samples from a Beta distribution.
binomial(n, p[, size])Draw samples from a binomial distribution.function not implemented
chisquare(df, size=None)Draw samples from a chi-square distribution.
dirichlet(alpha[, size])Draw samples from the Dirichlet distribution.function not implemented
exponential(scale=1.0, size=None)Draw samples from an exponential distribution.
f(dfnum, dfden[, size])Draw samples from an F distribution.function not implemented
gamma(shape, scale=1.0, size=None)Draw samples from a Gamma distribution.
geometric(p[, size])Draw samples from the geometric distribution.function not implemented
gumbel([loc, scale, size])Draw samples from a Gumbel distribution.function not implemented
hypergeometric(ngood, nbad, nsample[, size])Draw samples from a Hypergeometric distribution.function not implemented
laplace([loc, scale, size])Draw samples from the Laplace or double exponential distribution with specified location (or mean) and scale (decay).function not implemented
logistic(loc=0.0, scale=1.0, size=None)Draw samples from a logistic distribution.
lognormal(mean=0.0, sigma=1.0, size=None)Draw samples from a log-normal distribution.
logseries(p[, size])Draw samples from a logarithmic series distribution.function not implemented
multinomial(n, pvals[, size])Draw samples from a multinomial distribution.function not implemented
multivariate_normal(mean, cov[, size, ...)Draw random samples from a multivariate normal distribution.function not implemented
negative_binomial(n, p[, size])Draw samples from a negative binomial distribution.function not implemented
noncentral_chisquare(df, nonc[, size])Draw samples from a noncentral chi-square distribution.function not implemented
noncentral_f(dfnum, dfden, nonc[, size])Draw samples from the noncentral F distribution.function not implemented
normal(loc=0.0, scale=1.0, size=None)Draw random samples from a normal (Gaussian) distribution.
pareto(a[, size])Draw samples from a Pareto II or Lomax distribution with specified shape.function not implemented
poisson([lam, size])Draw samples from a Poisson distribution.function not implemented
power(a[, size])Draws samples in [0, 1] from a power distribution with positive exponent a - 1.function not implemented
rayleigh([scale, size])Draw samples from a Rayleigh distribution.function not implemented
standard_cauchy([size])Draw samples from a standard Cauchy distribution with mode = 0.function not implemented
standard_exponential(size=None)Draw samples from the standard exponential distribution.
standard_gamma(shape, size=None)Draw samples from a standard Gamma distribution.
standard_normal(size=None)Draw samples from a standard Normal distribution (mean=0, stdev=1).
standard_t(df[, size])Draw samples from a standard Student\u2019s t distribution with df degrees of freedom.function not implemented
triangular(left, mode, right[, size])Draw samples from the triangular distribution over the interval [left, right].function not implemented
uniform(low=0.0, high=1.0, size=None)Draw samples from a uniform distribution.
vonmises(mu, kappa[, size])Draw samples from a von Mises distribution.function not implemented
wald(mean, scale, size=None)Draw samples from a Wald, or inverse Gaussian, distribution.
weibull(a[, size])Draw samples from a Weibull distribution.function not implemented
zipf(a[, size])Draw samples from a Zipf distribution.function not implemented
\n\n#### Random Generator\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
functiondescriptionnotes
seed(seed=None)Seed the generator.
get_seed()Returns the current seed of the generator.function has no counterpart in numpy
get_state()Return a tuple representing the internal state of the generator.function not implemented
set_state(state)Set the internal state of the generator from a tuple.function not implemented
\n\n## Limitations and Differences with NumPy\n\n* Requires Python 3.6 or higher.\n* Arrays may have no more than 4 axes.\n* Cocos provides only a subset of NumPy's functions and methods. In many cases, Cocos does not support all of the parameters of its corresponding NumPy function or method.\n* Trailing singleton dimensions are cut off, e.g. there is no difference between an array with shape (2, 2, 1) and an array with shape (2, 2) in Cocos.\n* Matrix multiplication is not supported for integer types.\n\n## License\nMIT License\n\nCopyright (c) 2019 Michael Nowotny\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/michaelnowotny/cocos", "keywords": "", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "cocos", "package_url": "https://pypi.org/project/cocos/", "platform": "", "project_url": "https://pypi.org/project/cocos/", "project_urls": { "Homepage": "https://github.com/michaelnowotny/cocos" }, "release_url": "https://pypi.org/project/cocos/0.0.9/", "requires_dist": [ "arrayfire", "numpy", "scipy", "sympy", "pytest" ], "requires_python": ">=3.6.0", "summary": "Core Computational System", "version": "0.0.9" }, "last_serial": 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