Searched defs:numpy (Results 1 - 25 of 62) sorted by relevance

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/external/walt/pywalt/pywalt/
H A D	screen_stats.py	1 import numpy namespace 6 sensor_data = numpy.loadtxt(sensor_file_name) 7 blinker_data = numpy.loadtxt(blinker_file_name) 42 (numpy.median(dt_even), numpy.std(dt_even))) 44 (numpy.median(dt_odd), numpy.std(dt_odd)))
H A D	minimization.py	23 import numpy namespace 30 laser_data = numpy.loadtxt(fname_laser) 40 p = numpy.polyfit(x, y, 1, full=True) 52 shifts = numpy.arange(min_shift, max_shift, step) 56 side = ((numpy.arange(len(tl)) + 1) / 2) % 2 62 yl = numpy.interp(tl + shift, ty, y) 63 xl = numpy.interp(tl + shift, tx, x) 69 best_shift0 = shifts[numpy.argmin(residuals0)] 70 best_shift1 = shifts[numpy.argmin(residuals1)] 90 if numpy [all...]
/external/autotest/client/cros/cellular/mbim_compliance/
H A D	mbim_data_channel.py	6 import numpy namespace 68 numpy.set_printoptions(formatter={'int':lambda x: hex(int(x))}, 72 written, ntb_length, numpy.array(ntb)) 98 numpy.set_printoptions(formatter={'int':lambda x: hex(int(x))}, 101 ntb_length, numpy.array(ntb))
H A D	mbim_channel_endpoint.py	10 import numpy namespace 189 numpy.set_printoptions(formatter={'int':lambda x: hex(int(x))}, 192 len(response), numpy.array(response)) 209 numpy.set_printoptions(formatter={'int':lambda x: hex(int(x))}, 213 actual_written, len(payload), numpy.array(payload))
/external/tensorflow/tensorflow/compiler/xla/python/
H A D	numpy_bridge.h	31 #include "tensorflow/python/lib/core/numpy.h" 37 namespace numpy { namespace in namespace:xla::swig 39 // Maps XLA primitive types (PRED, S8, F32, ..., and TUPLE) to numpy 50 // (numpy dtype, dimensions). If the XLA shape represents a tuple, 51 // then the numpy dtype is NPY_OBJECT ('O') and `dimensions` is a 117 } // namespace numpy
/external/tensorflow/tensorflow/contrib/py2tf/utils/
H A D	type_check_test.py	21 import numpy namespace 39 self.assertFalse(type_check.is_tensor(numpy.eye(3)))
/external/autotest/client/cros/
H A D	http_speed.py	9 import numpy.random namespace 40 data = numpy.random.bytes(size)
/external/autotest/client/site_tests/power_CameraSuspend/
H A D	power_CameraSuspend.py	6 import numpy namespace 79 if last_image is not None and numpy.array_equal(image, last_image):
/external/tensorflow/tensorflow/contrib/periodic_resample/python/kernel_tests/
H A D	periodic_resample_op_test.py	21 import numpy namespace 34 input_tensor = numpy.arange(12).reshape((3, 4)) 35 desired_shape = numpy.array([6, None]) 45 input_tensor = numpy.arange(12).reshape((3, 4)) 46 desired_shape = numpy.array([5, None]) 56 input_tensor = numpy.arange(2 * 2 * 4).reshape((2, 2, 4)) 57 desired_shape = numpy.array([4, 4, None]) 58 output_tensor = numpy.array([[[0], [2], [4], [6]], [[1], [3], [5], [7]], 74 input_tensor = numpy.arange(2 * 2 * 2 * 8).reshape((2, 2, 2, 8)) 75 desired_shape = numpy [all...]
/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/
H A D	model_utils.py	21 import numpy namespace 77 times = numpy.array(times) 95 numpy.arange(steps)[None, ...])
H A D	estimators_test.py	21 import numpy namespace 51 times = numpy.arange(20, dtype=numpy.int64) 52 values = numpy.arange(20, dtype=dtype.as_numpy_dtype) 100 numpy.squeeze( 118 numpy.squeeze(
/external/tensorflow/tensorflow/contrib/timeseries/python/timeseries/state_space_models/
H A D	test_utils.py	21 import numpy namespace 55 rtol=1e-8 if evaled_current_matrix.dtype == numpy.float64 else 1e-4) 102 rtol=1e-8 if current_noise.dtype == numpy.float64 else 1e-3)
H A D	periodic.py	21 import numpy namespace 300 global_coeff = (math_ops.sin(original_matrix_powers * numpy.pi) / 315 row_addend = 1. / math_ops.sin(numpy.pi / num_latent_values_float * ( 320 numpy.pi / num_latent_values_float * 481 return 1. / math_ops.sin(numpy.pi / num_latent_values_float * coefficient) 511 sign = math_ops.cos(normalized * numpy.pi) 528 global_coefficient = (math_ops.sin(numpy.pi * original_matrix_powers) /
/external/tensorflow/tensorflow/examples/tutorials/mnist/
H A D	input_data.py	26 import numpy namespace
/external/webrtc/tools/cpu/
H A D	cpu_mon.py	15 import numpy namespace 32 (self.label, numpy.average(self.samples), 33 numpy.median(self.samples), 34 numpy.min(self.samples), numpy.max(self.samples))) 37 return numpy.max(self.samples)
/external/autotest/client/cros/power/
H A D	power_dashboard.py	5 import json, numpy, os, time, urllib, urllib2 namespace 159 power_dict['average'][domain] = numpy.average(domain_readings)
/external/autotest/client/site_tests/graphics_WebGLManyPlanetsDeep/
H A D	graphics_WebGLManyPlanetsDeep.py	6 import numpy namespace 76 arr = numpy.array([[v['frame_elapsed_time'], v['js_elapsed_time']]
/external/autotest/client/site_tests/power_SuspendStress/
H A D	power_SuspendStress.py	5 import logging, numpy, random, time namespace 98 keyvals[key + '_mean'] = numpy.mean(values) 99 keyvals[key + '_stddev'] = numpy.std(values) 100 keyvals[key + '_min'] = numpy.amin(values) 101 keyvals[key + '_max'] = numpy.amax(values)
/external/autotest/server/brillo/
H A D	audio_utils.py	9 import numpy namespace 204 fft_reference = numpy.fft.rfft(reference_data) 205 fft_rec = numpy.fft.rfft(rec_data) 206 fft_freqs_reference = numpy.fft.rfftfreq(len(reference_data), 208 fft_freqs_rec = numpy.fft.rfftfreq(len(rec_data), 1.0 / sample_rate) 212 numpy.argmax(numpy.abs(fft_reference))] 213 abs_fft_rec = numpy.abs(fft_rec) 214 freq_rec = fft_freqs_rec[numpy.argmax(abs_fft_rec)] 226 fft_rec_peak_val = numpy [all...]
/external/tensorflow/tensorflow/examples/learn/
H A D	random_forest_mnist.py	24 import numpy namespace 62 y=mnist.train.labels.astype(numpy.int32), 78 y=mnist.test.labels.astype(numpy.int32),
/external/webrtc/webrtc/modules/remote_bitrate_estimator/test/
H A D	plot_dynamics.py	16 import numpy namespace 82 x = numpy.array(x) 83 y = numpy.array(y)
/external/autotest/client/cros/audio/
H A D	audio_analysis.py	8 import numpy namespace 35 @returns: A numpy array containing normalized signal. The normalized signal 39 signal = numpy.array(signal) 74 signal_rms = numpy.linalg.norm(signal) / numpy.sqrt(len(signal)) 87 y_conv_w = signal * numpy.hanning(len(signal)) 93 y_f = 2.0 / length * numpy.fft.rfft(y_conv_w) 96 abs_y_f = numpy.abs(y_f) 124 @returns: A numpy array containing frequency corresponding to 125 numpy [all...]
H A D	audio_quality_measurement_unittest.py	8 import numpy namespace 18 numpy.random.seed(0) 33 noise = standard_noise * numpy.random.standard_normal() 64 numpy.random.seed(0) 82 noise = noise_amplitude * numpy.random.standard_normal() 131 self.y[j] = self.amplitude * (3 + numpy.random.uniform(-1, 1))
/external/autotest/server/site_tests/platform_InitLoginPerfServer/
H A D	platform_InitLoginPerfServer.py	6 import numpy namespace 159 self.display_perf_stats('Average', numpy.mean) 162 self.display_perf_stats('StdDev', lambda x: numpy.std(x, ddof=1))
/external/tensorflow/tensorflow/contrib/timeseries/examples/
H A D	multivariate.py	28 import numpy namespace 72 numpy.random.seed(1) # Make the example a bit more deterministic 81 next_sample = numpy.random.multivariate_normal( 83 mean=numpy.squeeze(current_prediction["mean"], axis=[0, 1]), 84 cov=numpy.squeeze(current_prediction["covariance"], axis=[0, 1])) 100 all_observations = numpy.squeeze(numpy.concatenate(values, axis=1), axis=0) 101 all_times = numpy.squeeze(numpy.concatenate(times, axis=1), axis=0)

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Indexes created Sun Aug 12 02:23:12 CEST 2018