How to use test_experimental method in pytest-play

Best Python code snippet using pytest-play_python

imageStats.py

Source:imageStats.py

1import sys, copy2import numpy as np3import itk4import numpy as np5import pandas as pd6from scipy import ndimage7CPUImageType = itk.Image[itk.F,2]8ReaderType = itk.ImageFileReader[CPUImageType]9reader = ReaderType.New();10reader.SetFileName(sys.argv[1]);11reader.Update();12reference_CT_slice=itk.GetArrayFromImage(reader.GetOutput());13reader.SetFileName(sys.argv[2]);14reader.Update();15simulated_CT_slice=itk.GetArrayFromImage(reader.GetOutput());16roi_length = 4017reference_fibre_in_centre = reference_CT_slice[429 - roi_length:430 + roi_length, 520 - roi_length:521 + roi_length];18test_fibre_in_centre = simulated_CT_slice[429 - roi_length:430 + roi_length, 520 - roi_length:521 + roi_length];19def create_circular_mask(h, w, center=None, radius=None):20    if center is None: # use the middle of the image21        center = (int(w/2), int(h/2))22    if radius is None: # use the smallest distance between the center and image walls23        radius = min(center[0], center[1], w-center[0], h-center[1])24    Y, X = np.ogrid[:h, :w]25    dist_from_center = np.sqrt((X - center[0])**2 + (Y-center[1])**2)26    mask = dist_from_center <= radius27    return np.array(mask, dtype=bool);28def createMasks(mask_shape):29    fibre_radius_in_px = int(108 / 1.9) / 230    core_radius_in_px = int(16 / 1.9) / 231    core_mask = create_circular_mask(mask_shape[1], mask_shape[0], None, core_radius_in_px);32    fibre_mask = create_circular_mask(mask_shape[1], mask_shape[0], None, fibre_radius_in_px);33    matrix_mask = np.logical_not(fibre_mask);34    #fibre_mask = np.subtract(fibre_mask, core_mask);35    fibre_mask = np.bitwise_xor(fibre_mask, core_mask);36    #TypeError: numpy boolean subtract, the `-` operator, is not supported, use the bitwise_xor, the `^` operator, or the logical_xor function instead.37    return core_mask, fibre_mask, matrix_mask38mask_shape = reference_fibre_in_centre.shape;39core_mask, fibre_mask, matrix_mask = createMasks(mask_shape);40core_mask = ndimage.binary_erosion(core_mask).astype(core_mask.dtype);41for i in range(4):42    fibre_mask = ndimage.binary_erosion(fibre_mask).astype(fibre_mask.dtype);43    matrix_mask = ndimage.binary_erosion(matrix_mask, border_value=1).astype(matrix_mask.dtype);44core_mask.shape = [core_mask.shape[0], core_mask.shape[1]]45fibre_mask.shape = [fibre_mask.shape[0], fibre_mask.shape[1]]46matrix_mask.shape = [matrix_mask.shape[0], matrix_mask.shape[1]]47def getMuStatistics(reference_fibre_in_centre, test_fibre_in_centre, core_mask, fibre_mask, matrix_mask):48    data = [];49    index = np.nonzero(core_mask);50    data.append(["Theorical",51                "Core",52                "W",53                341.61,54                341.61,55                341.61,56                0.0]);57    data.append(["Experimental",58                "Core",59                "W",60                np.min(reference_fibre_in_centre[index]),61                np.max(reference_fibre_in_centre[index]),62                np.mean(reference_fibre_in_centre[index]),63                np.std(reference_fibre_in_centre[index])]);64    data.append(["Simulated",65                "Core",66                "W",67                np.min(test_fibre_in_centre[index]),68                np.max(test_fibre_in_centre[index]),69                np.mean(test_fibre_in_centre[index]),70                np.std(test_fibre_in_centre[index])]);71    index = np.nonzero(fibre_mask);72    data.append(["Theorical",73                "Fibre",74                "SiC",75                2.736,76                2.736,77                2.736,78                0.0]);79    data.append(["Experimental",80                "Fibre",81                "SiC",82                np.min(reference_fibre_in_centre[index]),83                np.max(reference_fibre_in_centre[index]),84                np.mean(reference_fibre_in_centre[index]),85                np.std(reference_fibre_in_centre[index])]);86    data.append(["Simulated",87                "Fibre",88                "SiC",89                np.min(test_fibre_in_centre[index]),90                np.max(test_fibre_in_centre[index]),91                np.mean(test_fibre_in_centre[index]),92                np.std(test_fibre_in_centre[index])]);93    index = np.nonzero(matrix_mask);94    data.append(["Theorical",95                "Matrix",96                "Ti90Al6V4",97                13.1274,98                13.1274,99                13.1274,100                0.0]);101    data.append(["Experimental",102                "Matrix",103                "Ti90Al6V4",104                np.min(reference_fibre_in_centre[index]),105                np.max(reference_fibre_in_centre[index]),106                np.mean(reference_fibre_in_centre[index]),107                np.std(reference_fibre_in_centre[index])]);108    data.append(["Simulated",109                "Matrix",110                "Ti90Al6V4",111                np.min(test_fibre_in_centre[index]),112                np.max(test_fibre_in_centre[index]),113                np.mean(test_fibre_in_centre[index]),114                np.std(test_fibre_in_centre[index])]);115    return pd.DataFrame(data,116            index=None,117            columns=['CT', 'Structure', "Composition", 'min', 'max', 'mean', 'stddev'])118df = getMuStatistics(reference_fibre_in_centre, test_fibre_in_centre, core_mask, fibre_mask, matrix_mask)119test_experimental=df["CT"] == "Experimental";120test_simulated=df["CT"] == "Simulated";121test_W=df["Composition"] == "W"122test_SiC=df["Composition"] == "SiC"123test_Ti90Al6V4=df["Composition"] == "Ti90Al6V4"124print(df[test_experimental & test_W]["mean"].astype(float)[1],125    df[test_experimental & test_W]["stddev"].astype(float)[1],126    df[test_simulated & test_W]["mean"].astype(float)[2],127    df[test_simulated & test_W]["stddev"].astype(float)[2],128    df[test_experimental & test_SiC]["mean"].astype(float)[4],129    df[test_experimental & test_SiC]["stddev"].astype(float)[4],130    df[test_simulated & test_SiC]["mean"].astype(float)[5],131    df[test_simulated & test_SiC]["stddev"].astype(float)[5],132    df[test_experimental & test_Ti90Al6V4]["mean"].astype(float)[7],133    df[test_experimental & test_Ti90Al6V4]["stddev"].astype(float)[7],134    df[test_simulated & test_Ti90Al6V4]["mean"].astype(float)[8],135    df[test_simulated & test_Ti90Al6V4]["stddev"].astype(float)[8])136# MEAN_CORE_SIM=`grep "After noise CORE SIMULATED (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 13`137# STDDEV_CORE_SIM=`grep "After noise CORE SIMULATED (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 14`138#139# MEAN_FIBRE_REF=`grep "After noise FIBRE REF (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 13`140# STDDEV_FIBRE_REF=`grep "After noise FIBRE REF (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 14`141#142# MEAN_FIBRE_SIM=`grep "After noise FIBRE SIMULATED (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 13`143# STDDEV_FIBRE_SIM=`grep "After noise FIBRE SIMULATED (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 14`144#145# MEAN_MATRIX_REF=`grep "After noise MATRIX REF (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 13`146# STDDEV_MATRIX_REF=`grep "After noise MATRIX REF (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 14`147#148# MEAN_MATRIX_SIM=`grep "After noise MATRIX SIMULATED (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 13`149# STDDEV_MATRIX_SIM=`grep "After noise MATRIX SIMULATED (MIN, MEDIAN, MAX, MEAN, STDDEV)" run_SCW_$i/optimisation-$i.out | cut -d " " -f 14`...

test_experimental.py

Source:test_experimental.py

2# Simon Hulse3# simon.hulse@chem.ox.ac.uk4# Last Edited: Thu 13 Jan 2022 17:31:26 GMT5from nmr_sims. experimental import Experimental6def test_experimental():7    experimental = Experimental(8        channels=["1H", "13C"],9        sweep_widths=[10000, 100000],10        field="800MHz",11        temperature="25C",...

test_experimental_data.py

Source:test_experimental_data.py

1from neuromodcell.experimental_data import Experimental2def test_experimental():3    exp_trial = Experimental()4    exp_trial.define_exp(mean = 2)...

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