Python numpy 模块,around() 实例源码

我们从Python开源项目中,提取了以下41个代码示例,用于说明如何使用numpy.around()

项目:aapm_thoracic_challenge    作者:xf4j    | 项目源码 | 文件源码
def get_labels(contours, shape, slices):
    z = [np.around(s.ImagePositionPatient[2], 1) for s in slices]
    pos_r = slices[0].ImagePositionPatient[1]
    spacing_r = slices[0].PixelSpacing[1]
    pos_c = slices[0].ImagePositionPatient[0]
    spacing_c = slices[0].PixelSpacing[0]

    label_map = np.zeros(shape, dtype=np.float32)
    for con in contours:
        num = ROI_ORDER.index(con['name']) + 1
        for c in con['contours']:
            nodes = np.array(c).reshape((-1, 3))
            assert np.amax(np.abs(np.diff(nodes[:, 2]))) == 0
            z_index = z.index(np.around(nodes[0, 2], 1))
            r = (nodes[:, 1] - pos_r) / spacing_r
            c = (nodes[:, 0] - pos_c) / spacing_c
            rr, cc = polygon(r, c)
            label_map[z_index, rr, cc] = num

    return label_map
项目:demos    作者:jnez71    | 项目源码 | 文件源码
def ani_update(arg, ii=[0]):

    i = ii[0]  # don't ask...

    if np.isclose(t_arr[i], np.around(t_arr[i], 1)):
        fig2.suptitle('Evolution (Time: {})'.format(t_arr[i]), fontsize=24)

    graphic_floor[0].set_data([-floor_lim*np.cos(incline_history[i]) + radius*np.sin(incline_history[i]), floor_lim*np.cos(incline_history[i]) + radius*np.sin(incline_history[i])], [-floor_lim*np.sin(incline_history[i])-radius*np.cos(incline_history[i]), floor_lim*np.sin(incline_history[i])-radius*np.cos(incline_history[i])])
    graphic_wheel.center = (x_history[i], y_history[i])
    graphic_ind[0].set_data([x_history[i], x_history[i] + radius*np.sin(w_history[i])],
                            [y_history[i], y_history[i] + radius*np.cos(w_history[i])])
    graphic_pend[0].set_data([x_history[i], x_history[i] - cw_to_cm[1]*np.sin(q_history[i, 2])],
                             [y_history[i], y_history[i] + cw_to_cm[1]*np.cos(q_history[i, 2])])
    graphic_dist[0].set_data([x_history[i] - cw_to_cm[1]*np.sin(q_history[i, 2]), x_history[i] - cw_to_cm[1]*np.sin(q_history[i, 2]) - pscale*p_history[i]*np.cos(q_history[i, 2])],
                             [y_history[i] + cw_to_cm[1]*np.cos(q_history[i, 2]), y_history[i] + cw_to_cm[1]*np.cos(q_history[i, 2]) - pscale*p_history[i]*np.sin(q_history[i, 2])])

    ii[0] += int(1 / (timestep * framerate))
    if ii[0] >= len(t_arr):
        print("Resetting animation!")
        ii[0] = 0

    return [graphic_floor, graphic_wheel, graphic_ind, graphic_pend, graphic_dist]

# Run animation
项目:cpsc415    作者:WheezePuppet    | 项目源码 | 文件源码
def gen_adj_mat(longs, lats, prob_edge=.2,
                        additional_length=lambda: np.random.exponential(20,1)):
    '''Get an adjacency matrix for the cities whose longitudes and latitudes
    are passed. Each entry will either be a number somewhat greater than the
    crow-flies distance between the two cities (with probability prob_edge),
    or math.inf. The matrix will consist of floats, and be symmetric. The
    diagonal will be all zeroes. The "somewhat greater" is controlled by the
    additional_length parameter, a function returning a random amount.'''

    # Generate full nxn Bernoulli's, even though we'll only use the upper
    # triangle.
    edges = np.random.binomial(1, prob_edge, size=(len(longs),len(longs)))
    am = np.zeros((len(longs),len(longs)))
    for i in range(len(longs)):
        for j in range(len(longs)):
            if i==j:
                am[i,i] = 0
            elif i < j:
                if edges[i,j] == 1:
                    am[i,j] = (math.hypot(longs[i]-longs[j],lats[i]-lats[j])
                        + additional_length())
                    am[j,i] = am[i,j]
                else:
                    am[i,j] = am[j,i] = math.inf
    return np.around(am,1)
项目:pysheds    作者:mdbartos    | 项目源码 | 文件源码
def bbox_indices(self, bbox, shape, precision=7):
        """
        Return row and column coordinates of a bounding box at a
        given cellsize.

        Parameters
        ----------
        bbox : tuple of floats or ints (length 4)
               bbox of new data.
        shape : tuple of ints (length 2)
                The shape of the 2D array (rows, columns).
        precision : int
                    Precision to use when matching geographic coordinates.
        """
        rows = np.around(np.linspace(bbox[1], bbox[3],
               shape[0], endpoint=False)[::-1], precision)
        cols = np.around(np.linspace(bbox[0], bbox[2],
               shape[1], endpoint=False), precision)
        return rows, cols
项目:radar    作者:amoose136    | 项目源码 | 文件源码
def round_(a, decimals=0, out=None):
    """
    Round an array to the given number of decimals.

    Refer to `around` for full documentation.

    See Also
    --------
    around : equivalent function

    """
    try:
        round = a.round
    except AttributeError:
        return _wrapit(a, 'round', decimals, out)
    return round(decimals, out)
项目:ababe    作者:unkcpz    | 项目源码 | 文件源码
def get_cell(self):

        # from fractions import Fraction

        marr = np.array(self._matrix, dtype=np.float64).reshape((3, 3))
        g_arr = self._sites_grid.to_array()
        d = self.depth
        w = self.width
        l = self.length

        arr_bas = marr*np.array([d, w, l], dtype=np.int).reshape((3, 1))
        grid_position = np.array([p for p in CStru._yield_position(d, w, l)])
        frac = np.array([1/d, 1/w, 1/l], dtype=np.float64).reshape((1, 3))
        # round_frac = np.around(frac, decimals=22)
        arr_pos = grid_position * frac
        arr_num = np.array([i for i in g_arr.flat])

        return (arr_bas, arr_pos, arr_num)
项目:ababe    作者:unkcpz    | 项目源码 | 文件源码
def _get_new_id_seq(pos, numbers):
        """
        A helper function to produce the new sequence of the transformed
        structure. Algs is sort the position back to init and use the index
        to sort numbers.
        """
        # transfer the atom position into >=0 and <=1
        pos = np.around(pos, decimals=3)
        func_tofrac = np.vectorize(lambda x: round((x % 1), 3))
        o_pos = func_tofrac(pos)
        # round_o_pos = np.around(o_pos, decimals=3)
        # z, y, x = round_o_pos[:, 2], round_o_pos[:, 1], round_o_pos[:, 0]
        z, y, x = o_pos[:, 2], o_pos[:, 1], o_pos[:, 0]
        inds = np.lexsort((z, y, x))

        return inds
项目:ababe    作者:unkcpz    | 项目源码 | 文件源码
def _get_new_id_seq(pos, numbers):
        """
        A helper function to produce the new sequence of the transformed 
        structure. Algs is sort the position back to init and use the index
        to sort numbers.
        """
        # transfer the atom position into >=0 and <=1
        pos = np.around(pos, decimals=5)
        func_tofrac = np.vectorize(lambda x: round((x % 1), 3))
        o_pos = func_tofrac(pos)
        # round_o_pos = np.around(o_pos, decimals=3)
        # z, y, x = round_o_pos[:, 2], round_o_pos[:, 1], round_o_pos[:, 0]
        z, y, x = o_pos[:, 2], o_pos[:, 1], o_pos[:, 0]
        inds = np.lexsort((z, y, x))

        return inds
项目:ababe    作者:unkcpz    | 项目源码 | 文件源码
def __init__(self, gcell):
        self.lattice = np.around(gcell.lattice, decimals=6)
        self.positions = np.around(gcell.positions, decimals=6)
        self.numbers = gcell.numbers

        atoms_name_list = list(map(lambda x: Specie.to_name(x),
                                   list(self.numbers)))
        d = Counter(atoms_name_list)
        ordered_atoms = OrderedDict(sorted(d.items(),
                                           key=lambda x: Specie(x[0]).Z))
        # remove Ghostatoms
        if 'G' in ordered_atoms:
            del ordered_atoms['G']

        self.comment = ''.join(['{}{}'.format(k, v)
                               for k, v in ordered_atoms.items()])
项目:rl_trading    作者:ucaiado    | 项目源码 | 文件源码
def _pnl_pos(self, e, s, a, pnl, inputs):
        '''
        Return the reward based on PnL from the last step marked to the
        mid-price of the instruments traded

        :param e: Environment object. Environment where the agent operates
        :param a: Agent object. the agent that will perform the action
        :param s: dictionary. The inputs from environment to the agent
        :param pnl: float. The current pnl of the agent
        :param inputs: dictionary. The inputs from environment to the agent
        '''
        reward = self._pnl(e, s, a, pnl, inputs)
        s_main = e.s_main_intrument
        if not a.logged_action:
            return reward
        f_penalty = abs(e.agent_states[a][s_main]['Position']) * 0.02
        f_penalty += abs(np.around(a.log_info['duration'])) * 0.30
        return reward - f_penalty
项目:360-stabilizer    作者:MateusZitelli    | 项目源码 | 文件源码
def fixOffset(self, offset, img):
    size = img.shape
    finalImg = np.ndarray(size)
    indices = np.indices((self.videoSize[0],self.videoSize[1])).swapaxes(0,2).swapaxes(0,1)
    indices = np.around(indices, decimals=1)
    indices.shape = (self.videoSize[1] * self.videoSize[0], 2)
    phi = 2 * np.arctan(np.exp(indices[:, 1] / self.videoSize[1])) - 1/2 * np.pi - offset[0]
    lamb = indices[:, 0] - offset[1]
    x = lamb
    y = np.log(np.tan(np.pi / 4 + 1/2 * phi)) * self.videoSize[1]
    finalIdx = np.ndarray((self.videoSize[1] * self.videoSize[0], 2))
    finalIdx = np.around(finalIdx, decimals=1).astype(int)
    finalIdx[:, 1] = y % self.videoSize[1]
    finalIdx[:, 0] = x % self.videoSize[0]
    finalImg[indices[:,1], indices[:,0]] = img[finalIdx[:,1], finalIdx[:,0]]
    return finalImg
项目:matlab_imresize    作者:fatheral    | 项目源码 | 文件源码
def imresizemex(inimg, weights, indices, dim):
    in_shape = inimg.shape
    w_shape = weights.shape
    out_shape = list(in_shape)
    out_shape[dim] = w_shape[0]
    outimg = np.zeros(out_shape)
    if dim == 0:
        for i_img in range(in_shape[1]):
            for i_w in range(w_shape[0]):
                w = weights[i_w, :]
                ind = indices[i_w, :]
                im_slice = inimg[ind, i_img].astype(np.float64)
                outimg[i_w, i_img] = np.sum(np.multiply(np.squeeze(im_slice, axis=0), w.T), axis=0)
    elif dim == 1:
        for i_img in range(in_shape[0]):
            for i_w in range(w_shape[0]):
                w = weights[i_w, :]
                ind = indices[i_w, :]
                im_slice = inimg[i_img, ind].astype(np.float64)
                outimg[i_img, i_w] = np.sum(np.multiply(np.squeeze(im_slice, axis=0), w.T), axis=0)        
    if inimg.dtype == np.uint8:
        outimg = np.clip(outimg, 0, 255)
        return np.around(outimg).astype(np.uint8)
    else:
        return outimg
项目:algorithm-reference-library    作者:SKA-ScienceDataProcessor    | 项目源码 | 文件源码
def frac_coord(npixel, kernel_oversampling, p):
    """ Compute whole and fractional parts of coordinates, rounded to
    kernel_oversampling-th fraction of pixel size

    The fractional values are rounded to nearest 1/kernel_oversampling pixel value. At
    fractional values greater than (kernel_oversampling-0.5)/kernel_oversampling coordinates are
    rounded to next integer index.

    :param npixel: Number of pixels in total
    :param kernel_oversampling: Fractional values to round to
    :param p: Coordinate in range [-.5,.5[
    """
    assert numpy.array(p >= -0.5).all() and numpy.array(
        p < 0.5).all(), "Cellsize is too large: uv overflows grid uv= %s" % str(p)
    x = npixel // 2 + p * npixel
    flx = numpy.floor(x + 0.5 / kernel_oversampling)
    fracx = numpy.around((x - flx) * kernel_oversampling)
    return flx.astype(int), fracx.astype(int)
项目:orange3-educational    作者:biolab    | 项目源码 | 文件源码
def test_optimized(self):
        """
        Test if optimized works well
        """
        lr = self.logistic_regression

        lr.set_data(self.iris)
        op_theta = lr.optimized()
        self.assertEqual(len(op_theta), 4)

        # check if really minimal, function is monotonic so everywhere around
        # j should be higher
        self.assertLessEqual(
            lr.j(op_theta), lr.j(op_theta + np.array([1, 0, 0, 0])))
        self.assertLessEqual(
            lr.j(op_theta), lr.j(op_theta + np.array([0, 1, 0, 0])))
        self.assertLessEqual(
            lr.j(op_theta), lr.j(op_theta + np.array([0, 0, 1, 0])))
        self.assertLessEqual(
            lr.j(op_theta), lr.j(op_theta + np.array([0, 0, 0, 1])))
项目:lqRRT    作者:jnez71    | 项目源码 | 文件源码
def ani_update(arg, ii=[0]):

    i = ii[0]  # don't ask...

    if np.isclose(t_arr[i], np.around(t_arr[i], 1)):
        fig2.suptitle('Evolution (Time: {})'.format(t_arr[i]), fontsize=24)

    graphic_robot_1.center = ((x_history[i, 0]+td*np.cos(x_history[i, 2]), x_history[i, 1]+td*np.sin(x_history[i, 2])))
    graphic_robot_2.center = ((x_history[i, 0], x_history[i, 1]))
    graphic_robot_3.center = ((x_history[i, 0]-td*np.cos(x_history[i, 2]), x_history[i, 1]-td*np.sin(x_history[i, 2])))

    ii[0] += int(1 / (dt * framerate))
    if ii[0] >= len(t_arr):
        print("Resetting animation!")
        ii[0] = 0

    return None

# Run animation
项目:lqRRT    作者:jnez71    | 项目源码 | 文件源码
def ani_update(arg, ii=[0]):

    i = ii[0]  # don't ask...

    if np.isclose(t_arr[i], np.around(t_arr[i], 1)):
        fig2.suptitle('Evolution (Time: {})'.format(t_arr[i]), fontsize=24)

    graphic_robot_1.center = ((x_history[i, 0]+td*np.cos(x_history[i, 2]), x_history[i, 1]+td*np.sin(x_history[i, 2])))
    graphic_robot_2.center = ((x_history[i, 0], x_history[i, 1]))
    graphic_robot_3.center = ((x_history[i, 0]-td*np.cos(x_history[i, 2]), x_history[i, 1]-td*np.sin(x_history[i, 2])))

    ii[0] += int(1 / (dt * framerate))
    if ii[0] >= len(t_arr):
        print("Resetting animation!")
        ii[0] = 0

    return None

# Run animation
项目:lqRRT    作者:jnez71    | 项目源码 | 文件源码
def ani_update(arg, ii=[0]):

    i = ii[0]  # don't ask...

    if np.isclose(t_arr[i], np.around(t_arr[i], 1)):
        fig2.suptitle('Evolution (Time: {})'.format(t_arr[i]), fontsize=24)

    graphic_robot_1.center = ((x_history[i, 0]+td*np.cos(x_history[i, 2]), x_history[i, 1]+td*np.sin(x_history[i, 2])))
    graphic_robot_2.center = ((x_history[i, 0], x_history[i, 1]))
    graphic_robot_3.center = ((x_history[i, 0]-td*np.cos(x_history[i, 2]), x_history[i, 1]-td*np.sin(x_history[i, 2])))

    ii[0] += int(1 / (dt * framerate))
    if ii[0] >= len(t_arr):
        print("Resetting animation!")
        ii[0] = 0

    return None

# Run animation
项目:lqRRT    作者:jnez71    | 项目源码 | 文件源码
def ani_update(arg, ii=[0]):

    i = ii[0]  # don't ask...

    if np.isclose(t_arr[i], np.around(t_arr[i], 1)):
        fig2.suptitle('Evolution (Time: {})'.format(t_arr[i]), fontsize=24)

    graphic_robot_1.center = ((x_history[i, 0]+td*np.cos(x_history[i, 2]), x_history[i, 1]+td*np.sin(x_history[i, 2])))
    graphic_robot_2.center = ((x_history[i, 0], x_history[i, 1]))
    graphic_robot_3.center = ((x_history[i, 0]-td*np.cos(x_history[i, 2]), x_history[i, 1]-td*np.sin(x_history[i, 2])))

    ii[0] += int(1 / (dt * framerate))
    if ii[0] >= len(t_arr):
        print("Resetting animation!")
        ii[0] = 0

    return None

# Run animation
项目:lqRRT    作者:jnez71    | 项目源码 | 文件源码
def update(arg, ii=[0]):

    i = ii[0]  # don't ask...

    if np.isclose(t_arr[i], np.around(t_arr[i], 1)):
        fig3.suptitle('Evolution (Time: {})'.format(t_arr[i]), fontsize=24)

    link1[0].set_data([0, elb_history[i, 0]], [0, elb_history[i, 1]])
    link2[0].set_data([elb_history[i, 0], x_history[i, 0]], [elb_history[i, 1], x_history[i, 1]])
    end.set_offsets((x_history[i, 0], x_history[i, 1]))
    elb.set_offsets((elb_history[i, 0], elb_history[i, 1]))

    ii[0] += int(1 / (dt * framerate))
    if ii[0] >= len(t_arr):
        print("Resetting animation!")
        ii[0] = 0

    return [link1, link2, end, elb]

# Run animation
项目:DeepMoji    作者:bfelbo    | 项目源码 | 文件源码
def test_encode_texts():
    """ Text encoding is stable.
    """

    TEST_SENTENCES = [u'I love mom\'s cooking',
                      u'I love how you never reply back..',
                      u'I love cruising with my homies',
                      u'I love messing with yo mind!!',
                      u'I love you and now you\'re just gone..',
                      u'This is shit',
                      u'This is the shit']

    maxlen = 30
    batch_size = 32

    with open(VOCAB_PATH, 'r') as f:
        vocabulary = json.load(f)
    st = SentenceTokenizer(vocabulary, maxlen)
    tokenized, _, _ = st.tokenize_sentences(TEST_SENTENCES)

    model = deepmoji_feature_encoding(maxlen, PRETRAINED_PATH)

    encoding = model.predict(tokenized)
    avg_across_sentences = np.around(np.mean(encoding, axis=0)[:5], 3)
    assert np.allclose(avg_across_sentences, np.array([-0.023, 0.021, -0.037, -0.001, -0.005]))
项目:CIKM2017    作者:heliarmk    | 项目源码 | 文件源码
def myImputer(kernel,sample):
    kernelSize = kernel.shape[0];
    vectorSize = sample.shape[3];

    for fIndex in range(0,int(sample.shape[0])):
        for sIndex in range(0,int(sample.shape[1])):
            sslice = sample[fIndex][sIndex]
            #find the index of -1
            [x,y] = np.where(sslice == -1)
            #change -1 to 0
            sslice[sslice == -1] = 0
            if x.size == 0:
                continue
            #broaden the vector 
            tempVectorH = np.zeros([int((kernelSize-1)/2),vectorSize])
            tempVectorV = np.zeros([vectorSize-1+kernelSize,int((kernelSize-1)/2)])
            tempSlice = np.vstack((tempVectorH,sslice,tempVectorH))
            tempSlice = np.hstack((tempVectorV,tempSlice,tempVectorV))

            zeroSlice = np.zeros(sslice.shape);
            for k in range(len(x)):
                subSlice = tempSlice[x[k]:x[k]+kernelSize,y[k]:y[k]+kernelSize]
                imputerValue = np.sum(subSlice*kernel)
                zeroSlice[x[k],y[k]] = np.around(imputerValue)
            sslice += zeroSlice.astype("int32")
项目:krpcScripts    作者:jwvanderbeck    | 项目源码 | 文件源码
def round_(a, decimals=0, out=None):
    """
    Round an array to the given number of decimals.

    Refer to `around` for full documentation.

    See Also
    --------
    around : equivalent function

    """
    try:
        round = a.round
    except AttributeError:
        return _wrapit(a, 'round', decimals, out)
    return round(decimals, out)
项目:MOSPAT    作者:CR2MOS    | 项目源码 | 文件源码
def prepare_basemap(min_lat, min_lon, max_lat, max_lon, delta_lat, delta_lon):
    """

    :param min_lat: float 
    :param min_lon: float
    :param max_lat: float
    :param max_lon: float
    :param delta_lat: float
    :param delta_lon: float
    :return: A Basemap instance
    """
    m = Basemap(projection='cyl', llcrnrlat=min_lat, urcrnrlat=max_lat, urcrnrlon=max_lon,
                llcrnrlon=min_lon, resolution='l')
    m.drawcountries()
    m.drawcoastlines()
    m.drawparallels(np.arange(np.around(min_lat, 1), np.around(max_lat, 1), -round(delta_lat) / 5.0),
                    labels=[1, 0, 0, 0])
    m.drawmeridians(np.arange(np.around(min_lon, 1), np.around(max_lon, 1), -round(delta_lon) / 5.0),
                    labels=[0, 0, 0, 1])
    return m
项目:pythonprograms    作者:ElsaMJohnson    | 项目源码 | 文件源码
def svimg(totarr):
    #print it out:
    x,y=totarr.shape
    vl = np.around(totarr.flatten(),5)#round to 5 digits
    xx = np.repeat(np.arange(x),x)+1
    yy = np.tile(np.arange(y),y)+1
    big =np.column_stack((xx,yy,vl))
    np.savetxt("noisyimage.txt",big,fmt=('%4.1f','%4.1f','%10.5f'))
    ##Add this if you want to
    ##read it out to make sure it works
    ##Otherwise slows down routine.
    #row,col,data=np.loadtxt("noisyimage.txt",unpack=True)
    #rsize = int(max(row))
    #csize = int(max(col))
    #data=np.array(data).reshape(rsize,csize)
#   plt.imshow(data, interpolation='None',cmap=plt.cm.Greys_r)
项目:pygeotools    作者:dshean    | 项目源码 | 文件源码
def contour_edges(a):
    import matplotlib.pyplot as plt
    a = checkma(a)
    #Contour nodata value
    levels = [a.fill_value]
    #kw = {'antialiased':True, 'colors':'r', 'linestyles':'-'}
    kw = {'antialiased':True}
    #Generate contours around nodata
    cs = plt.contour(a.filled(), levels, **kw)
    #This returns a list of numpy arrays
    #allpts = np.vstack(cs.allsegs[0])
    #Extract paths
    p = cs.collections[0].get_paths()
    #Sort by number of vertices in each path
    p_len = [i.vertices.shape[0] for i in p]
    p_sort = [x for (y,x) in sorted(zip(p_len,p), reverse=True)]    
    #cp = p[0].make_compound_path(*p)
    return p_sort

#Brute force search for edges of valid data
项目:lsdc    作者:febert    | 项目源码 | 文件源码
def save_goal_image(self, traj):
        rounded = np.around(traj.score, decimals=2)
        best_score = np.min(rounded)
        for i in range(traj.score.shape[0]):
            if rounded[i] == best_score:
                first_best_index = i
                break

        print 'best_score', best_score
        print 'allscores', traj.score
        print 'goal index: ', first_best_index

        goalimage = traj._sample_images[first_best_index]
        # goalstate = traj.X_Xdot_full[i]
        img = Image.fromarray(goalimage)

        cPickle.dump([], open(self._hyperparams['save_goal_image'] + '.pkl', 'wb'))
        img.save(self._hyperparams['save_goal_image'] + '.png',)
项目:imagenet_models_flask    作者:alesolano    | 项目源码 | 文件源码
def evaluate_checkpoints(self, filename):
        # Load image
        with open(UPLOAD_FOLDER + '/' + filename, 'rb') as f:
            image_string = f.read()

        # Session
        with tf.Session() as sess:
            # Restore variables values
            self.saver.restore(sess, './models/'+self.loaded_model_name+'/model.ckpt')

            prob_values = sess.run(self.probs, feed_dict={
                self.input_image_string: image_string
                })

            pred_idx = prob_values[0].argsort()[-5:][::-1]
            pred_class = self.classes[pred_idx - 1] # from 1001 to 1000 classes
            pred_score = np.around(100*prob_values[0][pred_idx], decimals=2) # two decimals

            return list(pred_class), list(pred_score)
项目:imagenet_models_flask    作者:alesolano    | 项目源码 | 文件源码
def evaluate_frozen(self, filename):
        # Load image
        with open(UPLOAD_FOLDER + '/' + filename, 'rb') as f:
            image_string = f.read()

        # Session
        with tf.Session() as sess:
            prob_values = sess.run(self.probs, feed_dict={
                self.input_image_string: image_string
                })

            pred_idx = prob_values[0].argsort()[-5:][::-1]
            pred_class = self.classes[pred_idx - 1] # from 1001 to 1000 classes
            pred_score = np.around(100*prob_values[0][pred_idx], decimals=2) # two decimals

            return list(pred_class), list(pred_score)
项目:cellcomplex    作者:VirtualPlants    | 项目源码 | 文件源码
def histo_plot(figure,X,color,xlabel="",ylabel="",cumul=False,bar=True,n_points=400,smooth_factor=0.1,spline_order=3,linewidth=3,alpha=1.0,label=""):
    if '%' in xlabel:
        magnitude = 100
        X_values = np.array(np.minimum(np.around(X),n_points+1),int)
    else:
        # magnitude = np.power(10,np.around(4*np.log10(X.mean()))/4+0.5)
        magnitude = np.power(10,np.around(4*np.log10(np.nanmean(X)+np.nanstd(X)+1e-7))/4+1)
        magnitude = np.around(magnitude,int(-np.log10(magnitude))+1)
        # print magnitude
        #magnitude = X.mean()+5.0*X.std()
        X_values = np.array(np.minimum(np.around(n_points*X[True-np.isnan(X)]/magnitude),n_points+1),int)
    X_histo = np.zeros(n_points+1,float)
    for x in np.linspace(0,n_points,n_points+1):
        X_histo[x] = nd.sum(np.ones_like(X_values,float),X_values,index=x)
        if '%' in ylabel:
            X_histo[x] /= X_values.size/100.0
        if cumul:
            X_histo[x] += X_histo[x-1]

    if bar:
        bar_plot(figure,np.linspace(0,magnitude,n_points+1),X_histo,np.array([1,1,1]),color,xlabel,ylabel,label=label)
    else:
        smooth_plot(figure,np.linspace(0,magnitude,n_points+1),X_histo,color,color,xlabel,ylabel,n_points=n_points,smooth_factor=smooth_factor,spline_order=spline_order,linewidth=linewidth,alpha=alpha,label=label)
项目:augur    作者:nextstrain    | 项目源码 | 文件源码
def make_pivots(start, stop, pivots_per_year=12, precision=2):
    """Makes an array of pivots (i.e., timepoints) between the given start and stop
    by the given pivots per year. The generated pivots are floating point values
    that are then rounded to the requested decimal precision.

    >>> list(make_pivots(2000.0, 2001.0, 5))
    [2000.0, 2000.25, 2000.5, 2000.75, 2001.0]
    """
    # Calculate number of pivots (i.e., months) in the requested interval.
    number_of_pivots = np.ceil((stop - start) * pivots_per_year)

    # Build an evenly-spaced closed interval (including the start and stop
    # points) based on the calculated number of pivots.
    return np.around(
        np.linspace(start, stop, number_of_pivots),
        precision
    )
项目:netcdftime    作者:Unidata    | 项目源码 | 文件源码
def test_dayofwk(self):
        "Test computation of dayofwk in the 365_day calendar."

        converter = self.converters["noleap"]

        # Pick the date corresponding to the Julian day of 1.0 to test
        # the transision from positive to negative Julian days.
        julian_day = converter.date2num(datetimex(-4712, 1, 2, 12))

        old_date = converter.num2date(julian_day)
        for delta_year in range(1, 101): # 100 years cover several 7-year cycles
            date = converter.num2date(julian_day - delta_year * 365)

            # test that the day of the week changes by one every year (except
            # for wrapping around every 7 years, of course)
            if date.dayofwk == 6:
                self.assertEqual(old_date.dayofwk, 0)
            else:
                self.assertEqual(old_date.dayofwk - date.dayofwk, 1)

            old_date = date
项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda    作者:SignalMedia    | 项目源码 | 文件源码
def test_reindex_nearest(self):
        s = Series(np.arange(10, dtype='int64'))
        target = [0.1, 0.9, 1.5, 2.0]
        actual = s.reindex(target, method='nearest')
        expected = Series(np.around(target).astype('int64'), target)
        assert_series_equal(expected, actual)

        actual = s.reindex_like(actual, method='nearest')
        assert_series_equal(expected, actual)

        actual = s.reindex_like(actual, method='nearest', tolerance=1)
        assert_series_equal(expected, actual)

        actual = s.reindex(target, method='nearest', tolerance=0.2)
        expected = Series([0, 1, np.nan, 2], target)
        assert_series_equal(expected, actual)
项目:PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda    作者:SignalMedia    | 项目源码 | 文件源码
def almost(a, b, decimal=6, fill_value=True):
    """
    Returns True if a and b are equal up to decimal places.

    If fill_value is True, masked values considered equal. Otherwise,
    masked values are considered unequal.

    """
    m = mask_or(getmask(a), getmask(b))
    d1 = filled(a)
    d2 = filled(b)
    if d1.dtype.char == "O" or d2.dtype.char == "O":
        return np.equal(d1, d2).ravel()
    x = filled(masked_array(d1, copy=False, mask=m), fill_value).astype(float_)
    y = filled(masked_array(d2, copy=False, mask=m), 1).astype(float_)
    d = np.around(np.abs(x - y), decimal) <= 10.0 ** (-decimal)
    return d.ravel()
项目:gcMapExplorer    作者:rjdkmr    | 项目源码 | 文件源码
def ylimit(self, value):
        """Upper and lower limit of current plot.
        Permanent limits are stored in yScaleSteps, which can be changed by user using range box.

        This is the only function through which plots can be updated.
        """
        if value[0] == value[1]:
            return

        if not self.hiCmapAxis.doNotPlot:
            self._ylimit = [ value[0], value[1] ]

            # Setting yticks based on ylimits, only change yticks when y-limits are changed
            ydiff = value[0] - value[1]
            yticks = np.linspace(self.ylimit[0], self.ylimit[1], 100)

            # Set tick label according to precision
            self.yticksDecimals = gmlib.util.locate_significant_digit_after_decimal(ydiff)
            if self.yticksDecimals > 3:
                self.yticksFormatStyle = 'sci'
                self.yticks = np.around(yticks, decimals=self.yticksDecimals+1)
            else:
                self.yticks = np.around(yticks, decimals=self.yticksDecimals+1)

            self.updatePlot()
项目:aRMSD    作者:armsd    | 项目源码 | 文件源码
def project_radii(radii, spacing, r_min, r_max):
    """ Projects given radii to values between r_min and r_max; good spacing ~ 1000 """

    radii_norm = radii / np.max(radii)  # Normalize radii

    # Determine min and max of array and generate spacing
    radii_to_proj = np.around(np.linspace(np.min(radii_norm), np.max(radii_norm), spacing), 3)
    values_to_proj = np.around(np.linspace(r_min, r_max, spacing), 3)

    # Determine respective array positions
    pos = np.array([np.argmin(np.abs(radii_to_proj -
                                     radii_norm[entry])) for entry in range(len(radii_norm))], dtype=np.int)

    # Determine new radii
    return np.take(values_to_proj, pos)


###############################################################################
# HUNGARIAN (MUNKRES) ALGORITHM - TAKEN FROM SCIPY
###############################################################################
项目:aws-lambda-numpy    作者:vitolimandibhrata    | 项目源码 | 文件源码
def round_(a, decimals=0, out=None):
    """
    Round an array to the given number of decimals.

    Refer to `around` for full documentation.

    See Also
    --------
    around : equivalent function

    """
    try:
        round = a.round
    except AttributeError:
        return _wrapit(a, 'round', decimals, out)
    return round(decimals, out)
项目:aws-lambda-numpy    作者:vitolimandibhrata    | 项目源码 | 文件源码
def almost(a, b, decimal=6, fill_value=True):
    """
    Returns True if a and b are equal up to decimal places.

    If fill_value is True, masked values considered equal. Otherwise,
    masked values are considered unequal.

    """
    m = mask_or(getmask(a), getmask(b))
    d1 = filled(a)
    d2 = filled(b)
    if d1.dtype.char == "O" or d2.dtype.char == "O":
        return np.equal(d1, d2).ravel()
    x = filled(masked_array(d1, copy=False, mask=m), fill_value).astype(float_)
    y = filled(masked_array(d2, copy=False, mask=m), 1).astype(float_)
    d = np.around(np.abs(x - y), decimal) <= 10.0 ** (-decimal)
    return d.ravel()
项目:quantum-computing    作者:QuantumSystems    | 项目源码 | 文件源码
def qreport(self, header="State", state=None, visualize=False):
        # This is only a simulator function for debugging. it CANNOT be done on a real Quantum Computer.
        if state == None:
            state = self.sys_state
        print
        print header
        for i in range(len(state)):
            if self.disp_zeros or np.absolute(state[i]) > self.maxerr:
                barlen = 20
                barstr = ""
                if self.visualize or visualize:
                    barstr = "  x"
                    amp = np.absolute(state[i].item(0))*barlen
                    intamp = int(amp)
                    if amp > self.maxerr:
                        barstr = "  |"
                        for b in range(barlen):
                            if b <= intamp:
                                barstr = barstr+"*"
                            else:
                                barstr = barstr + "."
                ststr = ("{:0"+str(self.nqbits)+"b}    ").format(i)
                ampstr = "{:.8f}".format(np.around(state[i].item(0),8))
                print ststr + ampstr + barstr
项目:TF-FaceLandmarkDetection    作者:mariolew    | 项目源码 | 文件源码
def genLandmarkMap(landmarks, shape=[39, 39]):
    '''Generate landmark map according to landmarks.
    Input params:
    landmarks: K x 2 float 
    shape: H x W
    Output:
    landmarkMap: H x W x K binary map. For each H x W
    map, there's only one location nearest to the landmark
    location filled with 1, else 0.'''

    landmarks = landmarks.reshape((-1, 2))
    landmarkMap = np.zeros(shape + [len(landmarks)])
    for (i, landmark) in enumerate(landmarks):
        x = int(np.around(landmark[0] * shape[1]))
        y = int(np.around(landmark[1] * shape[0]))
        landmarkMap[y, x, i] = 1
    return landmarkMap
项目:lambda-numba    作者:rlhotovy    | 项目源码 | 文件源码
def round_(a, decimals=0, out=None):
    """
    Round an array to the given number of decimals.

    Refer to `around` for full documentation.

    See Also
    --------
    around : equivalent function

    """
    try:
        round = a.round
    except AttributeError:
        return _wrapit(a, 'round', decimals, out)
    return round(decimals, out)
项目:ZOO-Attack    作者:huanzhang12    | 项目源码 | 文件源码
def show(img, name = "output.png"):
    """
    Show MNSIT digits in the console.
    """
    np.save(name, img)
    fig = np.around((img + 0.5)*255)
    fig = fig.astype(np.uint8).squeeze()
    pic = Image.fromarray(fig)
    # pic.resize((512,512), resample=PIL.Image.BICUBIC)
    pic.save(name)
    remap = "  .*#"+"#"*100
    img = (img.flatten()+.5)*3
    if len(img) != 784: return
    print("START")
    for i in range(28):
        print("".join([remap[int(round(x))] for x in img[i*28:i*28+28]]))