Python pyplot.table方法代码示例

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def plot_compare_table(image_list, method_list, color_list, compare_dict, fig_name="", fig_num=111):
    """绘制了对比表格."""
    row_labels = image_list
    # 写入值：
    table_vals = []
    for i in range(len(row_labels)):
        row_vals = []
        for method in method_list:
            row_vals.append(compare_dict[method][i])
        table_vals.append(row_vals)
    # 绘制表格图
    colors = [[(0.95, 0.95, 0.95) for c in range(len(method_list))] for r in range(len(row_labels))]  # cell的颜色
    # plt.figure(figsize=(8, 4), dpi=120)
    plt.subplot(fig_num)
    plt.title(fig_name)  # 绘制标题
    lightgrn = (0.5, 0.8, 0.5)  # 这个是label的背景色
    plt.table(cellText=table_vals,
              rowLabels=row_labels,
              colLabels=method_list,
              rowColours=[lightgrn] * len(row_labels),
              colColours=color_list,
              cellColours=colors,
              cellLoc='center',
              loc='upper left')

    plt.axis('off')  # 关闭坐标轴 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def plot(self):
        print(self.policy)
        plt.figure()
        plt.xlim(0, MAX_CARS + 1)
        plt.ylim(0, MAX_CARS + 1)
        plt.table(cellText=np.flipud(self.policy), loc=(0, 0), cellLoc='center')
        plt.show() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_zorder():
    data = [[66386, 174296],
            [58230, 381139]]

    colLabels = ('Freeze', 'Wind')
    rowLabels = ['%d year' % x for x in (100, 50)]

    cellText = []
    yoff = np.array([0.0] * len(colLabels))
    for row in reversed(data):
        yoff += row
        cellText.append(['%1.1f' % (x/1000.0) for x in yoff])

    t = np.linspace(0, 2*np.pi, 100)
    plt.plot(t, np.cos(t), lw=4, zorder=2)

    plt.table(cellText=cellText,
              rowLabels=rowLabels,
              colLabels=colLabels,
              loc='center',
              zorder=-2,
              )

    plt.table(cellText=cellText,
              rowLabels=rowLabels,
              colLabels=colLabels,
              loc='upper center',
              zorder=4,
              )
    plt.yticks([]) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_label_colours():
    dim = 3

    c = np.linspace(0, 1, dim)
    colours = plt.cm.RdYlGn(c)
    cellText = [['1'] * dim] * dim

    fig = plt.figure()

    ax1 = fig.add_subplot(4, 1, 1)
    ax1.axis('off')
    ax1.table(cellText=cellText,
              rowColours=colours,
              loc='best')

    ax2 = fig.add_subplot(4, 1, 2)
    ax2.axis('off')
    ax2.table(cellText=cellText,
              rowColours=colours,
              rowLabels=['Header'] * dim,
              loc='best')

    ax3 = fig.add_subplot(4, 1, 3)
    ax3.axis('off')
    ax3.table(cellText=cellText,
              colColours=colours,
              loc='best')

    ax4 = fig.add_subplot(4, 1, 4)
    ax4.axis('off')
    ax4.table(cellText=cellText,
              colColours=colours,
              colLabels=['Header'] * dim,
              loc='best') 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_bbox_inches_tight():
    #: Test that a figure saved using bbox_inches='tight' is clipped correctly
    data = [[ 66386, 174296,  75131, 577908,  32015],
            [ 58230, 381139,  78045,  99308, 160454],
            [ 89135,  80552, 152558, 497981, 603535],
            [ 78415,  81858, 150656, 193263,  69638],
            [139361, 331509, 343164, 781380,  52269]]

    colLabels = rowLabels = [''] * 5

    rows = len(data)
    ind = np.arange(len(colLabels)) + 0.3  # the x locations for the groups
    cellText = []
    width = 0.4     # the width of the bars
    yoff = np.array([0.0] * len(colLabels))
    # the bottom values for stacked bar chart
    fig, ax = plt.subplots(1, 1)
    for row in xrange(rows):
        plt.bar(ind, data[row], width, bottom=yoff)
        yoff = yoff + data[row]
        cellText.append([''])
    plt.xticks([])
    plt.legend([''] * 5, loc=(1.2, 0.2))
    # Add a table at the bottom of the axes
    cellText.reverse()
    the_table = plt.table(cellText=cellText,
                          rowLabels=rowLabels,
                          colLabels=colLabels, loc='bottom') 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def plot_op(ops, path, width=[], head_width=None, F_base=16):
    assert len(width) == 0 or len(width) == len(ops) - 1
    table_vals = []
    scales = {0: "1/8", 1: "1/16", 2: "1/32"}; base_scale = 3
    for idx, op in enumerate(ops):
        scale = path[idx]
        if len(width) > 0:
            if idx < len(width):
                ch = int(F_base*2**(scale+base_scale)*width[idx])
            else:
                ch = int(F_base*2**(scale+base_scale)*head_width)
        else:
            ch = F_base*2**(scale+base_scale)
        row = [idx+1, PRIMITIVES[op], scales[scale], ch]
        table_vals.append(row)

    # Based on http://stackoverflow.com/a/8531491/190597 (Andrey Sobolev)
    col_labels = ['Stage', 'Operator', 'Scale', '#Channel_out']
    plt.tight_layout()
    fig = plt.figure(figsize=(3,3))
    ax = fig.add_subplot(111, frame_on=False)
    ax.xaxis.set_visible(False)  # hide the x axis
    ax.yaxis.set_visible(False)  # hide the y axis

    table = plt.table(cellText=table_vals,
                          colWidths=[0.22, 0.6, 0.25, 0.5],
                          colLabels=col_labels,
                          cellLoc='center',
                          loc='center')
    table.auto_set_font_size(False)
    table.set_fontsize(20)
    table.scale(2, 2)

    return fig 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_non_square():
    # Check that creating a non-square table works
    cellcolors = ['b', 'r']
    plt.table(cellColours=cellcolors) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_zorder():
    data = [[66386, 174296],
            [58230, 381139]]

    colLabels = ('Freeze', 'Wind')
    rowLabels = ['%d year' % x for x in (100, 50)]

    cellText = []
    yoff = np.zeros(len(colLabels))
    for row in reversed(data):
        yoff += row
        cellText.append(['%1.1f' % (x/1000.0) for x in yoff])

    t = np.linspace(0, 2*np.pi, 100)
    plt.plot(t, np.cos(t), lw=4, zorder=2)

    plt.table(cellText=cellText,
              rowLabels=rowLabels,
              colLabels=colLabels,
              loc='center',
              zorder=-2,
              )

    plt.table(cellText=cellText,
              rowLabels=rowLabels,
              colLabels=colLabels,
              loc='upper center',
              zorder=4,
              )
    plt.yticks([]) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_diff_cell_table():
    cells = ('horizontal', 'vertical', 'open', 'closed', 'T', 'R', 'B', 'L')
    cellText = [['1'] * len(cells)] * 2
    colWidths = [0.1] * len(cells)

    _, axes = plt.subplots(nrows=len(cells), figsize=(4, len(cells)+1))
    for ax, cell in zip(axes, cells):
        ax.table(
                colWidths=colWidths,
                cellText=cellText,
                loc='center',
                edges=cell,
                )
        ax.axis('off')
    plt.tight_layout() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_bbox_inches_tight():
    #: Test that a figure saved using bbox_inches='tight' is clipped correctly
    data = [[66386, 174296, 75131, 577908, 32015],
            [58230, 381139, 78045, 99308, 160454],
            [89135, 80552, 152558, 497981, 603535],
            [78415, 81858, 150656, 193263, 69638],
            [139361, 331509, 343164, 781380, 52269]]

    colLabels = rowLabels = [''] * 5

    rows = len(data)
    ind = np.arange(len(colLabels)) + 0.3  # the x locations for the groups
    cellText = []
    width = 0.4     # the width of the bars
    yoff = np.zeros(len(colLabels))
    # the bottom values for stacked bar chart
    fig, ax = plt.subplots(1, 1)
    for row in range(rows):
        ax.bar(ind, data[row], width, bottom=yoff, align='edge', color='b')
        yoff = yoff + data[row]
        cellText.append([''])
    plt.xticks([])
    plt.legend([''] * 5, loc=(1.2, 0.2))
    # Add a table at the bottom of the axes
    cellText.reverse()
    the_table = plt.table(cellText=cellText,
                          rowLabels=rowLabels,
                          colLabels=colLabels, loc='bottom') 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def generate_tabular_sample(cls, dataset_name, dataset_class, data_location, sample_location):
        """
        Generates a jpg from a sample of the pandas DataFrame
        """

        extract_loc = '%sraw/%s' % (data_location, 'sample_extract')

        file_to_extract = dataset_class.data_file
        _ = cls.extract_data_files(dataset_name, dataset_class, data_location, sample_location, extract_loc, None)

        # define the core DataFrames
        file_type = file_to_extract.split('.')[-1] 
        if file_type == 'csv':
            df = pd.read_csv('%s/%s' % ('%s%s' % (data_location, 'raw/sample_extract'), file_to_extract)).head()
        else:
            df = pd.DataFrame()

        plt.figure()

        cell_text = []
        for row in range(len(df)):
            cell_text.append(df.iloc[row, :3])

        plt.table(cellText=cell_text, colLabels=df.columns[:3], loc='center')
        plt.axis('off')

        plt.savefig(sample_location)

        shutil.rmtree(extract_loc) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_bbox_inches_tight():
    #: Test that a figure saved using bbox_inches='tight' is clipped correctly
    data = [[66386, 174296, 75131, 577908, 32015],
            [58230, 381139, 78045, 99308, 160454],
            [89135, 80552, 152558, 497981, 603535],
            [78415, 81858, 150656, 193263, 69638],
            [139361, 331509, 343164, 781380, 52269]]

    colLabels = rowLabels = [''] * 5

    rows = len(data)
    ind = np.arange(len(colLabels)) + 0.3  # the x locations for the groups
    cellText = []
    width = 0.4     # the width of the bars
    yoff = np.zeros(len(colLabels))
    # the bottom values for stacked bar chart
    fig, ax = plt.subplots(1, 1)
    for row in range(rows):
        ax.bar(ind, data[row], width, bottom=yoff, color='b')
        yoff = yoff + data[row]
        cellText.append([''])
    plt.xticks([])
    plt.legend([''] * 5, loc=(1.2, 0.2))
    # Add a table at the bottom of the axes
    cellText.reverse()
    the_table = plt.table(cellText=cellText,
                          rowLabels=rowLabels,
                          colLabels=colLabels, loc='bottom') 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def test_auto_column():
    fig = plt.figure()

    # iterable list input
    ax1 = fig.add_subplot(4, 1, 1)
    ax1.axis('off')
    tb1 = ax1.table(cellText=[['Fit Text', 2],
          ['very long long text, Longer text than default', 1]],
          rowLabels=["A", "B"],
          colLabels=["Col1", "Col2"],
          loc="center")
    tb1.auto_set_font_size(False)
    tb1.set_fontsize(12)
    tb1.auto_set_column_width([-1, 0, 1])

    # iterable tuple input
    ax2 = fig.add_subplot(4, 1, 2)
    ax2.axis('off')
    tb2 = ax2.table(cellText=[['Fit Text', 2],
          ['very long long text, Longer text than default', 1]],
          rowLabels=["A", "B"],
          colLabels=["Col1", "Col2"],
          loc="center")
    tb2.auto_set_font_size(False)
    tb2.set_fontsize(12)
    tb2.auto_set_column_width((-1, 0, 1))

    #3 single inputs
    ax3 = fig.add_subplot(4, 1, 3)
    ax3.axis('off')
    tb3 = ax3.table(cellText=[['Fit Text', 2],
          ['very long long text, Longer text than default', 1]],
          rowLabels=["A", "B"],
          colLabels=["Col1", "Col2"],
          loc="center")
    tb3.auto_set_font_size(False)
    tb3.set_fontsize(12)
    tb3.auto_set_column_width(-1)
    tb3.auto_set_column_width(0)
    tb3.auto_set_column_width(1)

    #4 non integer interable input
    ax4 = fig.add_subplot(4, 1, 4)
    ax4.axis('off')
    tb4 = ax4.table(cellText=[['Fit Text', 2],
          ['very long long text, Longer text than default', 1]],
          rowLabels=["A", "B"],
          colLabels=["Col1", "Col2"],
          loc="center")
    tb4.auto_set_font_size(False)
    tb4.set_fontsize(12)
    tb4.auto_set_column_width("-101") 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import table [as 别名]
def plotHITStatus( savePath = '/home/ubuntu/amt_guis/cocoa_depth/plots/', filename = 'time_info' ):
    pdf = PdfPages( savePath + filename + '.pdf')
    fig = plt.figure()
    plt.clf()

    page_size = 100
    ass_time_info_list = []
    
    mtc = MTurkConnection( host = _host )
    assignments = getReviewableAssignments()

    for ass in assignments:
        time_info = \
        {'AcceptTime':ass.AcceptTime,
        'SubmitTime':ass.SubmitTime,
        'ExecutionTime': [ question_form_answer.fields[0] for question_form_answer in ass.answers[0] if question_form_answer.qid == '_hit_rt' ][0] }
            
        ass_time_info_list.append( time_info )
            
    ass_time_info_list.sort(key=lambda x: datetime.datetime.strptime(x['AcceptTime'],'%Y-%m-%dT%H:%M:%SZ'))
    first_assignment = ass_time_info_list[0]
    ass_time_info_list.sort(key=lambda x: datetime.datetime.strptime(x['SubmitTime'],'%Y-%m-%dT%H:%M:%SZ'))
    last_assignment = ass_time_info_list[-1]

    time_since_beginning = int(( datetime.datetime.strptime(last_assignment['SubmitTime'],'%Y-%m-%dT%H:%M:%SZ') - datetime.datetime.strptime(first_assignment['AcceptTime'],'%Y-%m-%dT%H:%M:%SZ')).total_seconds())
    completed_percentage = []
    # time since beginning in one hour intervals
    time_range = range( 0, time_since_beginning + 3600, 3600 )

    for s in time_range:
        currently_completed = \
            [x for x in ass_time_info_list if datetime.datetime.strptime(x['SubmitTime'],'%Y-%m-%dT%H:%M:%SZ') < datetime.timedelta(seconds=s) + datetime.datetime.strptime(first_assignment['SubmitTime'],'%Y-%m-%dT%H:%M:%SZ')] 
        perc = len( currently_completed ) / float( NUMBER_HITS * NUMBER_HIT_ASSIGNMENTS )
        completed_percentage.append( perc )

    per_hour_completion_rate = len(ass_time_info_list) / float(time_since_beginning / 3600)
    #print per_hour_completion_rate
    
    hours_to_completion = ((NUMBER_HITS * NUMBER_HIT_ASSIGNMENTS) - len(ass_time_info_list)) / per_hour_completion_rate
    #print hours_to_completion

    plt.plot( time_range, completed_percentage )
   
    rows = ['Completed Assignments','Total Assignments','Hour Completion Rate','Hours to Completion']
    data = [["%d"%(len(ass_time_info_list))],["%d"%(NUMBER_HITS * NUMBER_HIT_ASSIGNMENTS)],["%.2f" % per_hour_completion_rate],["%.2f" % hours_to_completion]]
    
    plt.table(cellText=data,rowLabels=rows,loc='center',colWidths = [0.1]*3)
    
    plt.title('Per hour completion percentage')
    
    plt.xticks( time_range[0::10], [str(x/3600) for x in time_range[0::10]] )
    plt.yticks([0,0.2,0.4,0.6,0.8,1],['0%', '20%','40%','60%','80%','100%'])
    
    plt.ylabel('Completion Percentage')
    plt.xlabel('Hours since beginning of task')

    plt.grid()
    pdf.savefig()
    pdf.close()
    plt.close()